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Marketing automation

Marketing automation refers to software platforms and technologies designed for marketing departments and organizations to more effectively market on multiple channels online (such as email, social media, websites, etc.) and automate repetitive tasks.[1] Marketing departments, consultants and part-time marketing employees benefit by specifying criteria and outcomes for tasks and processes which are then interpreted, stored and executed by software, which increases efficiency and reduces human error.

Originally focused on email Marketing automation, Marketing automation refers to a broad range of automation and analytic tools for marketing[2] especially inbound marketing.

Marketing automation platforms are used as a hosted or web-based solution, and no software installation is required by a customer.

The use of a Marketing automation platform is to streamline sales and marketing organizations by replacing high-touch, repetitive manual processes with automated solutions.[3] Marketing automation is a platform that marketers use to plan, coordinate, manage and measure all of their marketing campaigns, both online and offline.

It is often used along with lifecycle marketing strategy to closely manage and nurture generated leads, aiming to convert leads into customers.[citation needed] Marketing automation is a subset of customer relationship management (CRM) or customer experience management (CXM) that focuses on the definition, segmentation, scheduling and tracking of marketing campaigns.

The use of Marketing automation makes processes that would otherwise have been performed manually much more efficient and makes new processes possible.

Marketing automation can be defined as a process where technology is used to automate several repetitive tasks that are undertaken on a regular basis in a marketing campaign.

A tool that allows an individual to design, execute and automate a time-bound marketing workflow can be called a Marketing automation platform.[citation needed] Marketing automation platforms allow marketers to automate and simplify client communication by managing complex omni-channel marketing strategies from a single tool.

Marketing automation assists greatly in areas like Lead Generation, Segmentation, Lead nurturing and lead scoring, Relationship marketing, Cross-sell and upsell, Retention, Marketing ROI measurement.

There are three categories of Marketing automation software: As of 25th May 2018 the General Data Protection Regulation came into effect, [5] this has had a large impact on the way marketing teams and organizations can manage their consumer data.

Any organization using Marketing automation tracking is required to ask consent from the consumer as well as provide transparency on how the data will be processed.

In order to effectively aid marketers in fully understanding customers and subsequently developing a strategic marketing plan, Marketing automation tools (MAT) are designed to perform eight key tasks:[6][verification needed]

Inbound marketing automation

Mobile marketing automation

Digital marketing

Digital marketing is the component of marketing that utilizes internet and online based digital technologies such as desktop computers, mobile phones and other digital media and platforms to promote products and services.[1][2] Its development during the 1990s and 2000s, changed the way brands and businesses use technology for marketing.

As digital platforms became increasingly incorporated into marketing plans and everyday life,[3] and as people increasingly use digital devices instead of visiting physical shops,[4][5] Digital marketing campaigns have become prevalent, employing combinations of search engine optimization (SEO), search engine marketing (SEM), content marketing, influencer marketing, content automation, campaign marketing, data-driven marketing, e-commerce marketing, social media marketing, social media optimization, e-mail direct marketing, display advertising, e–books, and optical disks and games have become commonplace.

Digital marketing extends to non-Internet channels that provide digital media, such as television, mobile phones (SMS and MMS), callback, and on-hold mobile ring tones.[6] The extension to non-Internet channels differentiates Digital marketing from online marketing.[7] The development of Digital marketing is inseparable from technology development.

One of the key points in the start of was in 1971, where Ray Tomlinson sent the very first email and his technology set the platform to allow people to send and receive files through different machines.[8] However, the more recognisable period as being the start of Digital marketing is 1990 as this was where the Archie search engine was created as an index for FTP sites.

In the 1980s, the storage capacity of computer was already big enough to store huge volumes of customer information.

Companies started choosing online techniques, such as database marketing, rather than limited list broker.[9] These kinds of databases allowed companies to track customers' information more effectively, thus transforming the relationship between buyer and seller.

However, the manual process was not as efficient.

In the 1990s, the term Digital marketing was first coined,.[10] With the debut of server/client architecture and the popularity of personal computers, the Customer Relationship Management (CRM) applications became a significant factor in marketing technology.[11] Fierce competition forced vendors to include more service into their software, for example, marketing, sales and service applications.

Marketers were also able to own huge online customer data by eCRM software after the Internet was born.

Companies could update the data of customer needs and obtain the priorities of their experience.

This led to the first clickable banner ad being going live in 1994, which was the "You Will" campaign by AT&T and over the first four months of it going live, 44% of all people who saw it clicked on the ad.[12][13] In the 2000s, with increasing numbers of Internet users and the birth of iPhone, customers began searching products and making decisions about their needs online first, instead of consulting a salesperson, which created a new problem for the marketing department of a company.[14] In addition, a survey in 2000 in the United Kingdom found that most retailers had not registered their own domain address.[15] These problems encouraged marketers to find new ways to integrate digital technology into market development.

In 2007, marketing automation was developed as a response to the ever evolving marketing climate.

Marketing automation is the process by which software is used to automate conventional marketing processes.[16] Marketing automation helped companies segment customers, launch multichannel marketing campaigns, and provide personalized information for customers.[16] However, the speed of its adaptability to consumer devices was not fast enough.

Digital marketing became more sophisticated in the 2000s and the 2010s, when[17][18] the proliferation of devices' capable of accessing digital media led to sudden growth.[19] Statistics produced in 2012 and 2013 showed that Digital marketing was still growing.[20][21] With the development of social media in the 2000s, such as LinkedIn, Facebook, YouTube and Twitter, consumers became highly dependent on digital electronics in daily lives.

Therefore, they expected a seamless user experience across different channels for searching product's information.

The change of customer behavior improved the diversification of marketing technology.[22] Digital marketing is also referred to as 'online marketing', 'internet marketing' or 'web marketing'.

The term Digital marketing has grown in popularity over time.

In the USA online marketing is still a popular term.

In Italy, Digital marketing is referred to as web marketing.

Worldwide Digital marketing has become the most common term, especially after the year 2013.[23] Digital media growth was estimated at 4.5 trillion online ads served annually with digital media spend at 48% growth in 2010.[24] An increasing portion of advertising stems from businesses employing Online Behavioural Advertising (OBA) to tailor advertising for internet users, but OBA raises concern of consumer privacy and data protection.[19] Nonlinear marketing, a type of interactive marketing, is a long-term marketing approach which builds on businesses collecting information about an Internet user's online activities, and trying to be visible in multiple areas.[25][26] Unlike traditional marketing techniques, which involve direct, one-way messaging to consumers (via print, television and radio advertising), nonlinear Digital marketing strategies are centered on reaching prospective customers across multiple online channels.[27] Combined with higher consumer knowledge and the demand for more sophisticated consumer offerings, this change has forced many businesses to rethink their outreach strategy and adopt or incorporate omnichannel, nonlinear marketing techniques to maintain sufficient brand exposure, engagement and reach.[28] Nonlinear marketing strategies involve efforts to adapt the advertising to different platforms,[29] and to tailor the advertising to different individual buyers rather than a large coherent audience.[26] Tactics may include: Some studies indicate that consumer responses to traditional marketing approaches are becoming less predictable for businesses.[30] According to a 2018 study, nearly 90% of online consumers in the United States researched products and brands online before visiting the store or making a purchase.[31] The Global Web Index estimated that in 2018, a little more than 50% of consumers researched products on social media.[32] Businesses often rely on individuals portraying their products in a positive light on social media, and may adapt their marketing strategy to target people with large social media followings in order to generate such comments.[33] In this manner, businesses can use consumers to advertise their products or services, decreasing the cost for the company.[34] One of the key objectives of modern Digital marketing is to raise brand awareness, the extent to which customers and the general public are familiar with and recognize a particular brand.

Enhancing brand awareness is important in Digital marketing, and marketing in general, because of its impact on brand perception and consumer decision-making.

According to the 2015 essay, “Impact of Brand on Consumer Behavior”: “Brand awareness, as one of the fundamental dimensions of brand equity, is often considered to be a prerequisite of consumers’ buying decision, as it represents the main factor for including a brand in the consideration set.

Brand awareness can also influence consumers’ perceived risk assessment and their confidence in the purchase decision, due to familiarity with the brand and its characteristics.”[35] Recent trends show that businesses and digital marketers are prioritizing brand awareness, focusing more of their Digital marketing efforts on cultivating brand recognition and recall than in previous years.

This is evidenced by a 2019 Content Marketing Institute study, which found that 81% of digital marketers have worked on enhancing brand recognition over the past year.[36] Another Content Marketing Institute survey revealed 89% of B2B marketers now believe improving brand awareness to be more important than efforts directed at increasing sales.[37] Increasing brand awareness is a focus of Digital marketing strategy for a number of reasons: Digital marketing strategies may include the use of one or more online channels and techniques (omnichannel) to increase brand awareness among consumers.[45] Building brand awareness may involve such methods/tools as: Search engine optimization techniques may be used to improve the visibility of business websites and brand-related content for common industry-related search queries.[46] The importance of SEO to increasing brand awareness is said to correlate with the growing influence of search results and search features like featured snippets, knowledge panels and local SEO on customer behavior.[47] SEM, also known as PPC advertising, involves the purchase of ad space in prominent, visible positions atop search results pages and websites.

Search ads have been shown to have a positive impact on brand recognition, awareness and conversions.[48] 33% of searchers who click on paid ads do so because they directly respond to their particular search query.[49] 70% of marketers list increasing brand awareness as their number one goal for marketing on social media platforms.

Facebook, Instagram, Twitter and YouTube are listed as the top platforms currently used by social media marketing teams.[50] 56% of marketers believe personalized content – brand-centered blogs, articles, social updates, videos, landing pages – improves brand recall and engagement.[51] According to Mentionlytics, an active and consistent content strategy that incorporates elements of interactive content creation, social posting and guest blogging can improve brand awareness and loyalty by 88%.[52] One of the major changes that occurred in traditional marketing was the "emergence of Digital marketing" (Patrutiu Baltes, Loredana, 2015), this led to the reinvention of marketing strategies in order to adapt to this major change in traditional marketing (Patrutiu Baltes, Loredana, 2015).

As Digital marketing is dependent on technology which is ever-evolving and fast-changing, the same features should be expected from Digital marketing developments and strategies.

This portion is an attempt to qualify or segregate the notable highlights existing and being used as of press time.[when?] To summarize, Pull Digital marketing is characterized by consumers actively seeking marketing content while Push Digital marketing occurs when marketers send messages without that content being actively sought by the recipients.

An important consideration today while deciding on a strategy is that the digital tools have democratized the promotional landscape.

The new digital era has enabled brands to selectively target their customers that may potentially be interested in their brand or based on previous browsing interests.

Businesses can now use social media to select the age range, location, gender and interests of whom they would like their targeted post to be seen by.

Furthermore, based on a customer's recent search history they can be ‘followed’ on the internet so they see advertisements from similar brands, products and services,[58] This allows businesses to target the specific customers that they know and feel will most benefit from their product or service, something that had limited capabilities up until the digital era.

Digital marketing activity is still growing across the world according to the headline global marketing index.

A study published in September 2018, found that global outlays on Digital marketing tactics are approaching $100 billion.[59] Digital media continues to rapidly grow; while the marketing budgets are expanding, traditional media is declining (World Economics, 2015).[60] Digital media helps brands reach consumers to engage with their product or service in a personalised way.

Five areas, which are outlined as current industry practices that are often ineffective are prioritizing clicks, balancing search and display, understanding mobiles, targeting, viewability, brand safety and invalid traffic, and cross-platform measurement (Whiteside, 2016).[61] Why these practices are ineffective and some ways around making these aspects effective are discussed surrounding the following points.

Prioritizing clicks refers to display click ads, although advantageous by being ‘simple, fast and inexpensive’ rates for display ads in 2016 is only 0.10 percent in the United States.

This means one in a thousand click ads are relevant therefore having little effect.

This displays that marketing companies should not just use click ads to evaluate the effectiveness of display advertisements (Whiteside, 2016).[61] Balancing search and display for digital display ads are important; marketers tend to look at the last search and attribute all of the effectiveness to this.

This, in turn, disregards other marketing efforts, which establish brand value within the consumers mind.

ComScore determined through drawing on data online, produced by over one hundred multichannel retailers that digital display marketing poses strengths when compared with or positioned alongside, paid search (Whiteside, 2016).[61] This is why it is advised that when someone clicks on a display ad the company opens a landing page, not its home page.

A landing page typically has something to draw the customer in to search beyond this page.

Things such as free offers that the consumer can obtain through giving the company contact information so that they can use retargeting communication strategies (Square2Marketing, 2012).[62] Commonly marketers see increased sales among people exposed to a search ad.

But the fact of how many people you can reach with a display campaign compared to a search campaign should be considered.

Multichannel retailers have an increased reach if the display is considered in synergy with search campaigns.

Overall both search and display aspects are valued as display campaigns build awareness for the brand so that more people are likely to click on these digital ads when running a search campaign (Whiteside, 2016).[61] Understanding Mobiles: Understanding mobile devices is a significant aspect of Digital marketing because smartphones and tablets are now responsible for 64% of the time US consumers are online (Whiteside, 2016).[61] Apps provide a big opportunity as well as challenge for the marketers because firstly the app needs to be downloaded and secondly the person needs to actually use it.

This may be difficult as ‘half the time spent on smartphone apps occurs on the individuals single most used app, and almost 85% of their time on the top four rated apps’ (Whiteside, 2016).[61] Mobile advertising can assist in achieving a variety of commercial objectives and it is effective due to taking over the entire screen, and voice or status is likely to be considered highly; although the message must not be seen or thought of as intrusive (Whiteside, 2016).[61] Disadvantages of digital media used on mobile devices also include limited creative capabilities, and reach.

Although there are many positive aspects including the users entitlement to select product information, digital media creating a flexible message platform and there is potential for direct selling (Belch & Belch, 2012).[63] Cross-platform measurement: The number of marketing channels continues to expand, as measurement practices are growing in complexity.

A cross-platform view must be used to unify audience measurement and media planning.

Market researchers need to understand how the Omni-channel affects consumer's behaviour, although when advertisements are on a consumer's device this does not get measured.

Significant aspects to cross-platform measurement involves deduplication and understanding that you have reached an incremental level with another platform, rather than delivering more impressions against people that have previously been reached (Whiteside, 2016).[61] An example is ‘ESPN and comScore partnered on Project Blueprint discovering the sports broadcaster achieved a 21% increase in unduplicated daily reach thanks to digital advertising’ (Whiteside, 2016).[61] Television and radio industries are the electronic media, which competes with digital and other technological advertising.

Yet television advertising is not directly competing with online digital advertising due to being able to cross platform with digital technology.

Radio also gains power through cross platforms, in online streaming content.

Television and radio continue to persuade and affect the audience, across multiple platforms (Fill, Hughes, & De Franceso, 2013).[64] Targeting, viewability, brand safety and invalid traffic: Targeting, viewability, brand safety and invalid traffic all are aspects used by marketers to help advocate digital advertising.

Cookies are a form of digital advertising, which are tracking tools within desktop devices; causing difficulty, with shortcomings including deletion by web browsers, the inability to sort between multiple users of a device, inaccurate estimates for unique visitors, overstating reach, understanding frequency, problems with ad servers, which cannot distinguish between when cookies have been deleted and when consumers have not previously been exposed to an ad.

Due to the inaccuracies influenced by cookies, demographics in the target market are low and vary (Whiteside, 2016).[61] Another element, which is affected within Digital marketing, is ‘viewabilty’ or whether the ad was actually seen by the consumer.

Many ads are not seen by a consumer and may never reach the right demographic segment.

Brand safety is another issue of whether or not the ad was produced in the context of being unethical or having offensive content.

Recognizing fraud when an ad is exposed is another challenge marketers face.

This relates to invalid traffic as premium sites are more effective at detecting fraudulent traffic, although non-premium sites are more so the problem (Whiteside, 2016).[61] Digital marketing Channels are systems based on the Internet that can create, accelerate, and transmit product value from producer to a consumer terminal, through digital networks.[65][66] Digital marketing is facilitated by multiple Digital marketing channels, As an advertiser one's core objective is to find channels which result in maximum two-way communication and a better overall ROI for the brand.

There are multiple Digital marketing channels available namely;[67] It is important for a firm to reach out to consumers and create a two-way communication model, as Digital marketing allows consumers to give back feed back to the firm on a community based site or straight directly to the firm via email.[80] Firms should seek this long term communication relationship by using multiple forms of channels and using promotional strategies related to their target consumer as well as word-of mouth marketing.[80] The ICC Code has integrated rules that apply to marketing communications using digital interactive media throughout the guidelines.

There is also an entirely updated section dealing with issues specific to digital interactive media techniques and platforms.

Code self-regulation on use of digital interactive media includes: Digital marketing planning is a term used in marketing management.

It describes the first stage of forming a Digital marketing strategy for the wider Digital marketing system.

The difference between digital and traditional marketing planning is that it uses digitally based communication tools and technology such as Social, Web, Mobile, Scannable Surface.[84][85] Nevertheless, both are aligned with the vision, the mission of the company and the overarching business strategy.[86] Using Dr Dave Chaffey's approach, the Digital marketing planning (DMP) has three main stages: Opportunity, Strategy and Action.

He suggests that any business looking to implement a successful Digital marketing strategy must structure their plan by looking at opportunity, strategy and action.

This generic strategic approach often has phases of situation review, goal setting, strategy formulation, resource allocation and monitoring.[86] To create an effective DMP, a business first needs to review the marketplace and set 'SMART' (Specific, Measurable, Actionable, Relevant and Time-Bound) objectives.[87] They can set SMART objectives by reviewing the current benchmarks and key performance indicators (KPIs) of the company and competitors.

It is pertinent that the analytics used for the KPIs be customised to the type, objectives, mission and vision of the company.[88][89] Companies can scan for marketing and sales opportunities by reviewing their own outreach as well as influencer outreach.

This means they have competitive advantage because they are able to analyse their co-marketers influence and brand associations.[90] To cease opportunity, the firm should summarize their current customers' personas and purchase journey from this they are able to deduce their Digital marketing capability.

This means they need to form a clear picture of where they are currently and how many resources they can allocate for their Digital marketing strategy i.e.

labour, time etc.

By summarizing the purchase journey, they can also recognise gaps and growth for future marketing opportunities that will either meet objectives or propose new objectives and increase profit.

To create a planned digital strategy, the company must review their digital proposition (what you are offering to consumers) and communicate it using digital customer targeting techniques.

So, they must define online value proposition (OVP), this means the company must express clearly what they are offering customers online e.g.

brand positioning.

The company should also (re)select target market segments and personas and define digital targeting approaches.

After doing this effectively, it is important to review the marketing mix for online options.

The marketing mix comprises the 4Ps – Product, Price, Promotion and Place.[91][92] Some academics have added three additional elements to the traditional 4Ps of marketing Process, Place and Physical appearance making it 7Ps of marketing.[93] The third and final stage requires the firm to set a budget and management systems; these must be measurable touchpoints, such as audience reached across all digital platforms.

Furthermore, marketers must ensure the budget and management systems are integrating the paid, owned and earned media of the company.[94] The Action and final stage of planning also requires the company to set in place measurable content creation e.g.

oral, visual or written online media.[95] After confirming the Digital marketing plan, a scheduled format of digital communications (e.g.

Gantt Chart) should be encoded throughout the internal operations of the company.

This ensures that all platforms used fall in line and complement each other for the succeeding stages of Digital marketing strategy.

One way marketers can reach out to consumers, and understand their thought process is through what is called an empathy map.

An empathy map is a four step process.

The first step is through asking questions that the consumer would be thinking in their demographic.

The second step is to describe the feelings that the consumer may be having.

The third step is to think about what the consumer would say in their situation.

The final step is to imagine what the consumer will try to do based on the other three steps.

This map is so marketing teams can put themselves in their target demographics shoes.[96] Web Analytics are also a very important way to understand consumers.

They show the habits that people have online for each website.[97] One particular form of these analytics is predictive analytics which helps marketers figure out what route consumers are on.

This uses the information gathered from other analytics, and then creates different predictions of what people will do so that companies can strategize on what to do next, according to the peoples trends.[98] The "sharing economy" refers to an economic pattern that aims to obtain a resource that is not fully utilized.[101] Nowadays, the sharing economy has had an unimagined effect on many traditional elements including labor, industry, and distribution system.[101] This effect is not negligible that some industries are obviously under threat.[101][102] The sharing economy is influencing the traditional marketing channels by changing the nature of some specific concept including ownership, assets, and recruitment.[102] Digital marketing channels and traditional marketing channels are similar in function that the value of the product or service is passed from the original producer to the end user by a kind of supply chain.[103] Digital marketing channels, however, consist of internet systems that create, promote, and deliver products or services from producer to consumer through digital networks.[104] Increasing changes to marketing channels has been a significant contributor to the expansion and growth of the sharing economy.[104] Such changes to marketing channels has prompted unprecedented and historic growth.[104] In addition to this typical approach, the built-in control, efficiency and low cost of Digital marketing channels is an essential features in the application of sharing economy.[103] Digital marketing channels within the sharing economy are typically divided into three domains including, e-mail, social media, and search engine marketing or SEM.[104] Other emerging Digital marketing channels, particularly branded mobile apps, have excelled in the sharing economy.[104] Branded mobile apps are created specifically to initiate engagement between customers and the company.This engagement is typically facilitated through entertainment, information, or market transaction.[104]

Salesforce Marketing Cloud

Salesforce Marketing Cloud is a provider of digital marketing automation and analytics software and services.

It was founded in 2000 under the name ExactTarget.

The company filed for an IPO in 2007, but withdrew its filing two years later and raised $145 million in funding.

It acquired CoTweet, Pardot, iGoDigital and Keymail Marketing.

In 2012, it raised $161.5 million in an initial public offering, before being acquired by Salesforce for $2.5 billion in 2013.

ExactTarget was renamed to Salesforce Marketing Cloud in 2014 after the acquisition by Salesforce.

Salesforce Marketing Cloud was founded under the name ExactTarget in late 2000 by Scott Dorsey, Chris Baggott, and Peter McCormick with $200,000 in financing.[4][5] Joanna Milliken joined ExactTarget as the first employee in 2001.[6] It raised $10.5 million in funding from Insight Venture Partners in 2004.[7] The firm grew from $11.5 million in its second year of operations to $41.1 million in 2006, which was its first profitable year.[8] In December 2007, ExactTarget filed an intent for an initial public offering with the Securities Exchange Commission,[9] but withdrew its filing in May 2009.[7] Instead, it announced that $70 million in venture funding had been raised for international expansion, which was followed by another $75 million round later that year.[7][10][11][12] An office was established in London[13] with the acquisition of a UK-based ExactTarget reseller, Keymail Marketing, in September 2009.[14][15] The company hired 200 additional employees.[7] In 2010, ExactTarget acquired CoTweet, a company founded in 2008 that develops and markets software for managing multiple Twitter accounts.[16] ExactTarget went public in March 2012[17] and raised $161.5 million in funding on the New York Stock Exchange.[18] In late 2012, it acquired a marketing automation vendor, Pardot, for $96 million, and the developers of a product recommendation engine, iGoDigital, for $21 million.[4][19] In 2012, its revenues grew 40 percent over the preceding year.[20] The following June, ExactTarget was acquired by salesforce.com for $2.5 billion.[21] A few months later, salesforce.com said it was laying off 200 staff due to overlaps after the ExactTarget acquisition.[22] That September at the ExactTarget Connections conference, salesforce.com said it was integrating ExactTarget into a new division called Salesforce ExactTarget Marketing Cloud.[23] In May 2014, Scott Dorsey stepped down as CEO of ExactTarget and was replaced by Scott McCorkle.[24] The company was renamed in October 2014 to "Salesforce Marketing Cloud", removing "ExactTarget" from its name, as part of its integration with Salesforce.[25] Salesforce has great plans to move Marketing Cloud to Microsoft Azure.[26] Salesforce Marketing Cloud develops marketing automation and analytics software for email, mobile, social and online marketing.

It also offers consulting and implementation services.[27] The software is sold primarily on a multi-year subscription basis.

The price of the subscription is based on what features are enabled, number of users and level of customer service.[28] The software's Interactive Marketing Hub was released in 2010, when the software's user interface was re-done.

It serves as the software's primary user interface for managing communications and content through different media.[29][30][31] The Salesforce Marketing Cloud software is offered in a hosted, online subscription model.[9] The company owns the CoTweet,[30] Pardot, and iGoDigital tools.

Its mobile features, as well as many of its workflow and collaboration tools, were released in July 2013.[32] Salesforce Marketing Cloud was founded as an email marketing vendor.[7] Its email management software maintains mailing lists and schedules[33] and modifies email messages based on what recipients read, click-on or forward.[34][35] In September 2014 the company introduced the Journey Builder for Apps, which is intended to create customer lifecycle maps of mobile app users.[36] That month, at the September 2014 ExactTarget Connections conference, they announced numerous updates to their software.

This included integration with software products owned by Salesforce.com, such as Buddy Media and Social Studio, as well as improvements to workflow and content management tools.[37] In November 2014 the company released a new version of Social Studio.

This release expanded Social Studio beyond Salesforce's Marketing Cloud, where it started, integrating it with the Service Cloud and the Sales Cloud.

This enabled sending leads over to the Sales Cloud — the salesperson can see the full context of the company's social media interactions with the lead.[38] As of December 2012, about two thirds of ExactTarget's 1,500 employees were located in Indianapolis.[4] The company hosts an annual user conference called Salesforce Connections, previously the ExactTarget Connections Event.[39] The first Connections event in 2007 attracted 500 attendees, and it has since grown into one of the largest conferences on digital marketing.

The event was located in Indianapolis from 2007 until 2014, New York City in 2015, and Atlanta in 2016.

It did not occur in 2017 as it was merged with world tours, and was brought back in Chicago in 2018.[40] As of April 28, 2016 the conference was renamed Salesforce Connections.[41] It merged with Salesforce World Tour in 2017.[42]

Voice-based marketing automation

Voice-based marketing automation (VBMA) refers to software platforms designed for marketing, sales, and support departments to measure, manage, and automate their phone conversations.

Marketing departments, sales teams, and support agents use VBMA to initiate, manage, monitor, track, route, record, and report on sales and support phone conversations.[1] VBMA encompasses a wide range of automation and analytics tools.

It is used as a standalone solution and as a way to complement the functionality found in traditional marketing automation software.[2] Voice-based marketing automation platforms have emerged as an integrated solution in response to both the growth in mobile users[3] and mobile advertising.[4] It is estimated that mobile search will generate 73 billion calls to businesses (up from 30 billion in 2013) and businesses are placing more value on phone calls as a lead source, as is evident from the estimated $64.6 billion spent annually on ads to generate phone calls.[5] With Google's call-only ad type, businesses were able to general billions of calls through mobile search.

In 2015, mobile search drove 48 percent of calls.[6] Advances in call analytics have been made to provide businesses deeper insights to measure and optimize inbound calls.[7] Voice-based marketing automation software consists of the following core pieces of functionality: There are three types of groups who use Voice-based marketing automation software:

Customer relationship management

Customer relationship management (CRM) is an approach to managing a company's interaction with current and potential customers.

It uses data analysis about customers' history with a company to improve business relationships with customers, specifically focusing on customer retention and ultimately driving sales growth.[1] One important aspect of the CRM approach is the systems of CRM that compile data from a range of different communication channels, including a company's website, telephone, email, live chat, marketing materials and more recently, social media.[2] Through the CRM approach and the systems used to facilitate it, businesses learn more about their target audiences and how to best cater to their needs.

The concept of Customer relationship management started in the early 1970s, when customer satisfaction was evaluated using annual surveys or by front-line asking.[3] At that time, businesses had to rely on standalone mainframe systems to automate sales, but the extent of technology allowed them to categorize customers in spreadsheets and lists.

In 1982, Kate and Robert D.

Kestnbaum introduced the concept of Database marketing, namely applying statistical methods to analyze and gather customer data.[citation needed] By 1986, Pat Sullivan and Mike Muhney released a customer evaluation system called ACT! based on the principle of digital rolodex, which offered a contact management service for the first time.

The trend was followed by numerous companies and independent developers trying to maximize leads' potential, including Tom Siebel, who designed the first CRM product Siebel Systems in 1993.[4] In order to compete with these new and quickly growing stand-alone CRM solutions the established enterprise resource planning (ERP) software companies like Oracle, SAP,[5] Peoplesoft and Navision[6] started extending their sales, distribution and customer service capabilities with embedded CRM modules.

This included embedding sales force automation or extended customer service (e.g.

inquiry, activity management) as CRM features in their ERP.

Customer relationship management was popularized in 1997, due to the work of Siebel, Gartner, and IBM.

Between 1997 and 2000, leading CRM products were enriched with shipping and marketing capabilities.[7] Siebel introduced the first mobile CRM app called Siebel Sales Handheld in 1999.

The idea of a stand-alone, cloud-hosted and moveable customer bases was soon adopted by other leading providers at the time, including PeopleSoft, Oracle, SAP and Salesforce.com.[8] The first open-source CRM system was developed by SugarCRM in 2004.

During this period, CRM was rapidly migrating to cloud, as a result of which it became accessible to sole entrepreneurs and small teams.

This increase in accessibility generated a huge wave of price reduction.[7] Around 2009, developers began considering the options to profit from social media's momentum, and designed tools to help companies become accessible on all users' favorite networks.

Many startups at the time benefited from this trend to provide exclusively social CRM solutions, including Base and Nutshell.[7] The same year, Gartner organized and held the first Customer relationship management Summit, and summarized the features systems should offer to be classified as CRM solutions.[9] In 2013 and 2014, most of the popular CRM products were linked to business intelligence systems and communication software to improve corporate communication and end-users' experience.

The leading trend is to replace standardized CRM solutions with industry-specific ones, or to make them customizable enough to meet the needs of every business.[10] In November 2016, Forrester released a report where it "identified the nine most significant CRM suites from eight prominent vendors".[11] Strategic CRM is concentrated upon the development of a customer-centric business culture.[12] The primary goal of Customer relationship management systems is to integrate and automate sales, marketing, and customer support.

Therefore, these systems typically have a dashboard that gives an overall view of the three functions on a single customer view, a single page for each customer that a company may have.

The dashboard may provide client information, past sales, previous marketing efforts, and more, summarizing all of the relationships between the customer and the firm.

Operational CRM is made up of 3 main components: sales force automation, marketing automation, and service automation.[13] The role of analytical CRM systems is to analyze customer data collected through multiple sources and present it so that business managers can make more informed decisions.[17] Analytical CRM systems use techniques such as data mining, correlation, and pattern recognition to analyze the customer data.

These analytics help improve customer service by finding small problems which can be solved, perhaps by marketing to different parts of a consumer audience differently.[13] For example, through the analysis of a customer base's buying behavior, a company might see that this customer base has not been buying a lot of products recently.

After scanning through this data, the company might think to market to this subset of consumers differently, in order to best communicate how this company's products might benefit this group specifically.[18] The third primary aim of CRM systems is to incorporate external stakeholders such as suppliers, vendors, and distributors, and share customer information across groups/departments and organisations.

For example, feedback can be collected from technical support calls, which could help provide direction for marketing products and services to that particular customer in the future.[19] A customer data platform (CDP) is a computer system used by marketing departments that assembles data about individual people from various sources into one database, with which other software systems can interact.[20] As of February 2017 there were about twenty companies selling such systems and revenue for them was around US$300 million.[20] The main components of CRM are building and managing customer relationships through marketing, observing relationships as they mature through distinct phases, managing these relationships at each stage and recognizing that the distribution of value of a relationship to the firm is not homogeneous.

When building and managing customer relationships through marketing, firms might benefit from using a variety of tools to help organizational design, incentive schemes, customer structures, and more to optimize the reach of its marketing campaigns.

Through the acknowledgement of the distinct phases of CRM, businesses will be able to benefit from seeing the interaction of multiple relationships as connected transactions.

The final factor of CRM highlights the importance of CRM through accounting for the profitability of customer relationships.

Through studying the particular spending habits of customers, a firm may be able to dedicate different resources and amounts of attention to different types of consumers.[21] Relational Intelligence, or awareness of the variety of relationships a customer can have with a firm, is an important component to the main phases of CRM.

Companies may be good at capturing demographic data, such as gender, age, income, and education, and connecting them with purchasing information to categorize customers into profitability tiers, but this is only a firm's mechanical view of customer relationships.[22] This therefore is a sign that firms believe that customers are still resources that can be used for up-sell or cross-sell opportunities, rather than humans looking for interesting and personalized interactions.[23] CRM systems include: Customer satisfaction has important implications for the economic performance of firms because it has the ability to increase customer loyalty and usage behavior and reduce customer complaints and the likelihood of customer defection.[25][26] The implementation of a CRM approach is likely to have an effect on customer satisfaction and customer knowledge for a variety of different reasons.

Firstly, firms are able to customize their offerings for each customer.[27] By accumulating information across customer interactions and processing this information to discover hidden patterns, CRM applications help firms customize their offerings to suit the individual tastes of their customers.[27] This customization enhances the perceived quality of products and services from a customer's viewpoint, and because perceived quality is a determinant of customer satisfaction, it follows that CRM applications indirectly affect customer satisfaction.

CRM applications also enable firms to provide timely, accurate processing of customer orders and requests and the ongoing management of customer accounts.[27] For example, Piccoli and Applegate discuss how Wyndham uses IT tools to deliver a consistent service experience across its various properties to a customer.

Both an improved ability to customize and a reduced variability of the consumption experience enhance perceived quality, which in turn positively affects customer satisfaction.[28] Furthermore, CRM applications also help firms manage customer relationships more effectively across the stages of relationship initiation, maintenance, and termination.[29] With Customer relationship management systems, customers are served better on day to day process.

With more reliable information, their demand for self service from companies will decrease.

If there is less need to interact with the company for different problems, customer satisfaction level increases.[30] These central benefits of CRM will be connected hypothetically to the three kinds of equity that are relationship, value, and brand, and in the end to customer equity.

Eight benefits were recognized to provide value drivers.[31] In 2012, after reviewing the previous studies, someone selected some of those benefits which are more significant in customer's satisfaction and summarized them into the following cases:[32] Research has found a 5% increase in customer retention boosts lifetime customer profits by 50% on average across multiple industries, as well as a boost of up to 90% within specific industries such as insurance.[39] Companies that have mastered customer relationship strategies have the most successful CRM programs.

For example, MBNA Europe has had a 75% annual profit growth since 1995.

The firm heavily invests in screening potential cardholders.

Once proper clients are identified, the firm retains 97% of its profitable customers.

They implement CRM by marketing the right products to the right customers.

The firm's customers' card usage is 52% above industry norm, and the average expenditure is 30% more per transaction.

Also 10% of their account holders ask for more information on cross-sale products.[39] Amazon has also seen great success through its customer proposition.

The firm implemented personal greetings, collaborative filtering, and more for the customer.

They also used CRM training for the employees to see up to 80% of customers repeat.[39] Customer or consumer profiles are the essence of the data that is collected alongside core data (name, address, company) and processed through customer analytics methods, essentially a type of profiling.

A customer is abstracted to information that sums up consumption habits so far and projects them into the future so that they can be grouped for marketing and advertising purposes.[40] Consultants argue that it is important for companies establishing strong CRM systems to improve their relational intelligence.[41] According to this argument, a company must recognize that people have many different types of relationships with different brands.

One research study analyzed relationships between consumers in China, Germany, Spain, and the United States, with over 200 brands in 11 industries including airlines, cars and media.

This information is valuable as it provides demographic, behavioral, and value-based customer segmentation.

These types of relationships can be both positive and negative.

Some customers view themselves as friends of the brands, while others as enemies, and some are mixed with a love-hate relationship with the brand.

Some relationships are distant, intimate or anything in between.[23] Managers must understand the different reasons for the types of relationships, and provide the customer with what they are looking for.

Companies can collect this information by using surveys, interviews, and more, with current customers.

For example, Frito-Lay conducted many ethnographic interviews with customers to try and understand the relationships they wanted with the companies and the brands.

They found that most customers were adults who used the product to feel more playful.

They may have enjoyed the company's bright orange color, messiness, and shape.[42] Companies must also improve their relational intelligence of their CRM systems.

These days, companies store and receive huge amounts of data through emails, online chat sessions, phone calls, and more.[43] Many companies do not properly make use of this great amount of data, however.

All of these are signs of what types of relationships the customer wants with the firm, and therefore companies may consider investing more time and effort in building out their relational intelligence.[22] Companies can use data mining technologies and web searches to understand relational signals.

Social media such as social networking sites, blogs, and forums can also be used to collect and analyze information.

Understanding the customer and capturing this data allows companies to convert customer's signals into information and knowledge that the firm can use to understand a potential customer's desired relations with a brand.[42] Many firms have also implemented training programs to teach employees how to recognize and effectively create strong customer–brand relationships.

For example, Harley Davidson sent its employees on the road with customers, who were motorcycle enthusiasts, to help solidify relationships.

Other employees have also been trained in social psychology and the social sciences to help bolster strong customer relationships.

Customer service representatives must be educated to value customer relationships and trained to understand existing customer profiles.

Even the finance and legal departments should understand how to manage and build relationships with customers.[44] Applying new technologies while using CRM systems requires changes in infrastructure of the organization as well as deployment of new technologies such as business rules, databases and information technology.[42] Contact center CRM providers are popular for small and mid-market businesses.

These systems codify the interactions between company and customers by using analytics and key performance indicators to give the users information on where to focus their marketing and customer service.

This allows agents to have access to a caller's history to provide personalized customer communication.

The intention is to maximize average revenue per user, decrease churn rate and decrease idle and unproductive contact with the customers.[45][46][47] Growing in popularity is the idea of gamifying, or using game design elements and game principles in a non-game environment such as customer service environments.

The gamification of customer service environments includes providing elements found in games like rewards and bonus points to customer service representatives as a method of feedback for a job well done.[48] Gamification tools can motivate agents by tapping into their desire for rewards, recognition, achievements, and competition.[49] Contact-center automation, the practice of having an integrated system that coordinates contacts between an organization and the public, is designed to reduce the repetitive and tedious parts of a contact center agent's job.

Automation prevents this by having pre-recorded audio messages that help customers solve their problems.

For example, an automated contact center may be able to re-route a customer through a series of commands asking him or her to select a certain number in order to speak with a particular contact center agent who specializes in the field in which the customer has a question.[50] Software tools can also integrate with the agent's desktop tools to handle customer questions and requests.

This also saves time on behalf of the employees.[16] Social CRM involves the use of social media and technology to engage and learn from consumers.[51] Because the public, especially young people, are increasingly using social networking sites, companies use[23] these sites to draw attention to their products, services and brands, with the aim of building up customer relationships to increase demand.

Some CRM systems integrate social media sites like Twitter, LinkedIn and Facebook to track and communicate with customers.

These customers also share their own opinions and experiences with a company's products and services, giving these firms more insight.

Therefore, these firms can both share their own opinions and also track the opinions of their customers.[19] Enterprise feedback management software platforms combine internal survey data with trends identified through social media to allow businesses to make more accurate decisions on which products to supply.[52] CRM systems can also include technologies that create geographic marketing campaigns.

The systems take in information based on a customer's physical location and sometimes integrates it with popular location-based GPS applications.

It can be used for networking or contact management as well to help increase sales based on location.[16] Despite the general notion that CRM systems were created for the customer-centric businesses, they can also be applied to B2B environments to streamline and improve customer management conditions.

For the best level of CRM operation in a B2B environment, the software must be personalized and delivered at individual levels.[53] The main differences between business-to-consumer (B2C) and business-to-business CRM systems concern aspects like sizing of contact databases and length of relationships.[54] The overall CRM market grew by 12.3 percent in 2015.[55] In 2018 it grew by 15.6% and reached $48.2 billion.

The following table lists the top vendors in 2012-2018 (figures in millions of US dollars) published in Gartner studies.[55][56][57][58][59] The four largest vendors of stand-alone or embedded CRM system offerings are Salesforce, SAP, Oracle, and Microsoft, which represented 42 percent of the market in 2015.[55] SAP, Oracle and Microsoft offer CRM also as integral part of a bigger ERP solution whereas Salesforces offers stand-alone CRM only.

Other providers also are popular for small and mid market businesses.

Splitting CRM providers into nine different categories (Enterprise CRM Suite, Midmarket CRM Suite, Small-Business CRM Suite, sales force automation, incentive management, marketing solutions, business intelligence, data quality, consultancies), each category has a different market leader.

Additionally, applications often focus on professional fields such as healthcare, manufacturing, and other areas with branch-specific requirements.[citation needed] In the Gartner CRM Summit 2010 challenges like "system tries to capture data from social networking traffic like Twitter, handles Facebook page addresses or other online social networking sites" were discussed and solutions were provided that would help in bringing more clientele.[60] Many CRM vendors offer subscription-based web tools (cloud computing) and SaaS.

Some CRM systems are equipped with mobile capabilities, making information accessible to remote sales staff.[61] Salesforce.com was the first company to provide enterprise applications through a web browser, and has maintained its leadership position.[62] Traditional providers have recently moved into the cloud-based market via acquisitions of smaller providers: Oracle purchased RightNow in October 2011[63] and SAP acquired SuccessFactors in December 2011.[64] The era of the "social customer" refers to the use of social media by customers.[65] Sales forces also play an important role in CRM, as maximizing sales effectiveness and increasing sales productivity is a driving force behind the adoption of CRM.

Empowering sales managers was listed as one of the top 5 CRM trends in 2013.[66] Another related development is vendor relationship management (VRM), which provide tools and services that allow customers to manage their individual relationship with vendors.

VRM development has grown out of efforts by ProjectVRM at Harvard's Berkman Center for Internet & Society and Identity Commons' Internet Identity Workshops, as well as by a growing number of startups and established companies.

VRM was the subject of a cover story in the May 2010 issue of CRM Magazine.[67] Pharmaceutical companies were some of the first investors in sales force automation (SFA) and some are on their third- or fourth-generation implementations.

However, until recently, the deployments did not extend beyond SFA—limiting their scope and interest to Gartner analysts.[68] Another trend worth noting is the rise of Customer Success as a discipline within companies.

More and more companies establish Customer Success teams as separate from the traditional Sales team and task them with managing existing customer relations.

This trend fuels demand for additional capabilities for more holistic understanding of the customer health, which is a limitation for many existing vendors in the space.[69] As a result, a growing number of new entrants enter the market, while existing vendors add capabilities in this area to their suites.

In 2017, artificial intelligence and predictive analytics were identified as the newest trends in CRM.[70] Companies face large challenges when trying to implement CRM systems.

Consumer companies frequently manage their customer relationships haphazardly and unprofitably.[71] They may not effectively or adequately use their connections with their customers, due to misunderstandings or misinterpretations of a CRM system's analysis.

Clients who want to be treated more like a friend may be treated like just a party for exchange, rather than a unique individual, due to, occasionally, a lack of a bridge between the CRM data and the CRM analysis output.

Many studies show that customers are frequently frustrated by a company's inability to meet their relationship expectations, and on the other side, companies do not always know how to translate the data they have gained from CRM software into a feasible action plan.[23] In 2003, a Gartner report estimated that more than $2 billion had been spent on software that was not being used.

According to CSO Insights, less than 40 percent of 1,275 participating companies had end-user adoption rates above 90 percent.[72] Many corporations only use CRM systems on a partial or fragmented basis.[73] In a 2007 survey from the UK, four-fifths of senior executives reported that their biggest challenge is getting their staff to use the systems they had installed.

Forty-three percent of respondents said they use less than half the functionality of their existing systems.[74] However, market research regarding consumers' preferences may increase the adoption of CRM among the developing countries' consumers.[75] Collection of customer data such as personally identifiable information must strictly obey customer privacy laws, which often requires extra expenditures on legal support.

Part of the paradox with CRM stems from the challenge of determining exactly what CRM is and what it can do for a company.[76] The CRM paradox, also referred to as the "dark side of CRM",[77] may entail favoritism and differential treatment of some customers.

CRM technologies can easily become ineffective if there is no proper management, and they are not implemented correctly.

The data sets must also be connected, distributed, and organized properly, so that the users can access the information that they need quickly and easily.

Research studies also show that customers are increasingly becoming dissatisfied with contact center experiences due to lags and wait times.

They also request and demand multiple channels of communications with a company, and these channels must transfer information seamlessly.

Therefore, it is increasingly important for companies to deliver a cross-channel customer experience that can be both consistent as well as reliable.[16]

Business process automation

Business process automation (BPA), also known as business automation or digital transformation,[1] is the technology-enabled automation of complex business processes.[2] It can streamline a business for simplicity, achieve digital transformation, increase service quality, improve service delivery or contain costs.

It consists of integrating applications, restructuring labor resources and using software applications throughout the organization.

Robotic process automation is an emerging field within BPA that uses artificial intelligence.

BPAs can be implemented in a number of business areas including marketing, sales and workflow.

Toolsets vary in sophistication, but there is an increasing trend towards the use of artificial intelligence technologies that can understand natural language and unstructured data sets, interact with human beings, and adapt to new types of problems without human-guided training.

BPA providers tend to focus on different industry sectors but their underlying approach tends to be similar in that they will attempt to provide the shortest route to automation by exploiting the user interface layer rather than going deeply into the application code or databases sitting behind them.

They also simplify their own interface to the extent that these tools can be used directly by non-technically qualified staff.

The main advantage of these toolsets is therefore their speed of deployment, the drawback is that it brings yet another IT supplier to the organization.[3] The market is, however, evolving in this area.

In order to automate these processes, connectors are needed to fit these systems/solutions together with a data exchange layer to transfer the information.

A process driven messaging service is an option for optimizing your data exchange layer.

By mapping your end-to-end process workflow, you can build an integration between individual platforms using a process driven messaging platform.

Process driven messaging service gives you the logic to build your process by using triggers, jobs and workflows.

Some companies uses an API where you build workflow/s and then connect various systems or mobile devices.

You build the process, creating workflows in the API where the workflow in the API acts as a data exchange layer.

A business process management system is quite different from BPA.

However, it is possible to build automation on the back of a BPM implementation.

The actual tools to achieve this vary, from writing custom application code to using specialist BPA tools.

The advantages and disadvantages of this approach are inextricably linked – the BPM implementation provides an architecture for all processes in the business to be mapped, but this in itself delays the automation of individual processes and so benefits may be lost in the meantime.

The practice of performing robotic process automation (RPA) results in the deployment of attended or unattended software agents to an organization's environment.

These software agents, or robots, are deployed to perform pre-defined structured and repetitive sets of business tasks or processes.

Artificial intelligence software robots are deployed to handle unstructured data sets and are deployed after performing and deploying robotic process automation.

Robotic process automation is the leading gateway for the adoption of artificial intelligence in business environments.

Ontraport

Ontraport is a "business automation software for entrepreneurs, solopreneurs and small businesses" that incorporates tools like CRM, marketing automation, ECommerce and reporting"[2][3][4][5] Landon Ray founded Ontraport in 2006 in Santa Barbara, California.[6][7][8] Ontraport offers customer relations management services that help with content management, such as creating and hosting webpages; lead tracking, which includes collecting customer data and behavior; traditional marketing approaches, such as e-mail, SMS, social media, and direct mail; managing online payments, including automated billing; and workflow automation, such as for recruiting.[9][10] Forbes named Ontraport No.

71 on its list of "America's Most Promising Companies."[11] The company also placed No.

10 on Inc.'s "Top 100 Software Companies" and No.

26 on its "Top 100 California Companies.".[12][13] Ontraport has clients all over the globe.[14] Landon Ray, Pin Chen and Steven Schneider founded Ontraport in 2006 in Santa Barbara, California.[15][16][17] Ray, the flower vendor turned wall street trader said he was “running another business and ran into the problems that all entrepreneurs do, and couldn’t believe there wasn’t a slick solution to solve them.”[7] The three started the small business automation platform from a backyard yurt and released Office AutoPilot (predecessor of Ontraport) in 2008.[15][17] In 2012 a three-year sales growth of 3001%, landed Ontraport on Inc.

500's list of America's Fastest Growing Private Companies.[1][18] The company's headquarters is based in Santa Barbara, California with an additional office in Sydney, Australia which opened in 2015 and has 100+ employees.

Ontraport's leadership team includes Founder / CEO Landon Ray, President Lena Requist, and Chief Technology Officer Pin Chen.[10] Ontraport offers a subscription-based sales and marketing software for small businesses and entrepreneurs.

Features include business automation, campaign builder, CRM, ecommerce, email marketing, SMS and postcards, landing pages, marketing automation, marketing tracking, membership sites, metrics dashboard, partner program and sales force automation.[27] All of the tools are centered around the visual campaign builder launched in 2017.[11] Ontraport also offers business strategy education through educational guides, conferences and certification.

Ontraport Education, launched in October 2016, provides training courses, video tutorials and strategy classes, geared to small business owners and entrepreneurs.

[25] Ontraport hosts events such as ONTRApalooza (OPLZA), an annual conference for users and small business owners.[12]

Lead generation

In marketing, Lead generation (/ˈliːd/) is the initiation of consumer interest or enquiry into products or services of a business.

Leads can be created for purposes such as list building, e-newsletter list acquisition or for sales leads.

The methods for generating leads typically fall under the umbrella of advertising, but may also include non-paid sources such as organic search engine results or referrals from existing customers.[1] Leads may come from various sources or activities, for example, digitally via the Internet, through personal referrals, through telephone calls either by the company or telemarketers, through advertisements, and events.

A 2015 study found that 89% of respondents cited email as the most-used channel for generating leads, followed by content marketing, search engine, and finally events.[2] A study from 2014 found that direct traffic, search engines, and web referrals were the three most popular online channels for Lead generation, accounting for 93% of leads.[3] Lead generation is often paired with lead management to move leads through the purchase funnel.

This combination of activities is referred to as pipeline marketing.

A lead is usually allotted to an individual to follow up on.

Once the individual (e.g.

salesperson) reviews and qualifies it to have potential business, the lead gets converted to an opportunity for a business.

The opportunity then has to undergo multiple sales stages before the deal is won.

A lead usually is the contact information and in some cases, demographic information of a customer who is interested in a specific product or service.

There are two types of leads in the Lead generation market: sales leads and marketing leads.

Sales leads are generated on the basis of demographic criteria such as FICO score (United States), income, age, household income, psychographic, etc.

These leads are resold to multiple advertisers.

Sales leads are typically followed up through phone calls by the sales force.

Sales leads are commonly found in the mortgage, insurance and finance industries.

Marketing leads are brand-specific leads generated for a unique advertiser offer.

In direct contrast to sales leads, marketing leads are sold only once.

Because transparency is a necessary requisite for generating marketing leads, marketing lead campaigns can be optimized by mapping leads to their sources.

An investor lead is a type of a sales lead.

An investor lead is the identity of a person or entity potentially interested in participating in an investment, and represents the first stage of an investment sales process.

Investor leads are considered to have some disposable income that they can use to participate in appropriate investment opportunities in exchange for return on investment in the form of interest, dividend, profit sharing or asset appreciation.

Investor lead lists are normally generated through investment surveys, investor newsletter subscriptions or through companies raising capital and selling the database of people who expressed an interest in their opportunity.

Investor Lead lists are commonly used by small businesses looking to fund their venture or simply needing expansion capital that was not readily available by banks and traditional lending sources.

Business leads are often grouped into segments to the level of qualification present within an organization.

Marketing Qualified Leads (MQLs) are leads that have typically come through Inbound channels, such as Web Search or content marketing, and have expressed interest in a company's product or service.

These leads have yet to interact with sales teams.

Sales Qualified Leads (SQLs) are leads screened by salespeople, oftentimes Sales Development Representatives (SDRs), for appropriate qualifying criteria to be followed-up with.

Qualifying criteria include need, budget, capacity, time-frame, interest, or authority to purchase.

Online Lead generation is an Internet marketing term that refers to the generation of prospective consumer interest or inquiry into a business' products or services through the Internet.

Leads, also known as contacts, can be generated for a variety of purposes: list building, e-newsletter list acquisition, building out reward programs, loyalty programs or for other member acquisition programs.

With the rise of social networking websites, social media is used by organizations and individuals to generate leads or gain business opportunities.

Many companies actively participate on social networks including LinkedIn, Twitter and Facebook to find talent pools or market their new products and services.[4] Email remains one of the main ways that businesses communicate with clients & vendors.

Because of this, marketers often send messages to users’ inboxes.

Many leads are generated every day with cold email campaigns and warm email campaigns.

For the foreseeable future email campaigns remain a great email marketing tool.

There are three main pricing models in the online advertising market that marketers can use to buy advertising and generate leads: Recently,[when?] there has been a rapid increase in online Lead generation: banner and direct response advertising that works off a CPL pricing model.

In a pay-per-acquisition (PPA) pricing model, advertisers pay only for qualified leads resulting from those actions, irrespective of the clicks or impressions that went into generating the lead.

PPA advertising is playing an active role in online Lead generation.

PPA pricing models are more advertiser-friendly as they are less susceptible to fraud and bots.

With pay per click, providers can commit fraud by manufacturing leads or blending one source of lead with another (example: search-driven leads with co-registration leads) to generate higher profits for themselves.

A GP Bullhound research report stated that the online Lead generation was growing at 71% YTY[when?] — more than twice as fast as the online advertising market.

The rapid growth is primarily driven by the advertiser demand for ROI focused marketing, a trend that is expected to accelerate during a recession.[citation needed] Common types of opt-in ad units include: A common advertising metric for Lead generation is cost per lead.

The formula is Cost / Leads, for example if you created 100 leads and it cost $1000, the cost per lead would be $10.

Many private healthcare organizations use online Lead generation as a way to contact their existing patients and to acquire new patients.

"The number of Cyberchondriacs has jumped to 175 million from 154 million last year, possibly as a result of the health care reform debate.

Furthermore, frequency of usage has also increased.

Fully 32% of all adults who online says they look for health information "often," compared to 22% last year." said Harris Interactive in a study completed and reported in August 2010 with demographics based in the United States of America.[5] Lead nurturing is the process of continuously contacting the potential buyer to update information and to improve the knowledge of the customer throughout the buying process.

All lead information tends to change or become obsolete as time passes.

To keep the information up to date, the Lead Manager needs to continuously contact the leads' contact to update the information, to deepen the information in a are often grouped into segments to the level of qualification present within an organization.[6] Lead nurturing Process is the set of actions that the marketing team makes in order to nurture the leads.

They can be both manual or automatic.

Marketing and artificial intelligence

Customer lifetime value

In marketing, Customer lifetime value (CLV or often CLTV), lifetime customer value (LCV), or life-time value (LTV) is a prediction of the net profit attributed to the entire future relationship with a customer.

The prediction model can have varying levels of sophistication and accuracy, ranging from a crude heuristic to the use of complex predictive analytics techniques.

Customer lifetime value can also be defined as the monetary value of a customer relationship, based on the present value of the projected future cash flows from the customer relationship.[citation needed] Customer lifetime value is an important concept in that it encourages firms to shift their focus from quarterly profits to the long-term health of their customer relationships.

Customer lifetime value is an important metric because it represents an upper limit on spending to acquire new customers.[1] For this reason it is an important element in calculating payback of advertising spent in marketing mix modeling.

One of the first accounts of the term Customer lifetime value is in the 1988 book Database Marketing, which includes detailed worked examples.[2] Early adopters of Customer lifetime value models in the 1990s include Edge Consulting and BrandScience.

The purpose of the Customer lifetime value metric is to assess the financial value of each customer.

Don Peppers and Martha Rogers are quoted as saying, “some customers are more equal than others.”[3] Customer lifetime value differs from customer profitability or CP (the difference between the revenues and the costs associated with the customer relationship during a specified period) in that CP measures the past and CLV looks forward.

As such, CLV can be more useful in shaping managers’ decisions but is much more difficult to quantify.

While quantifying CP is a matter of carefully reporting and summarizing the results of past activity, quantifying CLV involves forecasting future activity.[1] Present value is the discounted sum of future cash flows: each future cash flow is multiplied by a carefully selected number less than one, before being added together.

The multiplication factor accounts for the way the value of money is discounted over time.

The time-based value of money captures the intuition that everyone would prefer to get paid sooner rather than later but would prefer to pay later rather than sooner.

The multiplication factors depend on the discount rate chosen (10% per year as an example) and the length of time before each cash flow occurs.

For example, money received ten years from now must be discounted more than money received five years in the future.[1] CLV applies the concept of present value to cash flows attributed to the customer relationship.

Because the present value of any stream of future cash flows is designed to measure the single lump sum value today of the future stream of cash flows, CLV will represent the single lump sum value today of the customer relationship.

Even more simply, CLV is the monetary value of the customer relationship to the firm.

It is an upper limit on what the firm would be willing to pay to acquire the customer relationship as well as an upper limit on the amount the firm would be willing to pay to avoid losing the customer relationship.

If we view a customer relationship as an asset of the firm, CLV would present the monetary value of that asset.[1] One of the major uses of CLV is customer segmentation, which starts with the understanding that not all customers are equally important.

CLV-based segmentation model allows the company to predict the most profitable group of customers, understand those customers' common characteristics, and focus more on them rather than on less profitable customers.

CLV-based segmentation can be combined with a Share of Wallet (SOW) model to identify "high CLV but low SOW" customers with the assumption that the company's profit could be maximized by investing marketing resources in those customers.

Customer lifetime value metrics are used mainly in relationship-focused businesses, especially those with customer contracts.

Examples include banking and insurance services, telecommunications and most of the business-to-business sector.

However, the CLV principles may be extended to transactions-focused categories such as consumer packaged goods by incorporating stochastic purchase models of individual or aggregate behavior.[4] In either case, retention has a decisive impact on CLV, since low retention rates result in Customer lifetime value barely increasing over time.

When margins and retention rates are constant, the following formula can be used to calculate the lifetime value of a customer relationship: The model for customer cash flows treats the firm's customer relationships as something of a leaky bucket.

Each period, a fraction (1 less the retention rate) of the firm's customers leave and are lost for good.[1] The CLV model has only three parameters: (1) constant margin (contribution after deducting variable costs including retention spending) per period, (2) constant retention probability per period, and (3) discount rate.

Furthermore, the model assumes that in the event that the customer is not retained, they are lost for good.

Finally, the model assumes that the first margin will be received (with probability equal to the retention rate) at the end of the first period.[1] The one other assumption of the model is that the firm uses an infinite horizon when it calculates the present value of future cash flows.

Although no firm actually has an infinite horizon, the consequences of assuming one are discussed in the following.[1] Under the assumptions of the model, CLV is a multiple of the margin.

The multiplicative factor represents the present value of the expected length (number of periods) of the customer relationship.

When retention equals 0, the customer will never be retained, and the multiplicative factor is zero.

When retention equals 1, the customer is always retained, and the firm receives the margin in perpetuity.

The present value of the margin in perpetuity turns out to be the Margin divided by the Discount Rate.

For retention values in between, the CLV formula tells us the appropriate multiplier.[1] Simple commerce example (Avg Monthly Revenue per Customer * Gross Margin per Customer) ÷ Monthly Churn Rate The numerator represents the average monthly profit per customer, and dividing by the churn rate sums the geometric series representing the chance the customer will still be around in future months.[citation needed] For example: $100 avg monthly spend * 25% margin ÷ 5% monthly churn = $500 LTV A retention example CLV (Customer lifetime value) calculation process consists of four steps: Forecasting accuracy and difficulty in tracking customers over time may affect CLV calculation process.

Retention models make several simplifying assumptions and often involve the following inputs: Thus, one of the ways to calculate CLV, where period is a year, is as follows:[6] where GC {\displaystyle {\text{GC}}} is yearly gross contribution per customer, M {\displaystyle {\text{M}}} is the (relevant) retention costs per customer per year (this formula assumes the retention activities are paid for each mid year and they only affect those who were retained in the previous year), n {\displaystyle n} is the horizon (in years), r {\displaystyle r} is the yearly retention rate, d {\displaystyle d} is the yearly discount rate.

In addition to retention costs, firms are likely to invest in cross-selling activities which are designed to increase the yearly profit of a customer over time.[7] Simplified models It is often helpful to estimate Customer lifetime value with a simple model to make initial assessments of customer segments and targeting.

If GC {\displaystyle {\text{GC}}} is found to be relatively fixed across periods, CLV can be expressed as a simpler model assuming an infinite economic life (i.e., N → ∞ {\displaystyle {\text{N}}\rightarrow \infty } ) :[8] Note: No CLV methodology has been independently audited by the Marketing Accountability Standards Board (MASB) according to MMAP (Marketing Metric Audit Protocol).

Customer lifetime value has intuitive appeal as a marketing concept, because in theory it represents exactly how much each customer is worth in monetary terms, and therefore exactly how much a marketing department should be willing to spend to acquire each customer, especially in direct response marketing.

Lifetime value is typically used to judge the appropriateness of the costs of acquisition of a customer.

For example, if a new customer costs $50 to acquire (COCA, or cost of customer acquisition), and their lifetime value is $60, then the customer is judged to be profitable, and acquisition of additional similar customers is acceptable.

Additionally, CLV is used to calculate customer equity.

Advantages of CLV: The disadvantages of CLV do not generally stem from CLV modeling per se, but from its incorrect application.

The most accurate CLV predictions are made using the net present value (NPV) of each future net profit source, so that the revenue to be received from the customer in the future is recognized at the future value of money.

However, NPV calculations require additional sophistication including maintenance of a discount rate, which leads most organizations to instead calculate CLV using the nominal (non-discounted) figures.

Nominal CLV predictions are biased slightly high, scaling higher the farther into the future the revenues are expected from customers.

A common mistake is for a CLV prediction to calculate the total revenue or even gross margin associated with a customer.

However, this can cause CLV to be multiples of their actual value, and instead need to be calculated as the full net profit expected from the customer.

Opponents often cite the inaccuracy of a CLV prediction to argue they should not be used to drive significant business decisions.

For example, major drivers to the value of a customer such as the nature of the relationship are often not available as appropriately structured data and thus not included in the formula.

More predictors, such as specific demographics of a customer group, may have an effect that is intuitively obvious to an experienced marketer but are often omitted from CLV predictions and thus cause inaccuracies in certain customer segments.

The biggest problem with how many CLV models are actually used is that they tend to deny the very idea that marketing works (i.e., that marketing will change customer behavior).

Low-value customers can be turned into high-value customers by effective marketing.

Many CLV models use incorrect math in that they do not take account of the value of a far greater number of middle-value customers, over-prioritizing a smaller number of high value customers.

Additionally, these high-value customers may be saturated (i.e., not have the ability to buy any more coffee or insurance), may be the most expensive group to serve, and may be the most expensive group to reach by communication.

The use of survey data is a viable way to collect information on potential customers.[13] A Customer Life Time Value is the output of a model, not an input.

If you change the model inputs (e.g., let's say marketing is effective and you increase your retention rates), your average CLV will increase.

ActiveCampaign

ActiveCampaign is a cloud software platform for small-to-mid-sized business and is based in Chicago, Illinois.

The company offers software for customer experience automation (CXA), which combines the email marketing, marketing automation, sales automation, and CRM categories.[4][5][6] ActiveCampaign was founded by Jason VandeBoom in 2003.[7] It started as a consulting firm, and then as an on-premises software provider, helping small and midsize businesses automate marketing tasks and manage contacts.[8] The company would later transition from on-premises software to a software as a service business focused on marketing and sales automation.[7][9] As of 2020, ActiveCampaign has over 90,000 clients and $90 million in recurring revenue, with customers in 161 countries.[1] ActiveCampaign raised $20 million from Silversmith Capital Partners in 2016.[10] In February 2020 it raised $100 million in a Series B round led by Susquehanna Growth Equity, joined by Silversmith.[1][3] ActiveCampaign is headquartered in Chicago with offices in Indianapolis,[11] Sydney, Australia,[12] and Dublin, Ireland.[1][3] ActiveCampaign provides cloud-based marketing and sales automation software with features for email marketing, lead scoring and web analytics, a CRM platform, and a live chat messaging platform called Conversations.[7][10][13][14] ActiveCampaign distinguishes its software, called customer experience automation (CXA), from traditional email marketing and CRM platforms by extending its services into customer support.[3][15][16] ActiveCampaign integrates with over 300 applications, including Salesforce, WordPress, Shopify, PayPal, Stripe, Gmail, Facebook, and WooCommerce.[3][15][17] According to PC Magazine, "ActiveCampaign offers a lot of features for a relatively low price.

The downside is that it can be confusing to use at times; thankfully, its help resources are plentiful.[18] Solutions Review pointed out, "Users have access to detailed behavior tracking capabilities as well as precision marketing options through segmentation."[13] ActiveCampaign appeared on Crain's Chicago Business 2018 and 2019 best places to work lists,[19][20] Inc.com's 2018 list of best workplaces,[21] and the Chicago Tribune's 2018 list of top midsize workplaces.[22]

Return on marketing investment

Return on marketing investment (ROMI) is the contribution to profit attributable to marketing (net of marketing spending), divided by the marketing 'invested' or risked.

ROMI is not like the other 'return-on-investment' (ROI) metrics because marketing is not the same kind of investment.

Instead of money that is 'tied' up in plants and inventories (often considered capital expenditure or CAPEX), marketing funds are typically 'risked'.

Marketing spending is typically expensed in the current period (operational expenditure or OPEX).

The idea of measuring the market's response in terms of sales and profits is not new, but terms such as marketing ROI and ROMI are used more frequently now than in past periods.

Usually, marketing spending will be deemed as justified if the ROMI is positive.

In a survey of nearly 200 senior marketing managers, nearly half responded that they found the ROMI metric very useful.[1] The purpose of ROMI is to measure the degree to which spending on marketing contributes to profits.[1] Marketers are under more and more pressure to "show a return" on their activities.

The ROMI concept first came to prominence in the 1990s.

The phrase "Return on marketing investment" became more widespread in the next decade following the publication of two books Return on marketing investment by Guy Powell (2002) [2] and Marketing ROI by James Lenskold (2003).[3] In the book "What Sticks: Why Advertising Fails And How To Guarantee Yours Succeeds," Rex Briggs suggested the term "ROMO" for Return-On-Marketing-Objective, to reflect the idea that marketing campaigns may have a range of objectives, where the return is not immediate sales or profits.

For example, a marketing campaign may aim to change the perception of a brand.[4] A necessary step in calculating ROMI is the measurement and eventual estimation of the incremental sales attributed to marketing.

These incremental sales can be 'total' sales attributable to marketing or 'marginal.' [1] There are two forms of the Return on marketing investment (ROMI) metric.

The first, short-term ROMI, is also used as a simple index measuring the dollars of revenue (or market share, contribution margin or other desired outputs) for every dollar of marketing spent.

For example, if a company spends $100,000 on a direct mail piece and it delivers $500,000 in incremental revenue, then the ROMI factor is 5.0.

If the incremental contribution margin for that $500,000 in revenue is 60%, then the margin ROMI (the incremental margin for $100,000 of marketing spent) is $300,000 (= $500,000 x 60%).

Of which, the $100,000 spent on direct mail advertising will be subtracted and the difference will be divided by the same $100,000.

Every dollar expended in direct mail advertising translates to an additional $2 on the company's bottom line.

The value of the first ROMI is in its simplicity.

In most cases a simple determination of revenue per dollar spent for each marketing activity can be sufficient to help make important decisions to improve the entire marketing mix.

The most common short term approach to measuring ROMI is by applying Marketing Mix Modeling techniques to separate out the incremental sales effects of marketing investment.

In a similar way the second ROMI concept, long-term ROMI can be used to determine other less tangible aspects of marketing effectiveness.

For example, ROMI could be used to determine the incremental value of marketing as it pertains to increased brand awareness, consideration or purchase intent.

In this way both the longer-term value of marketing activities (incremental brand awareness, etc.) and the shorter-term revenue and profit can be determined.

This is a sophisticated metric that balances marketing and business analytics and is used increasingly by many of the world's leading organizations (Hewlett-Packard and Procter & Gamble to name two) to measure the economic (that is, cash-flow derived) benefits created by marketing investments.

For many other organizations, this method offers a way to prioritize investments and allocate marketing and other resources on a formalized basis.

Long term ROMI models will often draw on Customer lifetime value models to demonstrate the long term value of incremental customer acquisition or reduced churn rate.

Some more sophisticated Marketing Mix Modeling approaches include multi-year long term ROMI by including CLV type analysis.

Long term ROMI models have sometimes used brand valuation techniques to measure how building a brand with marketing spend can create balance sheet value for brands (or at least for brands that have been transacted, and therefore under accounting rules can have a balance sheet value).

The ISO 10668 standard sets out the appropriate process of valuing brands and sets out six key requirements, transparency, validity, reliability, sufficiency, objectivity and financial, behavioural and legal parameters.

Brand valuation is distinguished from brand equity by placing a money value on a brand, and in this way a ROMI can be calculated.

Note: No Return on marketing investment methodologies have been independently audited by the Marketing Accountability Standards Board (MASB) according to MMAP (Marketing Metric Audit Protocol) .

Direct measures of the short-term variant of ROMI are often criticized as only including the direct impact of marketing activities without including the long-term brand building value of any communication inserted into the market.

Short-term ROMI is best employed as a tool to determine marketing effectiveness to help steer investments from less productive activities to those that are more productive.

It is a simple tool to gauge the success of measurable marketing activities against various marketing objectives (e.g., incremental revenue, brand awareness or brand equity).

With this knowledge, marketing investments can be redirected away from under-performing activities to better performing marketing media.

Long-term ROMI is often criticized as a "silo-in-the-making"—it is intensively data driven and creates a challenge for firms that are not used to working business analytics into the marketing analytics that typically determine resource allocation decisions.

Long-term ROMI, however, is a sophisticated measure used by a number of firms interested in getting to the bottom of value for money challenges often posed by competing brand managers.

However, it is often unclear exactly what it means to 'show a return' on marketing investment.

"Certainly, marketing spending is not an 'investment' in the usual sense of the word.

There is usually no tangible asset and often not even a predictable (quantifiable) result to show for the spending, but marketers still want to emphasize that their activities contribute to financial health.

Some might argue that marketing should be considered an expense and the focus should be on whether it is a necessary expense.

Marketers believe that many of their activities generate lasting results and therefore should be considered 'investments' in the future of the business." [1][5] The difficulty of measuring ROMI varies across mediums.

Results of a recent North American survey show the ROI associated with one-way, traditional media (e.g.

television and radio) is more difficult to measure than interactive, web-based digital media such as permission-based email marketing or social media marketing.[6] In 2013, Black Ink introduced Eye On, the first SaaS designed to measure enterprise ROMI across all mediums.

[7] With the rise in Digital Marketing, the opportunity is available for marketers, or even business owners to run rough calculations of what their approximate ROI may be for their campaigns, before they even start investing.

Based from statistical research, and all things being equal, the business owner can calculate their current Digital Marketing ROI via their website and web analytics software to understand their : Add in readily available information on potential traffic from the Google Keyword Tool, and surveyed costs to acquire that traffic, the business owner or marketer can estimate the potential ROI if that traffic is acquired, and even measure it against other marketing methods.

[8]

Automation

IEEE Robotics and Automation Award Industrial robot Autonomous research robot Domestic robot Home Automation Banking Automation Laboratory Automation Integrated library system Broadcast Automation Console Automation Building Automation Automated attendant Automated guided vehicle Automated highway system Automated pool cleaner Automated reasoning Automated teller machine Automatic painting (robotic) Pop music Automation Robotic lawn mower Telephone switchboard Vending machine Automation, or Labor-saving technology is the technology by which a process or procedure is performed with minimal human assistance.[1] Automation[2] or automatic control is the use of various control systems for operating equipment such as machinery, processes in factories, boilers and heat treating ovens, switching on telephone networks, steering and stabilization of ships, aircraft and other applications and vehicles with minimal or reduced human intervention.

Automation covers applications ranging from a household thermostat controlling a boiler, to a large industrial control system with tens of thousands of input measurements and output control signals.

In control complexity, it can range from simple on-off control to multi-variable high-level algorithms.

In the simplest type of an automatic control loop, a controller compares a measured value of a process with a desired set value, and processes the resulting error signal to change some input to the process, in such a way that the process stays at its set point despite disturbances.

This closed-loop control is an application of negative feedback to a system.

The mathematical basis of control theory was begun in the 18th century and advanced rapidly in the 20th.

Automation has been achieved by various means including mechanical, hydraulic, pneumatic, electrical, electronic devices and computers, usually in combination.

Complicated systems, such as modern factories, airplanes and ships typically use all these combined techniques.

The benefit of Automation includes labor savings, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision.

The World Bank's World Development Report 2019 shows evidence that the new industries and jobs in the technology sector outweigh the economic effects of workers being displaced by Automation.[3] Job losses and downward mobility blamed on Automation has been cited as one of many factors in the resurgence of nationalist and protectionist politics in the US, UK and France, among other countries since the 2010s.[4][5][6][7][8] The term Automation, inspired by the earlier word automatic (coming from automaton), was not widely used before 1947, when Ford established an Automation department.[2] It was during this time that industry was rapidly adopting feedback controllers, which were introduced in the 1930s.[9] Fundamentally, there are two types of control loop; open loop control, and closed loop feedback control.

In open loop control, the control action from the controller is independent of the "process output" (or "controlled process variable").

A good example of this is a central heating boiler controlled only by a timer, so that heat is applied for a constant time, regardless of the temperature of the building.

(The control action is the switching the boiler off and on.

The process output is the building temperature).

In closed-loop control, the control action from the controller is dependent on the process output.

In the case of the boiler analogy, this would include a temperature sensor to monitor the building temperature, and thereby feed a signal back to the controller to ensure it maintains the building at the temperature set on the thermostat.

A closed loop controller, therefore, has a feedback loop which ensures the controller exerts a control action to give a process output equal to the "Reference input" or "set point".

For this reason, closed-loop controllers are also called feedback controllers.[10] The definition of a closed loop control system according to the British Standard Institution is 'a control system possessing monitoring feedback, the deviation signal formed as a result of this feedback being used to control the action of a final control element in such a way as to tend to reduce the deviation to zero.'[11] Likewise, a Feedback Control System is a system which tends to maintain a prescribed relationship of one system variable to another by comparing functions of these variables and using the difference as a means of control.[11] The advanced type of Automation that revolutionized manufacturing, aircraft, communications, and other industries, is feedback control, which is usually continuous and involves taking measurements using a sensor and making calculated adjustments to keep the measured variable within a set range.[12][13] The theoretical basis of closed-loop Automation is control theory.

One of the simplest types of control is on-off control.

An example is a thermostat used on household appliances which either opens or closes an electrical contact.

(Thermostats were originally developed as true feedback-control mechanisms rather than the on-off common household appliance thermostat.) Sequence control, in which a programmed sequence of discrete operations is performed, often based on system logic that involves system states.

An elevator control system is an example of sequence control.

A proportional–integral–derivative controller (PID controller) is a control loop feedback mechanism (controller) widely used in industrial control systems.

In a PID loop, the controller continuously calculates an error value e ( t ) {\displaystyle e(t)} as the difference between a desired setpoint and a measured process variable and applies a correction based on proportional, integral, and derivative terms, respectively (sometimes denoted P, I, and D) which give their name to the controller type.

The theoretical understanding and application dates from the 1920s, and they are implemented in nearly all analog control systems; originally in mechanical controllers, and then using discrete electronics and latterly in industrial process computers.

Sequential control may be either to a fixed sequence or to a logical one that will perform different actions depending on various system states.

An example of an adjustable but otherwise fixed sequence is a timer on a lawn sprinkler.

States refer to the various conditions that can occur in a use or sequence scenario of the system.

An example is an elevator, which uses logic based on the system state to perform certain actions in response to its state and operator input.

For example, if the operator presses the floor n button, the system will respond depending on whether the elevator is stopped or moving, going up or down, or if the door is open or closed, and other conditions.[14] Early development of sequential control was relay logic, by which electrical relays engage electrical contacts which either start or interrupt power to a device.

Relays were first used in telegraph networks before being developed for controlling other devices, such as when starting and stopping industrial-sized electric motors or opening and closing solenoid valves.

Using relays for control purposes allowed event-driven control, where actions could be triggered out of sequence, in response to external events.

These were more flexible in their response than the rigid single-sequence cam timers.

More complicated examples involved maintaining safe sequences for devices such as swing bridge controls, where a lock bolt needed to be disengaged before the bridge could be moved, and the lock bolt could not be released until the safety gates had already been closed.

The total number of relays and cam timers can number into the hundreds or even thousands in some factories.

Early programming techniques and languages were needed to make such systems manageable, one of the first being ladder logic, where diagrams of the interconnected relays resembled the rungs of a ladder.

Special computers called programmable logic controllers were later designed to replace these collections of hardware with a single, more easily re-programmed unit.

In a typical hard wired motor start and stop circuit (called a control circuit) a motor is started by pushing a "Start" or "Run" button that activates a pair of electrical relays.

The "lock-in" relay locks in contacts that keep the control circuit energized when the push-button is released.

(The start button is a normally open contact and the stop button is normally closed contact.) Another relay energizes a switch that powers the device that throws the motor starter switch (three sets of contacts for three-phase industrial power) in the main power circuit.

Large motors use high voltage and experience high in-rush current, making speed important in making and breaking contact.

This can be dangerous for personnel and property with manual switches.

The "lock-in" contacts in the start circuit and the main power contacts for the motor are held engaged by their respective electromagnets until a "stop" or "off" button is pressed, which de-energizes the lock in relay.[15] Commonly interlocks are added to a control circuit.

Suppose that the motor in the example is powering machinery that has a critical need for lubrication.

In this case, an interlock could be added to ensure that the oil pump is running before the motor starts.

Timers, limit switches, and electric eyes are other common elements in control circuits.

Solenoid valves are widely used on compressed air or hydraulic fluid for powering actuators on mechanical components.

While motors are used to supply continuous rotary motion, actuators are typically a better choice for intermittently creating a limited range of movement for a mechanical component, such as moving various mechanical arms, opening or closing valves, raising heavy press rolls, applying pressure to presses.

Computers can perform both sequential control and feedback control, and typically a single computer will do both in an industrial application.

Programmable logic controllers (PLCs) are a type of special purpose microprocessor that replaced many hardware components such as timers and drum sequencers used in relay logic type systems.

General-purpose process control computers have increasingly replaced stand-alone controllers, with a single computer able to perform the operations of hundreds of controllers.

Process control computers can process data from a network of PLCs, instruments, and controllers in order to implement typical (such as PID) control of many individual variables or, in some cases, to implement complex control algorithms using multiple inputs and mathematical manipulations.

They can also analyze data and create real-time graphical displays for operators and run reports for operators, engineers, and management.

Control of an automated teller machine (ATM) is an example of an interactive process in which a computer will perform a logic derived response to a user selection based on information retrieved from a networked database.

The ATM process has similarities with other online transaction processes.

The different logical responses are called scenarios.

Such processes are typically designed with the aid of use cases and flowcharts, which guide the writing of the software code.

The earliest feedback control mechanism was the water clock invented by Greek engineer Ctesibius (285–222 BC) It was a preoccupation of the Greeks and Arabs (in the period between about 300 BC and about 1200 AD) to keep accurate track of time.

In Ptolemaic Egypt, about 270 BC, Ctesibius described a float regulator for a water clock, a device not unlike the ball and cock in a modern flush toilet.

This was the earliest feedback controlled mechanism.[16] The appearance of the mechanical clock in the 14th century made the water clock and its feedback control system obsolete.

The Persian Banū Mūsā brothers, in their Book of Ingenious Devices (850 AD), described a number of automatic controls.[17] Two-step level controls for fluids, a form of discontinuous variable structure controls, was developed by the Banu Musa brothers.[18] They also described a feedback controller.[19][20] The introduction of prime movers, or self-driven machines advanced grain mills, furnaces, boilers, and the steam engine created a new requirement for automatic control systems including temperature regulators (invented in 1624; see Cornelius Drebbel), pressure regulators (1681), float regulators (1700) and speed control devices.

Another control mechanism was used to tent the sails of windmills.

It was patented by Edmund Lee in 1745.[21] Also in 1745, Jacques de Vaucanson invented the first automated loom.

The design of feedback control systems up through the Industrial Revolution was by trial-and-error, together with a great deal of engineering intuition.

Thus, it was more of an art than a science.

In the mid-19th century mathematics was first used to analyze the stability of feedback control systems.

Since mathematics is the formal language of automatic control theory, we could call the period before this time the prehistory of control theory.

In 1771 Richard Arkwright invented the first fully automated spinning mill driven by water power, known at the time as the water frame.[22] An automatic flour mill was developed by Oliver Evans in 1785, making it the first completely automated industrial process.[23][24] The centrifugal governor, which was invented by Christian Huygens in the seventeenth century, was used to adjust the gap between millstones.[25][26][27] Another centrifugal governor was used by a Mr.

Bunce of England in 1784 as part of a model steam crane.[28][29] The centrifugal governor was adopted by James Watt for use on a steam engine in 1788 after Watt's partner Boulton saw one at a flour mill Boulton & Watt were building.[21] The governor could not actually hold a set speed; the engine would assume a new constant speed in response to load changes.

The governor was able to handle smaller variations such as those caused by fluctuating heat load to the boiler.

Also, there was a tendency for oscillation whenever there was a speed change.

As a consequence, engines equipped with this governor were not suitable for operations requiring constant speed, such as cotton spinning.[21] Several improvements to the governor, plus improvements to valve cut-off timing on the steam engine, made the engine suitable for most industrial uses before the end of the 19th century.

Advances in the steam engine stayed well ahead of science, both thermodynamics and control theory.[21] The governor received relatively little scientific attention until James Clerk Maxwell published a paper that established the beginning of a theoretical basis for understanding control theory.

Development of the electronic amplifier during the 1920s, which was important for long-distance telephony, required a higher signal to noise ratio, which was solved by negative feedback noise cancellation.

This and other telephony applications contributed to control theory.

In the 1940s and 1950s, German mathematician Irmgard Flugge-Lotz developed the theory of discontinuous automatic controls, which found military applications during the Second World War to fire control systems and aircraft navigation systems.[12] Relay logic was introduced with factory electrification, which underwent rapid adaption from 1900 through the 1920s.

Central electric power stations were also undergoing rapid growth and operation of new high-pressure boilers, steam turbines and electrical substations created a large demand for instruments and controls.

Central control rooms became common in the 1920s, but as late as the early 1930s, most process control was on-off.

Operators typically monitored charts drawn by recorders that plotted data from instruments.

To make corrections, operators manually opened or closed valves or turned switches on or off.

Control rooms also used color-coded lights to send signals to workers in the plant to manually make certain changes.[30] Controllers, which were able to make calculated changes in response to deviations from a set point rather than on-off control, began being introduced the 1930s.

Controllers allowed manufacturing to continue showing productivity gains to offset the declining influence of factory electrification.[31] Factory productivity was greatly increased by electrification in the 1920s.

U.S.

manufacturing productivity growth fell from 5.2%/yr 1919–29 to 2.76%/yr 1929–41.

Alexander Field notes that spending on non-medical instruments increased significantly from 1929–33 and remained strong thereafter.[31] The First and Second World Wars saw major advancements in the field of mass communication and signal processing.

Other key advances in automatic controls include differential equations, stability theory and system theory (1938), frequency domain analysis (1940), ship control (1950), and stochastic analysis (1941).

Starting in 1958, various systems based on solid-state[32][33] digital logic modules for hard-wired programmed logic controllers (the predecessors of programmable logic controllers (PLC)) emerged to replace electro-mechanical relay logic in industrial control systems for process control and Automation, including early Telefunken/AEG Logistat, Siemens Simatic, Philips/Mullard/Valvo [de] Norbit, BBC Sigmatronic, ACEC Logacec, Akkord [de] Estacord, Krone Mibakron, Bistat, Datapac, Norlog, SSR, or Procontic systems.[32][34][35][36][37][38] In 1959 Texaco's Port Arthur Refinery became the first chemical plant to use digital control.[39] Conversion of factories to digital control began to spread rapidly in the 1970s as the price of computer hardware fell.

The automatic telephone switchboard was introduced in 1892 along with dial telephones.[40] By 1929, 31.9% of the Bell system was automatic.

Automatic telephone switching originally used vacuum tube amplifiers and electro-mechanical switches, which consumed a large amount of electricity.

Call volume eventually grew so fast that it was feared the telephone system would consume all electricity production, prompting Bell Labs to begin research on the transistor.[41] The logic performed by telephone switching relays was the inspiration for the digital computer.

The first commercially successful glass bottle blowing machine was an automatic model introduced in 1905.[42] The machine, operated by a two-man crew working 12-hour shifts, could produce 17,280 bottles in 24 hours, compared to 2,880 bottles made by a crew of six men and boys working in a shop for a day.

The cost of making bottles by machine was 10 to 12 cents per gross compared to $1.80 per gross by the manual glassblowers and helpers.

Sectional electric drives were developed using control theory.

Sectional electric drives are used on different sections of a machine where a precise differential must be maintained between the sections.

In steel rolling, the metal elongates as it passes through pairs of rollers, which must run at successively faster speeds.

In paper making the paper sheet shrinks as it passes around steam heated drying arranged in groups, which must run at successively slower speeds.

The first application of a sectional electric drive was on a paper machine in 1919.[43] One of the most important developments in the steel industry during the 20th century was continuous wide strip rolling, developed by Armco in 1928.[44] Before Automation many chemicals were made in batches.

In 1930, with the widespread use of instruments and the emerging use of controllers, the founder of Dow Chemical Co.

was advocating continuous production.[45] Self-acting machine tools that displaced hand dexterity so they could be operated by boys and unskilled laborers were developed by James Nasmyth in the 1840s.[46] Machine tools were automated with Numerical control (NC) using punched paper tape in the 1950s.

This soon evolved into computerized numerical control (CNC).

Today extensive Automation is practiced in practically every type of manufacturing and assembly process.

Some of the larger processes include electrical power generation, oil refining, chemicals, steel mills, plastics, cement plants, fertilizer plants, pulp and paper mills, automobile and truck assembly, aircraft production, glass manufacturing, natural gas separation plants, food and beverage processing, canning and bottling and manufacture of various kinds of parts.

Robots are especially useful in hazardous applications like automobile spray painting.

Robots are also used to assemble electronic circuit boards.

Automotive welding is done with robots and automatic welders are used in applications like pipelines.

With the advent of the space age in 1957, controls design, particularly in the United States, turned away from the frequency-domain techniques of classical control theory and backed into the differential equation techniques of the late 19th century, which were couched in the time domain.

During the 1940s and 1950s, German mathematician Irmgard Flugge-Lotz developed the theory of discontinuous automatic control, which became widely used in hysteresis control systems such as navigation systems, fire-control systems, and electronics.

Through Flugge-Lotz and others, the modern era saw time-domain design for nonlinear systems (1961), navigation (1960), optimal control and estimation theory (1962), nonlinear control theory (1969), digital control and filtering theory (1974), and the personal computer (1983).

Perhaps the most cited advantage of Automation in industry is that it is associated with faster production and cheaper labor costs.

Another benefit could be that it replaces hard, physical, or monotonous work.[47] Additionally, tasks that take place in hazardous environments or that are otherwise beyond human capabilities can be done by machines, as machines can operate even under extreme temperatures or in atmospheres that are radioactive or toxic.

They can also be maintained with simple quality checks.

However, at the time being, not all tasks can be automated, and some tasks are more expensive to automate than others.

Initial costs of installing the machinery in factory settings are high, and failure to maintain a system could result in the loss of the product itself.

Moreover, some studies seem to indicate that industrial Automation could impose ill effects beyond operational concerns, including worker displacement due to systemic loss of employment and compounded environmental damage; however, these findings are both convoluted and controversial in nature, and could potentially be circumvented.[48] The main advantages of Automation are: The main disadvantages of Automation are: The paradox of Automation says that the more efficient the automated system, the more crucial the human contribution of the operators.

Humans are less involved, but their involvement becomes more critical.

Lisanne Bainbridge, a cognitive psychologist, identified these issues notably in her widely cited paper "Ironies of Automation."[50] If an automated system has an error, it will multiply that error until it is fixed or shut down.

This is where human operators come in.[51] A fatal example of this was Air France Flight 447, where a failure of Automation put the pilots into a manual situation they were not prepared for.[52] Many roles for humans in industrial processes presently lie beyond the scope of Automation.

Human-level pattern recognition, language comprehension, and language production ability are well beyond the capabilities of modern mechanical and computer systems (but see Watson computer).

Tasks requiring subjective assessment or synthesis of complex sensory data, such as scents and sounds, as well as high-level tasks such as strategic planning, currently require human expertise.

In many cases, the use of humans is more cost-effective than mechanical approaches even where the Automation of industrial tasks is possible.

Overcoming these obstacles is a theorized path to post-scarcity economics.

Increased Automation often cause workers to feel anxious about losing their jobs as technology renders their skills or experience unnecessary.

Early in the Industrial Revolution, when inventions like the steam engine were making some job categories expendable, workers forcefully resisted these changes.

Luddites, for instance, were English textile workers who protested the introduction of weaving machines by destroying them.[53] More recently, some residents of Chandler, Arizona, have slashed tires and pelted rocks at driver-less cars, in protest over the cars' perceived threat to human safety and job prospects.[54] The relative anxiety about Automation reflected in opinion polls seems to correlate closely with the strength of organized labor in that region or nation.

For example, while a study by the Pew Research Center indicated that 72% of Americans are worried about increasing Automation in the workplace, 80% of Swedes see Automation and artificial intelligence as a good thing, due to the country's still-powerful unions and a more robust national safety net.[55] In the United States, 47% of all current jobs have the potential to be fully automated by 2033, according to the research of experts Carl Benedikt Frey and Michael Osborne.

Furthermore, wages and educational attainment appear to be strongly negatively correlated with an occupation's risk of being automated.[56] Even highly skilled professional jobs like a lawyer, doctor, engineer, journalist are at risk of Automation.[57] Prospects are particularly bleak for occupations that do not presently require a university degree, such as truck driving.[58] Even in high-tech corridors like Silicon Valley, concern is spreading about a future in which a sizable percentage of adults have little chance of sustaining gainful employment.[59] As the example of Sweden suggests, however, the transition to a more automated future need not inspire panic, if there is sufficient political will to promote the retraining of workers whose positions are being rendered obsolete.

According to a 2020 study in the Journal of Political Economy, Automation has robust negative effects on employment and wages: "One more robot per thousand workers reduces the employment-to-population ratio by 0.2 percentage points and wages by 0.42%."[60] Research by Carl Benedikt Frey and Michael Osborne of the Oxford Martin School argued that employees engaged in "tasks following well-defined procedures that can easily be performed by sophisticated algorithms" are at risk of displacement, and 47% of jobs in the US were at risk.

The study, released as a working paper in 2013 and published in 2017, predicted that Automation would put low-paid physical occupations most at risk, by surveying a group of colleagues on their opinions.[61] However, according to a study published in McKinsey Quarterly[62] in 2015 the impact of computerization in most cases is not the replacement of employees but Automation of portions of the tasks they perform.[63] The methodology of the McKinsey study has been heavily criticized for being intransparent and relying on subjective assessments.[64] The methodology of Frey and Osborne has been subjected to criticism, as lacking evidence, historical awareness, or credible methodology.[65][66] In addition the OECD, found that across the 21 OECD countries, 9% of jobs are automatable.[67] The Obama administration has pointed out that every 3 months "about 6 percent of jobs in the economy are destroyed by shrinking or closing businesses, while a slightly larger percentage of jobs are added."[68] A recent MIT economics study of Automation in the United States from 1990 to 2007 found that there may be a negative impact on employment and wages when robots are introduced to an industry.

When one robot is added per one thousand workers, the employment to population ratio decreases between 0.18–0.34 percentages and wages are reduced by 0.25–0.5 percentage points.

During the time period studied, the US did not have many robots in the economy which restricts the impact of Automation.

However, Automation is expected to triple (conservative estimate) or quadruple (a generous estimate) leading these numbers to become substantially higher.[69] Based on a formula by Gilles Saint-Paul, an economist at Toulouse 1 University, the demand for unskilled human capital declines at a slower rate than the demand for skilled human capital increases.[70] In the long run and for society as a whole it has led to cheaper products, lower average work hours, and new industries forming (i.e., robotics industries, computer industries, design industries).

These new industries provide many high salary skill-based jobs to the economy.

By 2030, between 3 and 14 percent of the global workforce will be forced to switch job categories due to Automation eliminating jobs in an entire sector.

While the number of jobs lost to Automation is often offset by jobs gained from technological advances, the same type of job loss is not the same one replaced and that leading to increasing unemployment in the lower-middle class.

This occurs largely in the US and developed countries where technological advances contribute to higher demand for highly skilled labor but demand for middle-wage labor continues to fall.

Economists call this trend "income polarization" where unskilled labor wages are driven down and skilled labor is driven up and it is predicted to continue in developed economies.[71] Unemployment is becoming a problem in the United States due to the exponential growth rate of Automation and technology.

According to Kim, Kim, and Lee (2017:1), "[a] seminal study by Frey and Osborne in 2013 predicted that 47% of the 702 examined occupations in the United States faced a high risk of decreased employment rate within the next 10–25 years as a result of computerization." As many jobs are becoming obsolete, which is causing job displacement, one possible solution would be for the government to assist with a universal basic income (UBI) program.

UBI would be a guaranteed, non-taxed income of around $1000 dollars per month, paid to all U.S.

citizens over the age of 21.

UBI would help those who are displaced, take on jobs that pay less money and still afford to get by.

It would also give those that are employed with jobs that are likely to be replaced by Automation and technology, extra money to spend on education and training on new demanding employment skills.

UBI however, should be seen as a short-term solution because it doesn't fully address the issue of income inequality which will be exacerbated by job displacement.

Lights-out manufacturing is a production system with no human workers, to eliminate labor costs.

Lights out manufacturing grew in popularity in the U.S.

when General Motors in 1982 implemented humans "hands-off" manufacturing in order to "replace risk-averse bureaucracy with Automation and robots".

However, the factory never reached full "lights out" status.[72] The expansion of lights out manufacturing requires:[73] The costs of Automation to the environment are different depending on the technology, product or engine automated.

There are automated engines that consume more energy resources from the Earth in comparison with previous engines and vice versa.[citation needed] Hazardous operations, such as oil refining, the manufacturing of industrial chemicals, and all forms of metal working, were always early contenders for Automation.[dubious – discuss][citation needed] The Automation of vehicles could prove to have a substantial impact on the environment, although the nature of this impact could be beneficial or harmful depending on several factors.

Because automated vehicles are much less likely to get into accidents compared to human-driven vehicles, some precautions built into current models (such as anti-lock brakes or laminated glass) would not be required for self-driving versions.

Removing these safety features would also significantly reduce the weight of the vehicle, thus increasing fuel economy and reducing emissions per mile.

Self-driving vehicles are also more precise with regard to acceleration and breaking, and this could contribute to reduced emissions.

Self-driving cars could also potentially utilize fuel-efficient features such as route mapping that is able to calculate and take the most efficient routes.

Despite this potential to reduce emissions, some researchers theorize that an increase of production of self-driving cars could lead to a boom of vehicle ownership and use.

This boom could potentially negate any environmental benefits of self-driving cars if a large enough number of people begin driving personal vehicles more frequently.[74] Automation of homes and home appliances is also thought to impact the environment, but the benefits of these features are also questioned.

A study of energy consumption of automated homes in Finland showed that smart homes could reduce energy consumption by monitoring levels of consumption in different areas of the home and adjusting consumption to reduce energy leaks (e.g.

automatically reducing consumption during the nighttime when activity is low).

This study, along with others, indicated that the smart home's ability to monitor and adjust consumption levels would reduce unnecessary energy usage.

However, new research suggests that smart homes might not be as efficient as non-automated homes.

A more recent study has indicated that, while monitoring and adjusting consumption levels does decrease unnecessary energy use, this process requires monitoring systems that also consume a significant amount of energy.

This study suggested that the energy required to run these systems is so much so that it negates any benefits of the systems themselves, resulting in little to no ecological benefit.[75] Another major shift in Automation is the increased demand for flexibility and convertibility in manufacturing processes.

Manufacturers are increasingly demanding the ability to easily switch from manufacturing Product A to manufacturing Product B without having to completely rebuild the production lines.

Flexibility and distributed processes have led to the introduction of Automated Guided Vehicles with Natural Features Navigation.

Digital electronics helped too.

Former analog-based instrumentation was replaced by digital equivalents which can be more accurate and flexible, and offer greater scope for more sophisticated configuration, parametrization, and operation.

This was accompanied by the fieldbus revolution which provided a networked (i.e.

a single cable) means of communicating between control systems and field-level instrumentation, eliminating hard-wiring.

Discrete manufacturing plants adopted these technologies fast.

The more conservative process industries with their longer plant life cycles have been slower to adopt and analog-based measurement and control still dominates.

The growing use of Industrial Ethernet on the factory floor is pushing these trends still further, enabling manufacturing plants to be integrated more tightly within the enterprise, via the internet if necessary.

Global competition has also increased demand for Reconfigurable Manufacturing Systems.

Engineers can now have numerical control over automated devices.

The result has been a rapidly expanding range of applications and human activities.

Computer-aided technologies (or CAx) now serve as the basis for mathematical and organizational tools used to create complex systems.

Notable examples of CAx include Computer-aided design (CAD software) and Computer-aided manufacturing (CAM software).

The improved design, analysis, and manufacture of products enabled by CAx has been beneficial for industry.[76] Information technology, together with industrial machinery and processes, can assist in the design, implementation, and monitoring of control systems.

One example of an industrial control system is a programmable logic controller (PLC).

PLCs are specialized hardened computers which are frequently used to synchronize the flow of inputs from (physical) sensors and events with the flow of outputs to actuators and events.[77] Human-machine interfaces (HMI) or computer human interfaces (CHI), formerly known as man-machine interfaces, are usually employed to communicate with PLCs and other computers.

Service personnel who monitor and control through HMIs can be called by different names.

In industrial process and manufacturing environments, they are called operators or something similar.

In boiler houses and central utilities departments they are called stationary engineers.[78] Different types of Automation tools exist: Host simulation software (HSS) is a commonly used testing tool that is used to test the equipment software.

HSS is used to test equipment performance with respect to factory Automation standards (timeouts, response time, processing time).[79] Cognitive Automation, as a subset of artificial intelligence, is an emerging genus of Automation enabled by cognitive computing.

Its primary concern is the Automation of clerical tasks and workflows that consist of structuring unstructured data.[80] Cognitive Automation relies on multiple disciplines: natural language processing, real-time computing, machine learning algorithms, big data analytics, and evidence-based learning.[81] According to Deloitte, cognitive Automation enables the replication of human tasks and judgment "at rapid speeds and considerable scale."[82] Such tasks include: Technologies like solar panels, wind turbines, and other renewable energy sources—together with smart grids, micro-grids, battery storage—can automate power production.

Many supermarkets and even smaller stores are rapidly introducing Self checkout systems reducing the need for employing checkout workers.

In the United States, the retail industry employs 15.9 million people as of 2017 (around 1 in 9 Americans in the workforce).

Globally, an estimated 192 million workers could be affected by Automation according to research by Eurasia Group.[83] Online shopping could be considered a form of automated retail as the payment and checkout are through an automated Online transaction processing system, with the share of online retail accounting jumping from 5.1% in 2011 to 8.3% in 2016[citation needed].

However, two-thirds of books, music, and films are now purchased online.

In addition, Automation and online shopping could reduce demands for shopping malls, and retail property, which in America is currently estimated to account for 31% of all commercial property or around 7 billion square feet.

Amazon has gained much of the growth in recent years for online shopping, accounting for half of the growth in online retail in 2016.[83] Other forms of Automation can also be an integral part of online shopping, for example, the deployment of automated warehouse robotics such as that applied by Amazon using Kiva Systems.

Food and drink The food retail industry has started to apply Automation to the ordering process; McDonald's has introduced touch screen ordering and payment systems in many of its restaurants, reducing the need for as many cashier employees.[84] The University of Texas at Austin has introduced fully automated cafe retail locations.[85] Some Cafes and restaurants have utilized mobile and tablet "apps" to make the ordering process more efficient by customers ordering and paying on their device.[86] Some restaurants have automated food delivery to customers tables using a Conveyor belt system.

The use of robots is sometimes employed to replace waiting staff.[87] Automated mining involves the removal of human labor from the mining process.[88] The mining industry is currently in the transition towards Automation.

Currently, it can still require a large amount of human capital, particularly in the third world where labor costs are low so there is less incentive for increasing efficiency through Automation.

The Defense Advanced Research Projects Agency (DARPA) started the research and development of automated visual surveillance and monitoring (VSAM) program, between 1997 and 1999, and airborne video surveillance (AVS) programs, from 1998 to 2002.

Currently, there is a major effort underway in the vision community to develop a fully-automated tracking surveillance system.

Automated video surveillance monitors people and vehicles in real time within a busy environment.

Existing automated surveillance systems are based on the environment they are primarily designed to observe, i.e., indoor, outdoor or airborne, the number of sensors that the automated system can handle and the mobility of sensor, i.e., stationary camera vs.

mobile camera.

The purpose of a surveillance system is to record properties and trajectories of objects in a given area, generate warnings or notify designated authority in case of occurrence of particular events.[89] As demands for safety and mobility have grown and technological possibilities have multiplied, interest in Automation has grown.

Seeking to accelerate the development and introduction of fully automated vehicles and highways, the United States Congress authorized more than $650 million over six years for intelligent transport systems (ITS) and demonstration projects in the 1991 Intermodal Surface Transportation Efficiency Act (ISTEA).

Congress legislated in ISTEA that:[90][T]he Secretary of Transportation shall develop an automated highway and vehicle prototype from which future fully automated intelligent vehicle-highway systems can be developed.

Such development shall include research in human factors to ensure the success of the man-machine relationship.

The goal of this program is to have the first fully automated highway roadway or an automated test track in operation by 1997.

This system shall accommodate installation of equipment in new and existing motor vehicles.Full Automation commonly defined as requiring no control or very limited control by the driver; such Automation would be accomplished through a combination of sensor, computer, and communications systems in vehicles and along the roadway.

Fully automated driving would, in theory, allow closer vehicle spacing and higher speeds, which could enhance traffic capacity in places where additional road building is physically impossible, politically unacceptable, or prohibitively expensive.

Automated controls also might enhance road safety by reducing the opportunity for driver error, which causes a large share of motor vehicle crashes.

Other potential benefits include improved air quality (as a result of more-efficient traffic flows), increased fuel economy, and spin-off technologies generated during research and development related to automated highway systems.[91] Automated waste collection trucks prevent the need for as many workers as well as easing the level of labor required to provide the service.[92] Business process Automation (BPA) is the technology-enabled Automation of complex business processes.[93] It can help to streamline a business for simplicity, achieve digital transformation, increase service quality, improve service delivery or contain costs.

BPA consists of integrating applications, restructuring labor resources and using software applications throughout the organization.

Robotic process Automation (RPA; or RPAAI for self-guided RPA 2.0) is an emerging field within BPA and uses artificial intelligence.

BPAs can be implemented in a number of business areas including marketing,[94] sales[95] and workflow.[96] Home Automation (also called domotics) designates an emerging practice of increased Automation of household appliances and features in residential dwellings, particularly through electronic means that allow for things impracticable, overly expensive

Sales force management system

Salesforce management systems (also sales force automation systems (SFA)) are information systems used in customer relationship management (CRM) marketing and management that help automate some sales and sales force management functions.

They are often combined with a marketing information system, in which case they are often called CRM systems.

An SFA, typically a part of a company's CRM system, is a system that automatically records all the stages in a sales process.

SFA includes a contact management system which tracks all contact that has been made with a given customer, the purpose of the contact, and any follow up that may be needed.

This ensures that sales efforts are not duplicated, reducing the risk of irritating customers.

SFA also includes a sales lead tracking system, which lists potential customers through paid phone lists, or customers of related products.

Other elements of an SFA system can include sales forecasting, order management and product knowledge.

More developed SFA systems have features where customers can actually model the product to meet their needs through online product building systems.

This is becoming popular in the automobile industry, where patrons can customize various features such as color and interior features such as leather vs.

upholstered seats.

An integral part of any SFA system is company-wide integration among different departments.

If SFA systems aren't adopted and properly integrated to all departments, there might be a lack of communication which could result in different departments contacting the same customer for the same purpose.

In order to mitigate this risk, SFA must be fully integrated in all departments that deal with customer service management.

Making a dynamic sales force links strategy and operational actions that can take place within a department.

the SFA relies on objectives, plans, budget, and control indicators under specific conditions.

In order to perform the objectives correctly, specific procedures must be implemented: The process usually starts from specific sales targets.

The command center analyzes the inputs and outputs established from a modeled control process and the sales force.

The control process enables the sales force to establish performance standards, measuring actual performance, comparing measured performance against established standards and taking corrective action.

The sales managers adjust their actions based on the overall process.

Aside from the control process, the following metrics are implemented: Five major activities are involved in staffing a sales force.

They must be divided into related steps.

The first step is plan the recruiting and selection process.

The responsibilities associated with this step are generally assigned to top sales executives, the field sales manager or the human resources manager.[1] The company wants to determine the number and type of people needed, which involves analyzing the market and the job and preparing a written job description.

The qualifications of the job must be established to fill the job.

Second, the recruiting phase includes identifying sources of recruits that are consistent with the type of person desired, selecting the source to be used and contacting the recruits.

You need to weigh out the options and evaluate its potential effectiveness versus its costs.

Third, select the most qualified applicants.

The selection phase has three steps, in the planning phase there may be qualifications specified and in the first step it is necessary to design a system for measuring the recruits against the standards from the planning phase.

Then the system must be put into effect with the new applicants and then making the actual selection is the final step.

The fourth activity is to hire those people who have been selected.

Just because one makes an offer does not mean that the job is done.

One must convince a recruit that the job offers everything that they need and want to get them to join a company or at least consider it.

The fifth activity is to assimilate the new hires into the company.

This is done by placing them under direction of an employee in the firm and possibly giving them a mentor to help them feel comfortable working in the firm and going through the training programs.

Sales-force automation systems vary in their capabilities.

They can vary depending on what information an organization needs.

The application also has implications based on an organization's size, organization rollup, demand of new system, sales processes, and number of users.

Depending on requirements, services can fall into one of two categories: With on-premises software, the customer manages and purchases the application.

On-premises software has some advantages and disadvantages.

The disadvantage of on-premises is the higher cost of the software, along with maintenance.

Customization is also needed for some who use additional processes outside of the normal out of the box solution.

Time is also a factor.

Many on-premises software implementations take longer - along with numerous testing and training sessions.

The overall advantage of on-premises software relates to overall return on investment.

Using the application for three to five years becomes more cost-effective.

Another advantage may depend on the amount of data.

With on-demand, certain volume restrictions hold, but with on-premises, data restrictions are based on the storage size of local hardware.

CRM is a mechanism which manages all the data of their customers, clients and other business partners in a single container.[citation needed] CRM with cloud computing allows businesses to keep stature of its customers from all its corners.[citation needed] Several tools can aid in automating sales activities.

The largest vendors are Salesforce.com, Microsoft Dynamics CRM, SAP AG and Oracle.

Many sales managers are always on the go.

The growth of smartphones has reignited the creation of mobile sales force automation systems.

Most companies IT departments are aware that adopting new abilities requires extensive testing.

Despite the time needed to test such a new product, it will pay off in the future for the sales department.

Smartphones appeal to salespeople because they are easy to carry and easy to use, show an appealing interface design, touchscreens and fast wireless network abilities.

More than 55% of global 2000 organization will deploy mobile SFA project by 2011 and newer Smartphone platforms, such as Apple's iOS and Google's Android, point to a future of increasing diversity in device selecting and support for sales force.[2] When implementing the mobile sales force automation application or during the first stage of systems development life cycle, project teams will need to evaluate how prospective solutions comprising mobile devices, software and support infrastructure and carrier services are packaged to deliver optimal system usability, manageability and integrative abilities, as well as scalability, reliability and performance.

Sales force automation systems can also create competitive advantage: The major disadvantages in Sales Force Management Systems are: Many organisations have found it difficult to persuade sales people to enter data into the system.

For this reason many[who?] have questioned the value of the investment.

Recent developments have embedded sales process systems that give something back to the seller within the CRM screens.

Because these systems help the sales person plan and structure their selling in the most effective way, increasing productivity, they give a reason to use the CRM.[citation needed]

Distribution (marketing)

Distribution (or place) is one of the four elements of the marketing mix.

Distribution is the process of making a product or service available for the consumer or business user who needs it.

This can be done directly by the producer or service provider, or using indirect channels with distributors or intermediaries.

The other three elements of the marketing mix are product, pricing, and promotion.

Decisions about distribution need to be taken in line with a company's overall strategic vision and mission.

Developing a coherent distribution plan is a central component of strategic planning.

At the strategic level, there are three broad approaches to distribution, namely mass, selective and exclusive distribution.

The number and type of intermediaries selected largely depends on the strategic approach.

The overall distribution channel should add value to the consumer.

Distribution is fundamentally concerned with ensuring that products reach target customers in the most direct and cost efficient manner.

In the case of services, distribution is principally concerned with access.[1] Although distribution, as a concept, is relatively simple, in practice distribution management may involve a diverse range of activities and disciplines including: detailed logistics, transportation, warehousing, storage, inventory management as well as channel management including selection of channel members and rewarding distributors.[2] Prior to designing a distribution system, the planner needs to determine what the distribution channel is to achieve in broad terms.

The overall approach to distributing products or services depends on a number of factors including the type of product, especially perishability; the market served; the geographic scope of operations and the firm's overall mission and vision.

The process of setting out a broad statement of the aims and objectives of a distribution channel is a strategic level decision.

Strategically, there are three approaches to distribution:[3] Summary of strategic approaches to distribution In consumer markets, another key strategic level decision is whether to use a push or pull strategy.

In a push strategy, the marketer uses intensive advertising and incentives aimed at distributors, especially retailers and wholesalers, with the expectation that they will stock the product or brand, and that consumers will purchase it when they see it in stores.

In contrast, in a pull strategy, the marketer promotes the product directly to consumers hoping that they will pressure retailers to stock the product or brand, thereby pulling it through the distribution channel.[7] The choice of a push or pull strategy has important implications for advertising and promotion.

In a push strategy, the promotional mix would consist of trade advertising and sales calls while the advertising media would normally be weighted towards trade magazines, exhibitions, and trade shows while a pull strategy would make more extensive use of consumer advertising and sales promotions while the media mix would be weighted towards mass-market media such as newspapers, magazines, television and radio.[8] Distribution of products takes place by means of a marketing channel, also known as a distribution channel.

A marketing channel is the people, organizations, and activities necessary to transfer the ownership of goods from the point of production to the point of consumption.

It is the way products get to the end-user, the consumer.

This is mostly accomplished through merchant retailers or wholesalers or, in the international context, by importers.

In certain specialist markets, agents or brokers may become involved in the marketing channel.

Typical intermediaries involved in distribution include: A firm can design any number of channels they require to reach customers efficiently and effectively.

Channels can be distinguished by the number of intermediaries between producer and consumer.[5] If there are no intermediaries then this is known as a zero-level distribution system or direct marketing.

A level one (sometimes called one-tier) channel has a single intermediary.

A level two (alternatively a two-tier) channel has two intermediaries, and so on.

This flow is typically represented as being manufacturer to retailer to consumer, but may involve other types of intermediaries.

In practice, distribution systems for perishable goods tend to be shorter - direct or single intermediary, because of the need to reduce the time a product spends in transit or in storage.

In other cases, distribution systems can become quite complex involving many levels and different types of intermediaries.

In practice, many organizations use a mix of different channels; a direct sales force may call on larger customers may be complemented with agents to cover smaller customers and prospects.

When a single organisation uses a variety of different channels to reach its markets, this is known as a multi-channel distribution network.

In addition, online retailing or e-commerce is leading to disintermediation, the removal of intermediaries from a supply chain.

Retailing via smartphone or m-commerce is also a growth area.

The firm's marketing department needs to design the most suitable channels for the firm's products, then select appropriate channel members or intermediaries.

An organisation may need to train staff of intermediaries and motivate the intermediary to sell the firm's products.

The firm should monitor the channel's performance over time and modify the channel to enhance performance.

To motivate intermediaries the firm can use positive actions, such as offering higher margins to the intermediary, special deals, premiums and allowances for advertising or display.[5] On the other hand, negative actions may be necessary, such as threatening to cut back on margin, or hold back delivery of product.

Care must be exercised when considering negative actions as these may fall foul of regulations and can contribute to a public backlash and a public relations disaster.

Channel conflict can arise when one intermediary's actions prevent another intermediary from achieving their objectives.[5] Vertical channel conflict occurs between the levels within a channel, and horizontal channel conflict occurs between intermediaries at the same level within a channel.

Channel conflict is a perennial problem.

There are risks that a powerful channel member may coordinate the interests of the channel for personal gain.[11] Channel-switching (not to be confused with zapping or channel surfing on TV) is the action of consumers switching from one type of channel intermediary to a different type of intermediary for their purchases.

Examples include switching from brick-and-mortar stores to online catalogues and e-commerce providers; switching from grocery stores to convenience stores or switching from top tier department stores to mass market discount outlets.[12] A number of factors have led to an increase in channel switching behaviour; the growth of e-commerce, the globalization of markets, the advent of Category killers (such as Officeworks and Kids 'R Us) as well as changes in the legal or statutory environment.

For instance, in Australia and New Zealand, following a relaxation of laws prohibiting supermarkets from selling therapeutic goods, consumers are gradually switching away from pharmacies and towards supermarkets for the purchase of minor analgesics, cough and cold preparations and complementary medicines such as vitamins and herbal remedies.[13] For the consumer, channel switching offers a more diverse shopping experience.

However, marketers need to be alert to channel switching because of its potential to erode market share.

Evidence of channel switching can suggest that disruptive forces are at play, and that consumer behaviour is undergoing fundamental changes.

A consumer may be prompted to switch channels when the product or service can be found at cheaper prices, when superior models become available, when a wider range is offered, or simply because it is more convenient to shop through a different channel (e.g.

online or one-stop shopping).[14] As a hedge against market share losses due to switching behaviour, some retailers engage in multi-channel retailing.[15] The emergence of a service-dominant logic perspective has focussed scholarly attention on how distribution networks serve to create customer value and to consider how value is co-created by all the players within the distribution chain, including the value created by customers themselves.[16] This emphasis on value-creation is contributing to a change in terminology surrounding distribution processes; "distribution networks" are often termed value-chains while "distribution centres" are often termed customer fulfillment centres.

For example, the retail giant Amazon, which utilises both direct online distribution alongside bricks and mortar stores, now calls its despatch centres "customer fulfillment centres".[17] Although the term, "customer fulfillment centre" has been criticised on the grounds that it is a neologism, its use is becoming increasingly mainstream as it slowly makes its way into introductory marketing textbooks.[18] Disintermediation occurs when manufacturers or service providers eliminate intermediaries from the distribution network and deal directly with purchasers.

Disintermediation is found in industries where radically new types of channel intermediaries displace traditional distributors.

The widespread public acceptance of online shopping has been a major trigger for disintermediation in some industries.

Certain types of traditional intermediaries are dropping by the wayside.[19]

Demand generation

Demand generation is the focus of targeted marketing programs to drive awareness and interest in a company's products and/or services.[1] Commonly used in business-to-business, business-to-government, or longer business-to-consumer sales cycles, Demand generation involves multiple areas of marketing and is really the marriage of marketing programs coupled with a structured sales process.[2] There are multiple components of a stepped Demand generation process that vary based on the size and complexity of a sale.

These components include, among other things: building awareness, positioning relevance, supporting validation and mitigating customer evaluation.

Useful Demand generation methodologies include AIDA (attract Attention, maintain Interest, create Desire, get Action), developed by E.

St.

Elmo Lewis.

Demand generation is a holistic approach to marketing and sales cohesion within the company.[3] Through various nurture campaigns and marketing approaches, Demand generation efforts aim to both create a long-term relationship between a brand and a potential buyer, and at the same time gauge and develop a prospect's purchasing interest in said brand's products/services.[4][5] Building brand or product/service awareness is a vital component in the Demand generation process, and often takes a continued effort and involves multiple facets of marketing.[5] Advanced Demand generation programs typically rely on some form of proactive Lead Generation activities supported by more traditional market programs and processes.

This is because Demand generation programs tend to assume that prospective customers are aware that they have a need or problem, and are attempting to solve it when they search for solutions.

If the prospect is unaware (consciously or, at least, subconsciously) that they have the problem, then Demand generation may not be effective - thus the need for adjunct lead generation activities.

The second key area of focus for a marketer focused on Demand generation is ensuring that when a prospect decides to seek a vendor to provide a solution in a given solution category, they discover the vendor that the marketer serves.

This is again accomplished with a variety of techniques and tools, often overlapping with the tools used for creating awareness of the category, but with a different emphasis.

Again, in this phase of the Demand generation process, many approaches and tools are used and this list is only a selection of the more common approaches.

Often confused with Demand generation is the lead process itself.

Converting demand into sales is a totally separate task.

Many companies, however, will call themselves Demand generation organizations when they are really lead generating.[10] This later phase of the buying process involves validating that a selected vendor will meet specified requirements, coming to an agreement with the vendor on costs, contract terms, support and services, and finalizing the purchase process.

This often involves coordinating the involvement of other organizational and extra-organizational resources such as sales representatives and reference clients.

The coordination of sales involvement, the selection of the right sales resource, and the timing of the involvement can be difficult to determine.

The scoring, ranking, and routing of leads into sales is a sufficiently deep topic to warrant further exploration.

The involvement of sales professionals in the solution validation process involves three main aspects.

These are the same whether inside sales or field sales professionals are being involved.

In order to effectively manage and optimize the required communication, response, and lead management processes outlined above, marketers focused on Demand generation must become proficient at two other related disciplines

SugarCRM

SugarCRM is a software company based in Cupertino, California.

It produces the web application Sugar, a customer relationship management (CRM) system.

SugarCRM's functionality includes sales-force automation, marketing campaigns, customer support, collaboration, Mobile CRM, Social CRM and reporting.

The company operates a number of websites, including its commercial website SugarCRM.com and Sugar Exchange (for third-party extensions), and user forums.

As of 2017, SugarCRM reported two million users.[4][better source needed] In February 2014, in a blog post that provoked a strong reaction from the development community, SugarCRM announced that they would no longer be releasing new open-source versions of their Community Edition application; from now on this would be a bug-fix-only application.[5] John Roberts conceived of the idea and name of SugarCRM while riding his mountain bike named Sugar in the Santa Cruz Mountains.

Clint Oram, John Roberts, and Jacob Taylor started full-time work on the SugarCRM open source project in April 2004, and incorporated the company in California in June 2004.

Roberts served as the CEO from 2004 to 2009, Oram was the vice president, and Taylor was the CTO & vice president of engineering.

In June 2004, Josh B.

Stein of DFJ invested $2 million into the startup and became a board member.

With the help of this investment, Sugar expanded quickly and by September 2004, potential users had downloaded 25,000 copies of the application, then named Sugar Open Source.

In October 2004, the company was named "Project of the Month" on Sourceforge.[6] The popularity of this project allowed the company to raise $86 million of venture capital from Draper Fisher Jurvetson, Walden International, New Enterprise Associates and Goldman Sachs.[7] In 2006, SugarCRM launched SugarCon, a conference for Sugar customers, users and developers.

It has since become an annual conference, held in the San Francisco Bay Area[8] to begin with but in 2018 the conference was moved to Las Vegas.[9] By 2008, SugarCRM employed over 150 people.[10] In June 2008, co-founder Taylor left the company, during what technology website The Register called "a mysterious exodus of senior and experienced business staff" from SugarCRM.[11] Clint Oram replaced him as the CTO.[citation needed] In May 2009, co-founder and CEO Roberts left the company.

He was replaced as CEO by SugarCRM board member Larry Augustin, who had previously founded and served as the CEO of VA Linux (now known as Geeknet).[11] In June 2010, Sugar launched Sugar 6, a major upgrade emphasizing ease of use and introducing a complete UI overhaul of Sugar Professional and Sugar Enterprise.[12] In June 2017, SugarCRM released SugarCRM Hint, a new product[13][14] which searches the web for additional information on users in SugarCRM.[15] Private equity firm Accel-KKR became a single investor in August 2018, describing the investment as being "nine figures".[16] SugarCRM sells CRM software, typically referred to as Sugar, in three editions:[17] Each product derives from the same code tree.

The products originated on the LAMP stack (Linux, Apache, MySQL and PHP) but also run on other PHP-capable platforms (such as Windows, Solaris and Mac OS X).

SugarCRM can also use MS IIS as a web server, DB2 and MS SQL or Oracle as alternative databases.[citation needed] SugarCRM provided a community edition, Sugar CE, previously known as Sugar Open Source.

It was available free of charge alongside paid editions until version 6.5.

In 2013, Sugar version 7 was announced but was only released in Sugar's hosted paid environment.

No update to the community edition was announced with it.

SugarCRM's community support team have stated that 7.0 will not be available in a community edition, and that no release date for an updated community edition was known.[18] After that SugarCRM released a notice saying that they "have no plans" to release 7 to Open Source.

In April 2018, Clint Oram, CMO & Founder of SugarCRM, Inc., posted to the company's community blog that the Community Edition open source project had officially ended.[19] Sugar is a software as a service (SaaS) product.

As of Sugar 7, customers can opt to use an on-premises product, SugarCRM's Sugar Cloud, one of SugarCRM's partners, or public cloud services (such as Amazon Web Services, Windows Azure, Rackspace Cloud or IBM SmartCloud).[citation needed] SugarCRM initially licensed Sugar Open Source under the SugarCRM Public License (based on the Mozilla Public License and the Attribution Assurance License).

While users could freely redistribute Sugar Open Source and the license allowed for the inspection and modification of the source code and for the creation of derived works, critics, including Dan Farber, editor in chief at CNET, expressed some concern over SugarCRM's use of the term "commercial open source" to describe its products.[20] On July 25, 2007, SugarCRM announced the adoption of the GNU General Public License (version 3) for Sugar Community Edition, the offering previously known as Sugar Open Source.[21] This license took effect with the release of Sugar Community Edition 5.0.

On April 11, 2010, SugarCRM announced that starting with version 6.0.0, the Sugar Community Edition would be licensed under the GNU Affero General Public License version 3.[22] The charts module, customer portal, mobile support, some SOAP functions and most of the default theme templates were removed from the AGPLv3 licensed Sugar Community Edition 6.[citation needed] In 2020, a statement "SugarCRM is not an open source solution" could be found on SugarCRMs website.[23]

Oracle CRM

Oracle hired Mark Barrenechea in 1996, who formed a "Front Office" team within Oracle Application division in 1997.

That team evolved into the CRM division of Oracle in 1998, and launched products like Oracle Sales Online, Oracle Marketing Online in the following years, competing with Siebel Systems and Salesforce.com.

Oracle became a leading player in the CRM market following its acquisition of Siebel Systems in September 2006 and later acquired UpShot CRM which offered a more robust user interface than the legacy Siebel On Demand product.[citation needed] Today Oracle CRM is divided into different product lines.

Siebel 8.1.1 is the latest release of their on-premises solution.[buzzword][1] Oracle CRM On Demand Release 26 and Oracle Sales Cloud Release 10 are the latest releases of their SaaS solutions.[buzzword] Oracle CRM On Premises is a traditional on-premises deployment where the customer is required to buy or lease infrastructure, including hardware, operating systems and databases, and install a packaged system in its data center.

In 2006, Forester Research estimated that on-premises solutions[buzzword] make up about 90 percent of CRM sales.[2] On-premises solutions[buzzword] are most suitable for organisations that need complete ownership and control over the deployment and maintenance of their CRM application and infrastructure.

They are also most suitable for integration with operational and legacy applications.

Some CRM providers and specialized third parties offer customized vertical industry solutions[buzzword] that extend on-premises deployments.

CRM On Demand[3] and Oracle Sales Cloud are cloud CRM solutions[buzzword] which are accessible over the internet and paid for by a monthly subscription charge.

This method of using software is often called software-as-a-service (SaaS) and is available to authorized users with a web browser.

The benefits of a SaaS solution[buzzword] are that there is no hardware requirement and minimal setup cost.[citation needed] Oracle Social CRM was released in 2008 and combines traditional enterprise CRM capabilities with social networking and Web 2.0 technologies.[4] The applications are designed to reflect the way sales people work by helping them identify qualified leads, develop sales campaigns and collaborate with colleagues.[citation needed] Other Social CRM Applications include Oracle Sales Prospector, Sales Campaigns and Sales Library.

These applications are designed to work with various CRM applications from Oracle and competitors.

These applications are provided using SaaS and paid for by a monthly subscription.

PeopleSoft Enterprise Customer Relationship Management is a family of applications in Oracle's PeopleSoft Enterprise product suite.

PeopleSoft merged with Oracle in 2005 and integrated product lines under the Oracle PeopleSoft name.

Features of Oracle’s Siebel CRM include:

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