Social media data mining has changed leaps and bounds from what it was considered a decade ago. Take for instance, Facebook advertisements know exactly what type of shoes or dress you are looking for? Or for that matter, your favorite café launches a promotion for your favorite meal.

As platforms like Facebook, Twitter, Instagram, etc. permeate our daily lives, growth-focused business players are leveraging these huge amounts of data generated to gain a competitive advantage in the industry. This consequently ushers them into the age of social media data mining. Let’s begin with understanding what data mining in social media is.

Social Media Data Mining – The New Business Imperative

As the name suggests, data from social media platforms is collected and analyzed to predict patterns and forecast trends. Facebook, Twitter, Instagram, Snapchat, etc. use algorithms to track as well as organize likes, clicks, page views, and other user interactions. This collective data is then applied to inform marketing and research processes. Mentioned here are some of the significant use cases of social media data mining:

• · Influencer Marketing

The insights derived from social media data mining allows businesses in identifying influencers—or users which have a strong presence in terms of follower bases and engagement rates on social platforms. Leveraging influencer marketing enables companies to bring attention to their services/products since they can help in driving hits and clicks via a previously untapped sales channel.

• · Targeted Advertising

Targeted advertising and optimized campaigns on social media platforms are skyrocketing since businesses figure out better ways to locate and address certain audiences. Digital marketers can use different data mining techniques to figure out what is the best time to run a specific ad on a particular digital platform. Also, they can find out which messages are most effective among certain demographic groups.

• Sales Enablement

Apart from gauging information on proprietary products, the stakeholders can also collect information about partners’ offerings or prospective clients to leverage in a unique sales pitch. On the other hand, customer feedback can be used to improvise the brand sentiment.

• Market Research

Data mining in social media enables companies to learn more about customer preferences, tastes, and biases. Take, for instance, a company that can determine public sentiment towards a certain logo or brand, or examine the demographic characteristics of emerging religious client groups, or for that matter politicians and religious groups. Hence, they can use this data to collate intelligence on potential partners, specific geographies, or peers.

Way Forward – Future of Social Media Data Mining

Professional data mining companies purchase/gauge out data from different social media sites. Besides, they also scrape data from blogs, forums, news sites, and other public pages where users interact with specific groups or leave comments. This pooled unstructured data in the form of posts, images, profiles, connections, etc., are used to identify behavioral patterns.

While some organizations have regularly collected user data for years, the advent of new-age cognitive technologies has made social media data mining increasingly sophisticated. Artificial intelligence and machine learning can not only analyze vast quantities of data but can also interpret acronyms, jargon, tone to capture context as well as provide a better measure of user sentiment.

Owing to such reasons, eminent industry leaders are bent on using social intelligence to informed decisions across product, marketing and customer services. Nevertheless, businesses must walk a fine line between coming off as overly intrusive and catering to specific audiences. Data breaches are still a major concern for users. Laws around social media data mining are still evolving, and organizations must police themselves to remain ethical.