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Artificial intelligence has forever changed the way that marketing is structured. Marketing’s main concepts are understanding what customers need, matching them to products and services, and persuading them to buy. These are all jobs that were previously complicated for humans to perform. Artificial intelligence is dramatically enhancing the advertising processes. 

Primary data is made up of statistics and very intricate numbers. Secondary data consists of surveys, questionnaires, polls, etc.  In marketing, secondary data is most focused on when starting research on a market segment. This is because it is cheaper, faster, and more direct when trying to target people’s specific personal opinions. In contrast, primary data costs lots of money to gain access to and takes much more time to be evaluated. With the use of algorithms, agencies are able to collect primary data more efficiently and cost effectively. For example, the social media app, Instagram, provides every business account with “insights” and “impressions”. Insights and impressions consist of a variety of graphs. The graphs reveal an account’s views, shares, viewer’s locations, viewer’s gender, etc. With the use of Instagram stories “polls”, influencers and companies are able to receive secondary data directly from their followers. This is all free, and given almost immediately after a post. These insights are instant gratification for marketers and or influencers. 

Specifically, through tracking buying patterns, companies are able to target consumers with advertisements catered to their interests. Unfortunately, user’s data that is collected typically results in forming stereotypes, targeting, biases, etc. These robots make assumptions based on your searches or clicks. 

In fact, a study was performed where Target was able to predict whether women were pregnant, just based on their buying patterns. Target's statistician Andrew Pole used analytics to notice when women purchased large quantities of unscented lotion at the beginning of their second trimester. Andrew Pole’s data also revealed when women purchased large amounts of calcium, magnesium, and zinc within their first 20-weeks of pregnancy. This study displays how analytics are used to predict purchase behavior and profile consumers. Many of these women had not even told close friends and family yet about their pregnancy, but Target already knew about how far along they were. Although the algorithms do not know people personally, they can still predict every one of your actions online. 

These algorithms impact many users psychologically. Financial targeting is one of the most obvious online. Due to the overuse of algorithms, companies are able to track the spending of consumers. For instance, tracking how often you purchase products from websites, what your searches are for, etc. For consumers with bad financial habits or poor money management, they are hurt the most. AI actually assists in upselling and cross-selling. It can reduce the likelihood that customers will abandon their online shopping carts. Constantly receiving promotions and advertisements may be too tempting for some. The algorithms also cause people to question who they are and if they truly know themselves. For users that struggle with their mental health, this is especially dangerous. Obviously, social media is addictive, and always being shown other people’s lives can have its consequences on our mental health.