In 2012 a writer for the New York Times named Charles Duhigg wanted to explore how retailers were using the data they had begun collecting involving customer purchases. What he found was stunning for the times, what some might call “creepy.” As the pandemic has progressed in the world, a recent shopper survey found people are now spending up to 30% more on-line now. Big data and developments in artificial intelligence is shaping your shopping experience.

In 2012, a statistician at Target named Andrew Pole began looking into purchasing “cues” found in their databases for those women expecting a child. He started by looking at women who had signed up for their Target baby registries in the past and looked at their previous purchases. One data analyst working with Pole found women on the registry bought larger quantities of unscented baby lotion as they entered their second trimester. They then found pregnant women began buying more scent-free soap and extra big bags of cotton balls. The data team constructed twenty or so buying “cues” that indicated an individual was pregnant.

Target then began a marketing campaign sending coupons for baby clothes to those women portraying the targeted purchasing pattern. As the story goes, Target received a letter in the mail from a father complaining that his daughter in high school received these coupons for baby clothes stating “Are you trying to encourage her to get pregnant?” The store manager called to apologize to the father, only to have the father respond that her daughter had told her she was due in August.

Fast forward to the present day as purchasing goods and services on-line has accelerated the collection of vast amounts of data from the 76% of Americans that shopped on-line just last year. More products are available for purchase than ever before, but shoppers do experience shoppers fatigue in deciding from all the choices. If you go to Wayfair’s website to search for coffee mugs, you will have 37,173 varieties to choose! This has led to some shoppers to exit the site unable to decide and failing to purchase a mug.

To enhance the shopping experience retailers and increase their online sales, retailers are adding enhanced search and recommendation engines. These sophisticated algorithms take the data and predict what the customer wants, showing them 3 to 5 choices from a wide variety of mugs to choose from. In the last five years the company’s success rate has jumped over 50%.

Shopper data collected consists of past purchases, gender, age, and other criteria only known to the company. Now companies break down key characteristics of each purchase ranging from color to functionality. Databases include what else you have searched for, detailing characteristics of the search from vacations to favorite celebrity clothing styles. Software now uses these data patterns to predict goods and services you are searching for, prioritizing and targeting the top choices to show you. This form of artificial intelligence also learns from its mistakes, improving its prediction for the next purchase.

As e-commerce continues to collect data and develop software that learns what you need before you need it, will it present you with the ideal Christmas/birthday present for your friends? Does a company ship you Benadryl as allergy season approaches and it sees you buying more tissue? Only time will tell how convenient or “creepy” it will get!

Dr. Steve Patchin is Superintendent of Hancock Public Schools. Programs he has contributed to creating include Mind Trekkers and CareerFEST, helping students explore their talents and associated careers in STEM. His research has focused on increasing development of self-efficacy in individual students.