How Target Used AI To Become A Retail Giant

Target, the Minneapolis-based retail giant, has undergone 5 redesign since 1962. Not only have the designs changed but they have also introduced a new world of retail with the help of AI. They never shied away from using the cutting edge technology and today are at the forefront of AI adoption in the retail sector. Target achieves its target by helping customers experience a whole new shopping experience with AI.

Early AI Implementations

Target's journey with AI began over a decade ago when the company started building a vast data warehouse and implementing extensive data-mining approaches. By assigning each shopper a unique Guest ID number linked to their credit card, name, or email address, Target created a comprehensive database storing information on purchases and demographic details. This robust dataset formed the foundation for predictive analytics, allowing Target to uncover subtle patterns and correlations in customer behavior.

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One significant early use of AI at Target was to forecast customer pregnancies. Andrew Pole, Target's statistician, discovered numerous significant patterns suggesting a customer's pregnant status after meticulously analysing past purchase data. For example, an increase in the purchase of unscented lotion during the second trimester proved to be a reliable signal. Furthermore, the increasing consumption of supplements such as calcium, magnesium, and zinc during the first 20 weeks became a critical indicator. Other obvious signals include the unexpected purchase of scent-free soap, larger bags of cotton balls, hand sanitizers, and washcloths, which frequently indicate an upcoming delivery date. This feature enabled Target to offer highly targeted coupons and promotions based on certain phases of pregnancy, illustrating the value of AI in personalised marketing.