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Predicting what shoppers will buy next has long been a dream for retailers, but very few have had the data or the technology to pull off that vision. One might argue that, in the fast-moving consumer goods space (e.g., grocery), predicting purchase intent is a little easier given the frequency of purchases, high basket sizes, and transaction and loyalty data.

However, most of these companies’ technology stacks falls short, particularly in the antiquated grocery industry. An exception to many rules in retail is Amazon, where households purchase across multiple categories at high frequencies, giving the retailer a more in-depth view of their customer’s buying habits.

But, that is truly an exception. Think about the more common scenario – an apparel retailer who may only sell to a particular customer a couple of times a year. That leaves the retailer with very little data to work with when it comes to determining behavior patterns or intent. And, even if your customers shop frequently and you have massive amounts of data on them – are you using it to make more money?

In her July 2015 article, “Who Owns The Customer Profile In Retail?,” RSR Managing Partner Nikki Baird notes that retailers understand that they don’t need data warehouses. According to Baird, “[Retailers] need a customer profile solution – one with a lot of data sources going in, and a lot of ways to reach out and connect those profiles to action systems like digital marketing platforms or email campaign tools. Or location-aware marketing through the retailer app on a customer’s phone. Or something else that hasn’t been invented yet.”



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Well, that day has come as we proudly unveil our artificial intelligence-powered personalization platform, Genie. Genie helps retail marketers accurately predict consumer purchase behavior, making it easier to target customers and prospects with contextually relevant messages. This is done by combining a retailer’s data, such as transaction and loyalty data, with demographics, location, time and other factors to predict a customer’s next purchase.

Sound too good to be true? In our early tests, Genie has delivered 72 percent accuracy when predicting next likely purchase at the category level and 45 percent accuracy predicting next likely purchase at the SKU level. This accuracy enables retailers to improve personalization and micro-targeting, resulting in:

  • More conversions
  • Higher redemption of coupons and promotions
  • Increased visit frequency, foot traffic, time in store and basket size
  • Greater brand affinity


Hiro Sake, a hand-crafted premium spirit company, is one of the first companies to implement Genie. The company’s co-founder and CEO, Carlos Anna, said, “Today’s consumer expects a personalized shopping experience. They’re willing to provide personal information about their shopping habits, but expect marketing messages that are specific to their wants and needs in return. Genie is the first recommendation engine that can anticipate a consumer’s needs based on the factors that drive purchase decisions, including location, price sensitivity and more.”

Interested in learning more about how Genie can help your organization drive sales across all channels? Set up a demo by contacting

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