Companies claim that customers aren’t “just a number to us,” but that’s more than a catchphrase for number-crunching analytics firm 84.51°.
The company is the recent spinoff of former Kroger-Tesco analytics joint venture dunnhumby, now wholly owned by US supermarket giant The Kroger Co. Renamed for the longitude of its Cincinnati headquarters and rebuilt from the ground up in 2015, 84.51° now focuses much of its activities on Kroger customers and partners, such as global consumer packaged goods companies. It believes that its core competitive differentiator is not technology, but rather its focus on helping customers build long-term relationships with their consumers and other customers. (The company says its new name also represents the “longitudinal view” it takes on understanding customer behavior.)
Most retailers rely on segmentation analysis to determine which promotions to send consumers, creating blocks of homogenous groups of people (such as single-parent households in middle-class neighborhoods). But 84.51° uses analytics differently, eschewing what CIO Yael Cosset calls an “archaic” approach in favor of a much more relevant, personalized one.
“We think of it as a snowflake, because we believe no two individuals are the same, and hence we should not engage them the same way, send them the same promotions,” he says.
So, for example, you might send a promotion for a particular kind of bottled water to consumers who have already demonstrated an affinity for that kind of product, but you wouldn’t send them a promotion for a cola drink just because the supplier is offering one. This is the kind of commitment necessary to develop long-term relationships with consumers, Cosset says.
The company goes beyond knowing which consumers like to buy bottled water or condiments; it tries to identify which ones prefer sparkling water to flat, or Dijon mustard to steak sauce. “You can’t do that with segmentation,” Cosset says.
That approach requires investing in the development of sophisticated algorithms that enables 84.51° to analyze millions of data points about each individual consumer, including their reactions to previous promotions.
Using Oracle Exadata and Oracle Big Data Appliance, teams of analysts and data scientists at 84.51° leverage a combination of conventional statistical packages and more advanced machine learning algorithms to generate the analytics foundation required to deliver personalization at scale.
A single campaign uses dozens of targeting models in combination with complex optimization algorithms to send the right offers to the right people. Often, offers are based on contextual cues gathered in real time and are specifically targeted for each customer.
“We spend a huge amount of time, money, and resources to really get solid sustainable data assets,” Cosset says. “Our data asset is a competitive advantage.”
Retailers cannot expect to build long-term, sustainable relationships with customers if they base the terms of those relationships on financial incentives alone, Cosset says. “They’re transactional, not relationship-based,” he says. “The real differentiator is what you do with the data—how do you provide real and relevant value to every single customer, how do you engage them the way that matters most to them, how do you create this personal relationship.”