Data-Driven Poster Child Tesco Loses Its Halo
Tesco had been recognized as a data-driven company that wowed investors. Now not so much, with its market value at an 11 year low. Investors are understandably disappointed. Should that give us pause about the value of customer data? Harvard Business Review might be making that case but we aren’t so sure. Tesco simply didn’t use data to support the customer experience. It seems to have used data to support the decisions it was already determined to make.
Tesco, Britain’s largest supermarket chain, got that way by pioneering the use of data specifically by mining data from their customer loyalty cards. Michael Schrage at Harvard Business Review writes:
With the notable exception of, say, an Amazon, no global store chain was thought to have demonstrably keener data-driven insight into customer loyalty and behavior.
Observers and those in the UK may already know that Tesco is on a downward spiral with it’s market value plummeting to an 11 year low. A big part of the problem seems to be a major gaffe the company made in estimating it’s profits. But there are other problems. Schrage continues
But the harsh numbers suggest that all this data, all this analytics, all the assiduous segmentation, customization and promotion have done little for Tesco’s domestic competitiveness since Leahy’s celebrated departure. As the Telegraph story further observed, “…judging by correspondence from Telegraph readers and disillusioned shoppers, one of the reasons that consumers are turning to [discounters] Aldi and Lidl is that they feel they are simple and free of gimmicks. Shoppers are questioning whether loyalty cards, such as Clubcard, are more helpful to the supermarket than they are to the shopper.”
Making The Anti-Data Case
That makes sense. But then Schrage begins to speculate.
How damning; how daunting; how disturbing for any and every serious data-driven enterprise and marketer. If true, Tesco’s decline present a clear and unambiguous warning that even rich and data-rich loyalty programs and analytics capabilities can’t stave off the competitive advantage of slightly lower prices and a simpler shopping experience. Better insights, loyalty and promotion may not be worthless, but they are demonstrably worth less in this retail environment.
A harsher alternative interpretation is that, despite its depth of data and experience, today’s Tesco simply lacks the innovation and insight chops to craft promotions, campaigns and offers that allow it to even preserve share, let alone grow it. What an indictment of Tesco’s people, processes and customer programs that would be. In less than a decade, the driver and determinant of Tesco’s success has devolved into an analytic albatross. Knowledge goes from power to impotence.
Schrage seems to want to give data driven business practices a blanket indictment. But what if the actual problem wasn’t Tescos inability to innovate or create new promotions? What if the problem wasn’t the fact that Tesco is a data-driven company? What if data-driven marketing isn’t doomed?
Data vs. The Value Of Correct Data Analysis & Execution
Assuming that data really does drive Tesco’s marketing, it is our guess that they made one or both of the following errors.
First, they may have been driven by the wrong data and were working to increase the wrong metrics. Many companies use only the data that supports their current intuition. Bryan Eisenberg explains how Amazon’s four pillars of success revolve around data. If you read it you will learn how Amazon avoids this pitfall.
Second, they may have gotten so buried in data analysis that they lost sight of the simple fact that all that data always tells a story about people. Data simply measure the actions people take based on their feelings, motivations and situations. May I recommend that you check out, on IBM’s SmarterCommerce blog, Bryan’s demonstration of how using Buyer Legends avoids this pitfall this by turning data into story and then story into action.
Does your company use data to support the customer experience or does it use data to support decisions it’s already determined to make?