The promise of retail data has long been to connect an advertising dollar to a customer’s purchase. But what happens when sales drop unexpectedly? The data can often show what happened and who was involved, but the crucial context of why it happened frequently remains a mystery.
A richer understanding is emerging from the practice of layering different data sets – connecting a brand’s customer list with a retailer’s, or linking in-store foot traffic to media consumption.
For one fast-food brand, this approach uncovered that a sales dip coincided with external pressures on its core Latino audience, an insight that reshaped its outreach strategy, said Sam Bloom, head of partnerships, PMG, in this video interview with Beet.TV.
Unlocking the ‘why’ beyond the sale
The most significant opportunity in using retail insights is not just confirming a purchase, but decoding the motivations behind consumer choices, or the lack thereof, Bloom said.
“The biggest unlock we see in applying data beyond the point of sale is understanding the whys of which consumers are or are not consuming our client’s products and services,” Bloom said. He pointed to a quick-service restaurant client that had experienced several consecutive weeks of poor sales.
“One of the insights that we got was that the audiences were primarily Latino,” he explained. “When you see macro things like some of the immigration and some of the other things going on, we see real impacts at the bottom line. The next question is, what can we do to support those audiences, to connect with those audiences in ways to drive them back to the franchise?”
Fusing physical and digital signals
Achieving such deep insights requires two key data collaborations, according to Bloom.
- The first involves securely merging a client’s own customer data with a retailer’s, creating a more complete view of the shopper journey in a privacy-compliant manner. “We’re now able to connect client’s first-party data with the retailer’s first-party data and collaborate in an anonymized and privacy-friendly way,” Bloom said, enabling analysis of “transactions, life changes, all those kinds of good things.”
- The second method connects shopper behavior in physical locations with their media consumption habits, bridging the long-standing gap between the two worlds.
That capability is central to the growth of the U.S. retail media market, which eMarketer forecasts will exceed $62 billion in 2025. “We’re able to look at those behaviors prior to transactions, post-transactions, to try to decipher patterns so that we can start to build learnings to be able to effectively communicate on an ongoing basis with consumers,” he added.
Context as a proxy in a privacy-first world
As third-party signals disappear, advertisers are being forced to find new ways to achieve precision. For PMG, the industry’s privacy shift has put a renewed emphasis on the power of context as a reliable proxy for audience intent.
“The probably the biggest unlock for us has been around contextual,” Bloom said. “What we’re seeing… is there’s sort of two big findings:
- ”One is in some cases, we can find those environments that have high contextual relevance and they’re outperforming.
- ”But there’s an inverse of that too, we also see some environments that have very negative correlations to outcomes. So we can eliminate those environments.”
The future of retail data, Bloom concluded, involves understanding the full context of a consumer’s life, from “life stages, seasonality, need states” to “drive times” and “consumer occasions.”
You’re watching “Using Precision Data to Build Brands”, a Beet.TV leadership series presented by Kroger Precision Marketing. For more videos from this series, please visit this page.
