First-party data and in-store media: how they connect

What does your first-party data have to do with a screen in a corner store? More than you might expect, and in a different way than in online advertising. First-party data is information a company collects directly from its own customers and operations: its own sales, its shipments, its website visits, its customer service records. For in-store media, it's most useful for planning and measurement at the store and market level, not for matching individuals.

That distinction keeps the connection both practical and privacy-conscious.

What counts as first-party data for a brand?

For a CPG brand, first-party data often includes shipment data to distributors, sales records by market, promotional history, and customer contacts from programs the brand runs directly, such as email sign-ups or rebate offers.

For a retailer or network, first-party data includes its own sales and operational records.

The quality of first-party data varies. Shipment data may be timely and detailed, while market-level sales estimates may be rougher. Knowing the strengths and gaps of each source helps decide how much weight to give it in planning.

Each party's first-party data belongs to that party, and using it comes with obligations: to the people it describes, and under applicable law. The FTC's privacy and security guidance is a useful starting point, and rules vary by state.

How can first-party data guide an in-store plan?

At the market level. A brand's own sales and shipment data shows where its products are distributed and where they sell well or poorly. That's valuable for deciding where in-store media should run. NRS Digital Media campaigns can be activated by geography down to the zip code, so a brand can align media with the markets its own data highlights. The store locations page shows where the network operates.

At the product level. A brand knows which items it wants to grow, which are launching and which have distribution gaps. SKU-level activation lets a campaign focus on those items in stores that carry them.

At the timing level. A brand's promotional calendar and seasonal history indicate when a campaign is most useful.

None of this requires matching individual shoppers. It uses the brand's own knowledge of its business to decide where, what and when.

What shouldn't you expect?

Individual matching. In-store screens reach shoppers in a shared physical space. NRS data is aggregated at the store, UPC and transaction level, which describes what sold without tracking individual shoppers. A brand shouldn't expect to connect its customer list to specific people who saw an in-store ad.

Personalized targeting. A counter screen shows the same ad to everyone at the counter. Relevance comes from choosing the right stores, products and moments, not from personalizing to an individual.

That's a design feature. It avoids many of the privacy concerns that come with individual-level targeting. What you can expect is clear information about where, when and in which stores a campaign ran, along with store-level results measured against comparison stores.

How does first-party data help measurement?

By providing context. A brand's shipment data can show whether distribution changed in the campaign period, which affects how results are read. Its promotion calendar shows whether a deal was running at the same time.

By supporting comparisons. A brand's own market-level sales can confirm or question what store-level results show. If advertised markets look stronger in both sources, that's more convincing.

And by tracking non-store actions. For campaigns aimed at sign-ups or website visits, a brand's own analytics, measured by market, can be compared between targeted and untargeted areas. To discuss how your data could inform a plan, contact the NRS Digital Media team, or visit the NRS Digital Media site.