Just for conversions? Why marketers may be missing the bigger picture on retail data.

Retail data is quickly becoming a key component in many advertisers’ strategies, with uses ranging from targeting shoppers on retailers’ sites to finding audiences in fast-growing open internet channels like connected TV, streaming audio and more.

Google Chrome’s third-party cookie deprecation is likely drawing interest, but many marketers who see retail data simply as a cookie replacement that can bring conversions may be missing out on its full capabilities.

Advertising industry leaders tell The Current that retail data doesn’t just equip marketers with privacy-conscious first-party transactional data. It can also address some of the perceived shortfalls of deterministic data, such as scale, while augmenting the accuracy of probabilistic data when used as a seed.

“With the cookieless era nearing, advertisers are now feeling the pressure to look for alternative targeting solutions,” Damien Lemaitre, global commerce director of media at dentsu, tells The Current. “The deterministic data segments they relied on need to be replaced with future-proof strategies.”

In short, retail data can serve double duty for marketers in a world where privacy-conscious third-party data signals are becoming scarcer and under greater regulatory scrutiny.

“Retail media is one of the last gold reserves available for true deterministic data. We can plug that in and make that available in all the different systems we buy. It’s a gold mine, and I don’t think enough brands are thinking about it,” Chris Twining, global innovation director at iProspect, told Campaign and The Trade Desk last year.

How retail data can improve deterministic data

But first, what are deterministic and probabilistic data?

The former allows advertisers to identify consumers through data they’ve provided (like email addresses when logging in to websites) — for example, by matching it to publisher inventory. Probabilistic data is usually derived from multiple data points, which are put together to approximate consumers’ identities.

While deterministic data sounds like the obvious choice for marketers who don’t want to waste media spend on irrelevant audiences, probabilistic data can help advertisers reach new customers by surfacing those who may be similar to the ones a brand is interested in, for example.

Both are necessary in a marketer’s toolkit, but both can come with potential issues, like scale for deterministic data and accuracy for its probabilistic sibling.

Retail data, meanwhile, can solve for both scale and accuracy in a privacy-conscious way, thanks to retailers possessing enormous quantities of data points through transactions and loyalty programs. That data is also often verified and linked to logged-in shoppers’ email addresses or other contact information.

“The utilization of retail data significantly enhances marketers’ comprehension of consumers and their distinctive purchasing behaviors,” Kyle Cook, EVP of media strategy at Universal Media, tells The Current. “This advancement not only facilitates the construction of more refined audience segments but also the development of highly effective campaigns that cater to varied buying patterns.”

Case in point: Coca-Cola, which leaned on Singaporean retailer FairPrice’s retail data in a Lunar New Year campaign. The beverage giant targeted customers who had purchased the company’s products over the past one to three months and saw a 189% uplift in sales, as well as an average conversion time of 12 hours from initial ad exposure to making a purchase.

Using retail data to seed probabilistic audiences

In addition to using retail data in a deterministic way, for example by targeting “vegetarian frozen-meals buyers in the last week,” advertisers can also use it to create high-fidelity probabilistic audiences that are based on the accuracy of shopping data, rather than loosely defined signals that make up cohorts such as “health-conscious shoppers.”

“Retail data can further add to probabilistic audience targeting as an insights generation mechanic, which can be used to steer the curation of probabilistic audiences,” says Ian Black, head of retail media at Publicis Commerce. “These insights often take the form of purchase timings and cycles, adjacent products bought, audience demographics and geographies.

“This data can be effectively harnessed by advertisers to create probabilistic audience segments that are rooted in transaction-based insights,” adds Black.

That could open up more targeting opportunities for brands, extending retail data’s usefulness beyond conversions. “Purchase data will be utilized to create unique audience cohorts and replace many of the existing legacy data segments used by brands for upper-funnel campaigns,” Daniel Folkman, SVP of business at Gopuff, tells The Current.

Indeed, some are already applying the precision of retail data to the audience-expansion capabilities afforded by alternative identity solutions like Unified ID 2.0 (UID2), RampID and ID5.

For example, Universal Media worked with a grocer to improve their lookalike audience strategies by using UID2. Cook says that comparative studies demonstrated the superior accuracy of UID2 in pinpointing genuine consumers, resulting in a 78% increase in audience size and a 17% decrease in cost per mille — as well as a 22% improvement in conversion rates.

“Brands looking to expand audiences should turn to leveraging UID2 for assured audience growth, which showcases the seamless integration of retail and audience data,” says Cook. “By leveraging cookieless IDs, advertisers can craft strategies that are both data-driven and privacy-conscious, enhancing the accuracy and scalability of their efforts.”

The Current is owned and operated by The Trade Desk, Inc.