Commerce Signals, a Verisk Financial company that uses U.S. payment-card data to help marketers target ads to consumers, has begun rolling out transaction-based audiences through the LiveRamp Data Marketplace.
Audiences -- available today -- supports about 40 million datasets focused on purchase card data analytics and buyer segments.
Commerce Signals is not the first company to launch transaction-based audiences, but it claims to have the largest reach into 162 million households.
“It lets marketers target consumer based on actual highly-likely purchases,” said Nick Mangiapane, Commerce Signals CMO, adding that the artificial intelligence (AI) models used are 90% accurate.
Marketers can find the segments in the LiveRamp data marketplace. The segments are available by merchant or category, such as “heavy shoppers in grocery” or “heavy shoppers at Target.”
Marketers can buy the audiences and integrate each into programmatic and direct advertising campaigns across a range of online, mobile and addressable television networks.
The company’s patented technology platform leverages permissioned, anonymized transactional data from banks and processors, with the ability to continuously analyze shopper behavior across virtually all retail and direct-to-consumer business categories, down to specific retailers by zip code or store location.
Mangiapane said the company takes a feed file and tests it against 40 million households to determine accuracy. “We can’t say, ‘Oh, Kevin bought pizza from Papa John’s last week, so I’m going to target him,’ for privacy reasons,” he said.
The company can take a small feed file, find small cohorts of people, and build a model to target individuals like Kevin in the example given by Mangiapane.
“We remove Kevin from the feed file, because we used his purchases to build the model,” Mangiapane said. “It helps drive return on investment.”
All the data is anonymous. There are persistent IDs in the data, but no personal identifiable information is tied to the model.
Commerce Signals also builds audiences with anonymized consumer data, joining each credit or debit card a consumer might use.