Location Plus Transaction = Priceless. MasterCard Hooks Up With PlaceIQ For Location-Based Insights

MasterCardPlaceIQMasterCard is partnering with location data company PlaceIQ to help retailers and merchants connect what people buy to where people go.

The relationship, unveiled Wednesday, “paints a much richer picture than location or transaction insights can provide by themselves,” said Shubhra Srivastava, VP of media solutions at MasterCard.

“Location data complements transaction-based insights and provides more context to our advertising partners,” she said.

The MasterCard Audiences data comes from an internal division of MasterCard called MasterCard Advisors that aggregates purchase behavior across the many billions of transactions the company processes every year across different categories like CPG, retail, dining, travel and automotive.

“A proprietary MasterCard methodology identifies audience segments with higher statistical probability to make purchases within the category,” said Srivastava.

The data is anonymized and used to create segments that advertisers buy to help power their digital marketing.

The PlaceIQ piece allows advertisers to match the aggregated segments to device IDs, information they can use to either inform their media strategy by targeting high affinity users or to measure media effectiveness by tracking visitation lift to particular locations.

“We know where the customer goes and MasterCard knows what they buy, and those two things are being fused together,” said Nadya Kohl, EVP of business development at PlaceIQ. Kohl joined PlaceIQ in 2014 after more than a decade in database marketing-focused exec roles at Experian.

“Aside from first-party data, the next most powerful predictor of consumer action is using transactional data to understand preferences, affinities and the baskets people typically buy on a category basis,” she said.

For example, take a specialty high-end eyewear retailer looking to reach consumers with an active interest in fitness and physical activity. It’s a tricky category. A lot of people who look at activewear online or even make activewear purchases aren’t really that into it – it’s just an aspirational state.

“But by fusing transactions with location data, you can tell that someone is actually out there every weekend being active,” Kohl said. “This unlocks an ephemeral condition that’s normally really hard to get at without asking questions on a survey basis. There’s almost no one out there who isn’t going to answer ‘Very’ in response to the question, ‘How active are you?’”

The ultimate goal is to make MasterCard’s insights a little more insightful.

“Instead of reaching high spenders in women’s retailers, advertisers can reach high spenders in women’s retailers that frequent a gym at least two times a week,” said Srivastava. “[And] on the measurement side, the location partners can tell if advertising drove people to a specific location, while MasterCard can close the loop and determine if transactions were made at the location or later through an ecommerce channel.”

It’s really just a matter of riffing on the possibilities.

“The use cases are extensive for joining these kinds of data sets,” Kohl said. “And as people start to test out theories, it’ll become more ubiquitous and accessible.”

And accessibility is key, said Kohl. If data isn’t portable, advertisers will be disinclined to experiment.

Advertisers can access the MasterCard Audience/PlaceIQ combo data set directly or through a number of MasterCard’s or PlaceIQ’s existing distribution partners, including Oracle BlueKai and Adobe.

“The less friction there is, the more handshakes you can take out of the process,” Kohl said. “And the more handshakes you can take out of the process, the easier you make it for marketers to get on with the business of understanding their customers rather than having to manage a hundred different relationships”

The location-infused MasterCard data set is already live with a number of advertisers in the dining, retail, travel and entertainment sectors. Srivastava declined to share names.

1 Comment

  1. Good story showing how the integration of this data provides more context for understanding consumer and then interacting with them more intelligently. But there are other pieces to this puzzle including associating the right content with the shoppers affinities and location context and product intelligence, which is know if the products they are interested in are actually available in the nearest or best location of that shopper.

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