Highland Math Forms First Data Co-op Of Data Sellers

Data transparency is all the rage in digital advertising, but data companies themselves still exist in a world of black boxes and inscrutable spreadsheets.

Highland Math was founded last year to help address the issue, by creating a consortium of data providers that pool their own returns to create a market research data set. The company works with 37 data providers, up from 18 last summer, said co-founder and CEO Dan Scudder.

It’s an issue Scudder knows well from the marketplace perspective. As LiveRamp’s co-founder and former GM of data, he saw firsthand how data vendors were frustrated and hungry for insights and analytics on platform data performance. Those frustrated LiveRamp partners became the first set of Highland Math customers.

ShareThis builds audience segments from web traffic data and sells it to ad platforms or other data marketplaces like LiveRamp, Oracle and Acxiom. But when ShareThis gets data back from those platforms, it’s devoid of important contextual information, said Andi Wilson, VP of platform partnerships.

ShareThis sees its raw sales total for the month from each platform, but wouldn’t know if it’s growing its share of sales in its category or what kind of data is performing best, she said.

“Solving for the black box of reporting within the data landscape” is becoming a priority. Highland Math, which ShareThis started working with five months ago, is part of that effort.

If data sales on one platform are decreasing, the data provider doesn’t know if that’s because the platform itself is shrinking or if the company is losing share, said Matt Frattaroli, VP of digital platform and agency partnerships for Alliant, an audience data provider.

For example, Alliant had low sales on one platform, and assumed it had a normal market share of a relatively low-selling platform. With Highland Math’s data set, Alliant saw it actually had low share of sales and needed to ramp up on that platform.

The Highland Math data is also a useful tool for forecasting and planning.

Epsilon saw an expected jump in political data sales during the 2018 election. But after joining Highland Math’s data service earlier in the year, Epsilon could see how and where it was being outsold by other political data providers, said product VP Gillian MacPherson. So Epsilon sharpened its political audience segments early in the primary period and increased political outreach.

“Data reporting is pretty archaic,” said Paul Bell, GM of global data solutions for the programmatic technology company 33Across. It’s an honor system where data and sales can’t be audited, he said, though there’s good reason for that since the platforms need to ensure privacy for their partners.

But the result is a 30-60 day lag between sales and reporting that makes it impossible to take advantage of fast-moving trends or respond in time if sales on one platform are slipping.

Data providers also need help creating a taxonomy for data marketplaces. There are no conventions or standards for naming. So, for instance, segments as similar as “auto intenders,” “car intenders” and “in-market for vehicle” must be reconciled manually across platforms.

Smaller or newer data marketplaces also return more data than companies like Oracle or Nielsen, which own data assets too and consider their marketplace data proprietary information.

But for most data companies, the competitive tensions are dwarfed by the missed opportunities due to lack of marketplace data.

“I come from a CPG background, where most retailers contribute data for market share purposes only,” MacPherson said. “I view this as the same kind of data set, and think people who consider it a competitive issue are missing the bigger picture.”

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