Commentary
How's Free, Is Free Good Enough For You? New DMP Built On Second-Party Retail/Brand Data
- by Joe Mandese @mp_joemandese, October 29, 2018
A powerful new DMP providing “second-party” data from thousands of retailers and brands revealing the journey of how, what, when, where and why consumers make their purchases online has just rolled out. And best of all, it’s completely free to use.
The data platform, dubbed CoEx, was developed by Boston-based ownerIQ, and it is the culmination of consumer data from more than 2,100 retail and brand customers that use its technology to identify and target consumers in-market to make a purchase.
The ownerIQ team doesn’t call the new platform a “co-op,” because users are not required to share their own data, but their hope is that by making CoEx available for free for other to use, they will ultimately sign up to become customers of ownerIQ’s programmatic media-buying services, enriching the data in the platform even more.
It’s not required that CoEx users utilize ownerIQ’s buying platform. They can integrate CoEx into their own in-house or third-party DSP if they want, but as ownerIQ CEO Jay Habegger notes, data is only as good as it is applied.
“For retailers and brands specifically, there is very little value in data management if they don’t actually apply the data to their current marketing or advertising activity,” he says, adding: “So many clients will make a substantial investment in DMPs before seeing any value. Furthermore, having to work with separate technologies on activating the data slows down their time to market and causes them significant data loss. We are offering a state-of-the-art data management alternative that will reduce their cost and allow them to activate their data faster and at full scale.”
I have long been impressed by ownerIQ’s taxonomy, which is derived from more than 62,000 product and brand types organized into hundreds or thousands of individual addressable segments.
The CoEx DMP enables anyone to access these segments simply and quickly.
For instance, an apparel retailer client can build a segment of “jeans shoppers” by selecting segments of their audience such as: product>pants>“jeans” or brand>”True Religion” or brand>“Calvin Klein.” In addition, they can also add second-party data from ownerIQ’s marketplace to this 1st party segment to build scale.
To illustrate how it works, I asked the ownerIQ team to create a short demonstration video embedded below.
These steps annotate the video:
STEPS IN VIDEO:
1.) Choose a Data Source Apply your 1st party data (My Audience), a branded partner’s audience (My Data Network) and/or entire audience network (Aggregated Data) to your segments |
2.) Choose Behavior Type Select browsing interactions (i.e.- shopping behaviors) or purchase-data from select data sources. |
3.) Choose Interaction Type Decide whether to target all interactions with a specific product type, like Home Appliances, or just interactions with a specific brand. |
4.) Select Product and Brand Types Choose from an easy-to-navigate list of product types or brands within each product category. |
Joe Mandese is the Editor in Chief of MediaPost. You can reach Joe at joe@mediapost.com.
Is the data any good?
Always in the eye of the processor or analyst, but the data tells retailers what brands people are researching, or tells brands what retailers people are visiting as part of their journey. Is that good data?