Audience Data 2.0

The advertising industry has been using audience data in digital media for about a decade.  In that time, we’ve discovered one ultimate truth: first-party data is king.  For instance, retargeting is usually the best digital tactic on direct-response campaigns, while third-party data helps to provide scale but doesn’t perform nearly as well.  And with the proliferation of programmatic media, advertisers have new ways of leverage their first-party data.  Enter audience data 2.0.

Data management platforms (DMPs) are essential to fully harnessing audience data 2.0.  A DMP is a database that can create unique audiences based on particular user paths and engagement with the site.  Using Boolean logic, an audience pool can be built for users that have been to landing page A and C, downloaded a white paper, and come from publisher B.  Advertisers can serve unique creative to these users and bid differently on them based on their propensity to convert or their life time value to the brand.  DMPs can help squeeze out every bit of efficiency from programmatic buys.  



What’s more important is that DMPs establish a foundation for all future data use.  For instance, cross-device mobile targeting is a trend that’s been growing.  Many advertisers are realizing that their own websites provide a wealth of cross device data.  Finding the same users on desktop, tablets, and mobile devices are possible with a DMP.  Hopefully, as programmatic TV evolves, DMPs can also be used to get closer to true audience targeting on TV buys.

Second-party data, or another entity’s first-party data, is another major component of audience data 2.0.  Publishers are making more of their first-party data available to advertisers. Publisher account teams are getting trained on how DMPs work and how they can create unique offerings based on this data.  For instance, advertisers that are unable to place ads on popular section of a publisher site can now use audience data from that section and place ads in front of the same audience across the site. Publishers have been making this data available through private deals, but it wouldn’t be surprising to see audience segments made directly available to advertisers’ DMPs for a fee.

A “data co-op” is another interesting concept, where advertisers can share first-party data with each other.  It may be difficult to find other advertisers willing to share proprietary data, but there are opportunities worth exploring.  Independent business units of the same company may be more willing to share data.  This could reduce ad conflicts among the media buys of each business unit.  There’s also the potential to build on existing relationships with affiliates and re-sellers.  These companies have access to a broader array of transactional first-party data that brands could leverage.  Advertisers should also look to partners that sell complementary products.  For instance, insurance companies could use first-party data from realtors and automobile companies as a proxy for prospective customers.  

Advertisers, their publishers, and their partners should start discussing the possibilities of sharing audience data.  Data privacy policies may also need to be reviewed and reworked to account for second-party data.  It’s important to get in front of this today because it won’t end with audience data 2.0.  The growth of programmatic media will continue to evolve the way we think about and use audience data.

1 comment about "Audience Data 2.0".
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  1. Matt Prohaska from Prohaska Consulting, June 29, 2015 at 6:48 a.m.

    Great post, Brian! In one instance, our team has seen the marketer data co-op work in Europe already among about 10 brands of non-competing verticals with complimentary data, and we're helping data supplier Vendigi provide unique housing data to various buyers (and sellers). Big opportunity here for industry trade groups as well to provide this services for its buyer or seller members. What will be neat, hopefully in data 2.0 & not waiting til 3.0, is if the DMPs & Exchanges can integrate better to allow sellers & buyers to learn more appropriately about each other's audiences pre-PMP for forecasting and for top & bottom funnel better synching. Something I'm sure The Media Kitchen & other top buyers can use more with their publisher partners. Kudos, BN.

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