Role of user data in a DSP Platform - Part I

Key benefit of any good Demand Side Platform (DSP) is to buy media programmatically and efficiently based on its algorithm’s ability to understand data and other business criteria. The most important aspect of the DSP is to utilize user data to accurately predict the value of a user for a given impression.

Hence for any DSP platform it is of paramount importance to invest in their bidding and predictive logic to win impressions that are most valuable for their customers and help deliver the end business goals. It’s much more than clicks and conversions that we are talking about here. A good DSP has to give much more weightage to the audiences from which those clicks and conversions are coming from because it is this audience and their positive mind share, which the advertisers and brands are really after.

So it all begins with a data strategy. How much audience data do we have in our region, total number of unique users, total number of segments to which these user belongs, audience profile of the users, trends and audiences that really convert for a given campaign, uplift seen in a campaign due to audience data etc.

Those days are long gone when marketers used to run after premium inventory and totally ignore remnant inventory. With DSPs becoming mainstream, agencies and ad networks have now started leveraging user data to make every impression coming even from remnant inventory almost as valuable as an impression coming from a premium inventory. Hence with user data the gap between value of impression coming from a premium inventory versus remnant inventory has drastically reduced. And, in time people will stop differentiating between impressions based on inventory source but will start valuing impressions based on audiences.

In my next post I'll share some practical insights around behavior targeting and retargeting optimizations in a DSP platform.