Solving the Remnant Inventory Problem
By Ben Barokas
As an industry, it’s taken us more than 15 years to get a grip on dealing with remnant ad inventory, but I think there’s finally a light at the end of the tunnel. Over the past two or three years in particular, the R&D that’s gone toward solving this problem has begun to drive substantive results for publishers, boosting eCPMs and easing the burden on their perpetually overworked ad ops teams. We’ve moved far beyond the static daisy chain into real time optimization, but how does it all work, and what are we doing to stay ahead of the problem?
At its core, optimization is about “peeling off the layers” to reveal a clearer picture of what every impression is worth. Doing this at scale means accounting for a laundry list of ever-shifting variables (discrepancy, frequency, fill, user, content, geo) across countless sources of ad demand—and the problem isn’t getting any easier. The good news is, we’re on the cusp of another phase of innovation. Between Real Time Bidding (RTB) and a host of data infusion techniques, premium publishers in particular are poised to reap gains proportionate to the high quality of their content and audiences.