<b>Stop optimizing to average CPM; model the clearing price distribution</b>

<b>Stop optimizing to average CPM; model the clearing price distribution</b>

Average CPM is a single number standing in for a distribution, and that abstraction hides the levers that actually move your win rate. The richer object is the clearing-price distribution: for a given segment, the full curve of what it took to win.

1. Pull every auction you bid on for one segment and record the minimum winning price where known (from win notices and loss reasons in log-level data).
2. Plot the distribution. You will usually see it is right-skewed — most impressions clear cheaply, a long tail clears expensive.
3. Your win rate is just the fraction of that curve sitting below your bid. Raising your bid sweeps you further up the curve, but with diminishing returns once you've cleared the dense low part.

This reframes bidding from 'pick a CPM' to 'pick a percentile.' Bidding to the 60th percentile of the clearing distribution might win 60% of available impressions; chasing the 90th costs far more per incremental win because the tail is expensive and sparse.

<b>Why it matters:</b> the distribution tells you where the cheap, winnable volume sits and where you're about to overpay for scarcity. Two segments with identical average CPMs can have completely different efficient bid points once you look at the shape.