<b>Bid shading is a feedback loop, not a discount</b>

<b>Bid shading is a feedback loop, not a discount</b>

When the industry moved to first-price auctions (you pay exactly what you bid, not the runner-up's price), DSPs introduced bid shading: the DSP lowering your bid toward the expected clearing price so you don't massively overpay.

1. The shading model predicts a clearing price from recent win/loss data for similar inventory.
2. It submits a shaded bid below your stated value.
3. The outcome (win or loss, and at what price) feeds back into the model.

Here is the part most buyers miss. The model trains on <i>its own shaded bids</i>. If it shades too aggressively and loses, it never observes the true clearing price for that auction — it only sees a loss. That censored data biases the model toward thinking inventory clears lower than it does, which encourages more shading, which produces more losses on contested impressions.

The correction is exploration: a small fraction of bids submitted unshaded or lightly shaded specifically to observe real clearing prices and recalibrate. Vendors who skip exploration get a model that drifts confidently in the wrong direction.

<b>Why it matters:</b> when your win rate quietly erodes on premium supply but your CPMs look great, suspect a shading model that has stopped exploring. Ask your DSP what percentage of traffic it reserves for price discovery.