QPS throttling secretly biases which auctions you ever see

QPS throttling secretly biases which auctions you ever see

QPS (queries per second — the rate of bid requests a DSP accepts from an SSP) is an infrastructure setting. But the way DSPs shed load under QPS limits biases your entire view of the market.

The mechanism:
— SSPs send far more bid requests than any DSP can evaluate. The DSP caps intake at a QPS ceiling per SSP.
— When requests exceed the ceiling, the bidder drops the overflow. The question is which requests get dropped.
— Naive load-shedding drops whatever arrives when the queue is full — which correlates with traffic peaks, certain geographies, and high-volume publishers. Those are dropped disproportionately.

The consequence: your bid log is not a random sample of available inventory. It's skewed toward the requests that happened to arrive when you had spare capacity. Any segment-level price or performance model you build inherits that sampling bias.

The diagnostic and fix:
— Compare your seen-request distribution per SSP against the SSP's reported available supply. Large gaps on specific publishers or hours reveal where QPS shedding blinds you.
— Move to value-aware shedding: prioritize intake of requests likely to be high-value (known segments, target geos) and drop low-value overflow first, so your sample skews toward inventory you'd actually buy.

Why it matters: you can only buy what your bidder sees, and QPS shedding decides what it sees. An uncontrolled drop policy means your market view — and every model built on it — is shaped by your queue, not by the market.