DSP-native frequency capping vs identity-graph capping: why your caps leak

DSP-native frequency capping vs identity-graph capping: why your caps leak

Frequency capping limits how many times one user sees your ad. The tool you cap with determines how badly it leaks across devices and environments.

1. DSP-native, cookie-based capping: counts impressions against a cookie. The moment the same person appears on a new device, browser, or cookie-less environment, the counter resets. Your '3 per day' cap silently becomes 9.

2. Identity-graph capping: counts against a persistent person-level ID that stitches devices together. Holds the cap across screens, but only for users the graph can resolve — unresolved users still leak.

3. Channel-level capping (CTV especially): on connected TV there is no cookie at all; you cap against IP or device ID. Households share IPs, so an IP-level cap can over-suppress (capping a whole family as one user) or under-suppress.

4. The tradeoff: tighter identity resolution gives truer caps but covers fewer users; looser methods cover everyone but count wrong.

Why it matters: an advertiser reports 'we cap at 3' while a heavy user sees 15 because each device, each cleared cookie, each app is a fresh counter. Pull impression-per-unique distribution from log-level data, not the average. If the long tail of your impression-per-user curve is fat, your cap is leaking and the fix is the identity layer, not a lower number.