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Whitelisting & Blacklisting

Also known as: Whitelist, Blacklist, Allowlist / Blocklist

What is Whitelisting & Blacklisting?

Whitelisting and blacklisting are the practice of restricting a campaign to only proven-good traffic sources (the whitelist) or explicitly blocking known-bad ones (the blacklist). They are the core levers for controlling traffic quality on programmatic and native buys.

Key takeaways
  • A whitelist restricts a campaign to proven-good placements; a blacklist blocks known-bad ones
  • On open networks a few placements carry the campaign while most lose money
  • These lists are the core quality-control levers on programmatic and native buys
  • Building them well turns a break-even buy into a profitable, low-fraud one
  • Whitelisting too early on thin data locks out placements that had no fair chance

How it works

On open native and programmatic networks, a single campaign is served across thousands of publisher placements of wildly varying quality. A partner starts broad to gather conversion data, letting each placement accumulate enough clicks and FTDs to judge it fairly. Placements that produce clicks but no conversions, or that trip fraud signals, are added to the blacklist so the campaign stops buying them.

As the data matures, the partner inverts the approach: they identify the small set of placements that drove almost all the profitable conversions and build a whitelist, restricting spend to only those sources. This concentrates budget on winners and sharply cuts cost per acquisition. Because the broker pays only for genuine, low-fraud conversions, a disciplined whitelist also keeps the partner's traffic clean enough that the broker keeps the deal alive.

  1. Launch broad

    Run across the full inventory to collect performance data per placement.

  2. Gather per-placement data

    Track clicks, conversions and fraud signals down to the individual site or source ID.

  3. Blacklist the losers

    Block placements that produce clicks but no FTDs, or that show fraud patterns.

  4. Identify the winners

    Isolate the placements that drove the bulk of profitable conversions.

  5. Build the whitelist

    Restrict spend to the proven placements once the data is statistically meaningful.

  6. Review and refresh

    Periodically re-test blacklisted sources and prune whitelist decay.

Why it matters for partnership: On open networks, most placements lose money and a few carry the campaign. Building a whitelist of profitable placements and blacklisting fraudulent or non-converting ones is how a partner turns a break-even buy into a profitable, low-fraud one the broker will keep paying for.

Real World Example

After two weeks on a native network, an affiliate blacklists 60 low-quality sites that produced clicks but no FTDs, and whitelists the 12 sites that drove all the conversions, cutting cost per acquisition sharply.

Whitelist vs Blacklist
Aspect Whitelist Blacklist
Logic Allow only these sources Block these sources
Default state Everything else is excluded Everything else is allowed
Best when Winners are known and few Bad sources are known, exploring the rest

Pro Tip

Start broad to gather data, then aggressively blacklist non-converting placements and rebuild spend around a tight whitelist.

Common Pitfalls

Whitelisting too early on thin data and locking out placements that had not yet had a fair chance to convert.

FAQ

When should I move to a whitelist?

Once you have enough conversion data per placement to distinguish real performers from noise, usually after a deliberate testing phase.