Services / PROGRAMMATIC & AD STACK STRATEGY

PROGRAMMATIC & AD STACK STRATEGY

Most programmatic stacks are not underperforming because a partner is bad. They are underperforming because the stack was assembled one integration at a time, over years, by people who have since left — and nobody has looked at the whole thing at once since.

I take the whole stack apart: every wrapper module, every bidder, every floor rule, every exchange line item, every timeout. Then I put it back together around one question — what does this inventory actually clear at, by ad unit, by device, by geo, by hour?

The output is not a slide deck of best practices. It is a prioritized list of specific configuration changes, each one tied to the revenue it is holding back and the effort it takes to ship.

You are probably here because

  • Traffic is flat or up, programmatic revenue is flat or down
  • Eight SSPs in the wrapper, three of them win anything
  • Floors were set once, eighteen months ago, and never revisited
  • Prebid and Open Bidding are quietly bidding against each other
  • Nobody can say what your actual timeout-to-bid-density curve looks like

HOW THE ENGAGEMENT RUNS

  1. 01

    1. Full stack inventory

    Wrapper config, adUnit definitions, bidder params, identity modules, floor module, GAM line item hierarchy, Open Bidding setup, and every timeout in the chain. Documented as it actually is, not as the last runbook says it is.

  2. 02

    2. Partner-level performance truth

    Bid rate, win rate, timeout rate, and net CPM per bidder per ad unit per device — reconciled against SSP reporting. This is where dead-weight partners surface, and where a bidder that looks mediocre in aggregate turns out to own one specific placement.

  3. 03

    3. Floor and demand modeling

    Your floors get tested against the bid landscape you actually receive, not against a benchmark. Floors set too high suppress bid density; floors set too low leave the entire delta between the first and second price on the table.

  4. 04

    4. Ship, measure, iterate

    Changes go out in a sequence designed so each one is measurable on its own. You get the test plan, the expected effect, and the metric that proves or kills it.

WHAT YOU GET

A documented as-built map of the current stack — the artifact most publishers discover they never had
Partner scorecard with a keep / renegotiate / remove recommendation per SSP, backed by their own numbers
Floor strategy by ad unit, device and geo, with the model behind it
A sequenced change log — what to ship, in what order, and how to tell whether it worked
Working sessions with your engineering and AdOps teams so the changes survive after the engagement ends

Scope covered

  • Full programmatic stack architecture review and optimization (GAM, Prebid, Exchange Bidding)
  • Header bidding wrapper audit — duplicate keys, bid timeout tuning, bidder configuration
  • SSP partner evaluation, onboarding, and performance benchmarking
  • Private Marketplace (PMP) deal structuring and activation
  • Floor price strategy and yield optimization across direct, programmatic, and exchange
  • Competitive exclusion and ad quality enforcement setup

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Think this is your problem?

Scoping conversations are free and specific. Bring your numbers — I will tell you whether there is something here worth engaging on.