The CFO test
Pick the success metric for the campaign before you brief the creative or the channel. Then ask the simplest possible question: would your CFO defend this metric in a board meeting next quarter? If the answer is "well, sort of", change the metric. The metrics that pass: contribution margin per acquired customer over a 90 to 180 day window, marginal contribution against a documented holdout, payback period weighted by retention, net revenue retention by acquisition cohort. The metrics that fail: cost per click, click-through rate, engagement rate, share of voice, impressions, anything that ends in "rate" without a denominator the CFO can name. Most perform marketing programmes fail this test on the first quarter and never recover, because the metric becomes load-bearing in the operating model before anyone has tested whether the CFO actually believes it. The r/PerformanceMarketing subreddit has a long-running "metrics that survive the boardroom" thread that is the cleanest practitioner summary of which metrics pass and which do not. Mark Ritson and Les Binet both make the same point at length in the Marketing Week and IPA publications.
The agent in the loop
A perform marketing programme in 2026 has at least one specialised AI agent in the loop. The four most common entry points: variant generation against a brand guardrail rubric (the agent produces 200 ad variants, the human reviews 20), send-time decisioning per profile (the agent picks the optimal send time inside a defined window), audience design from warehouse data (the agent proposes look-alike or rule-based segments and tests them against a holdout), post-campaign analysis with hypothesis generation (the agent reads the campaign performance data and produces three falsifiable hypotheses for the next iteration). The agent does the iteration; the human keeps the taste, the brand judgement, and the kill decision. We ship these in two weeks at clients. The Anthropic Building with Claude documentation and the OpenAI Agents SDK both publish patterns for agentic loops that are the cleanest practical references; r/MachineLearning has the practitioner debates on what works and what does not. The Yao et al. ReAct paper (2022) is still the cleanest theoretical reference for the reasoning-action loop the agent runs.
The kill list
Any perform marketing operation that does not kill at least one campaign a quarter is not really running on outcomes; it is running on consensus, which is what teams do when nobody is accountable for the result. The kill list (what we shut down, why we shut it down, what we tried next, what we learned) is the most under-published artefact in performance marketing. Publishing it internally changes the culture because it normalises the act of killing something, which is the only way the team stops sandbagging the metric to keep their work alive. Publishing it externally (which we do in our quarterly notes, and which a handful of in-house teams at Patagonia and Monzo do in their public communications) changes the conversation with buyers because it signals honest measurement. Most CMOs we work with have never seen a kill list before kickoff; by the end of the first year, every team we coach is keeping one. The discipline is not optional once you have run on outcomes for a quarter.
How to wire the operating model in 90 days
Week 1: write the success metric for one campaign and get the CFO (or the equivalent senior finance partner) to nod in writing. Weeks 2 and 3: ship one AI agent into the loop on that campaign. Variant generation is usually the cheapest first step because the brand guardrail rubric is something the team already implicitly holds and can write down in an afternoon. Weeks 4 to 12: run the campaign, eval the agent output against the rubric, kill weak variants weekly, publish a postmortem at the end of the quarter that includes the kill list. By the end of week 12 you have a working perform marketing operation on one campaign with a documented operating model, a published metric, an agent in the loop, an eval harness, and a kill list. Expand from there to the second campaign, the second channel, the second agent. The 90-day pattern is the minimum viable operating model; anything shorter skips a step you will rediscover later at higher cost.
What perform marketing is not
It is not "we run ads on every channel because that is what perform marketing means". It is not "we track impressions and clicks because those are the numbers the platforms surface by default". It is not "we measure brand awareness only because brand is what we believe in". It is not even "we measure ROAS" because ROAS without a holdout is a vanity number that mixes incremental and inframarginal returns. A perform marketing operation pairs a clear outcome metric (CFO-defensible), a measurable activation (with a holdout), and a kill discipline (with a published kill list). Anything missing one of those three is something else. The Bob Hoffman columns and the Ehrenberg-Bass How Brands Grow body of work both define the boundaries from different angles; both are worth reading before the next quarterly planning session.
Further reading
Real, named sources the editor can swap in for specific URLs. We do not auto-link these because the right link changes over time. If you find a great primary source, write us and we will update the note.
- r/PerformanceMarketing, r/digital_marketing. Working threads on metric design, attribution honesty, and kill-list discipline.
- Anthropic's Building with Claude documentation. Eval-first agent design patterns. The practical reference for wiring an agent into a marketing loop.
- r/MachineLearning. Practitioner debates on agent design, variant-generation systems, and post-campaign analysis loops.
- Ehrenberg-Bass Institute on brand-vs-activation. The reference text for what perform marketing should and should not optimize for.
- Mark Ritson columns (Marketing Week). The most-quoted modern critic of impression-counting cosplay. Worth subscribing if you're scoping perform marketing.
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