Are You Running Too Many Incrementality Tests?

Prioritize tests where uncertainty has real financial consequences, then use the results to guide decisions long after the test ends.

What Happened

MarTech published a piece by consultant Tom Leonard on August 24, 2026, arguing that incrementality testing is having a moment but most marketing teams are misusing it. Leonard introduced a framework called IDEATE (Insight, Draft Hypothesis, Envision Paths, Arrange the Test, Track Results, Execute on Findings) and made the case that testing capacity is finite, so it should be spent only on questions where the answer changes a spending decision.

Why This Matters for B2B Marketing Leaders in HR Tech and FinTech

You are under pressure to prove marketing efficiency, and incrementality testing has become the fashionable answer to platform attribution inflation. But B2B programs in HR Tech and FinTech run on longer sales cycles, smaller audience pools, and fewer conversion events than DTC. That makes indiscriminate testing expensive and often statistically weak. Leonard's point applies with extra force to your team: if a channel is already corroborated by MMM, pipeline data, and sales response, another test is waste. If Meta ASC or LinkedIn spend keeps scaling while your blended CAC drifts up, that is where uncertainty carries real financial consequences and deserves your limited testing slots.

The Starr Conspiracy's Take

The smartest B2B marketing teams we work with already know that measurement is a portfolio decision, not a checklist. Leonard's Envision Paths step is the one most B2B teams skip, and it is exactly where bias creeps in. You should write down what you will do at each possible result before the test runs, because a test only creates value if you act on it. This is the same discipline we apply when mapping demand states across the AI-influenced buyer journey: decide the response before the signal arrives, or you will rationalize your way back to the status quo.

What to Watch Next

Expect incrementality partners to consolidate through 2027 as buyers demand tighter integration with MMM and pipeline attribution. Watch whether platforms like Meta and LinkedIn respond with their own conversion lift APIs, and whether your finance partners start asking for pre-committed decision rules before approving test budgets.

Related Questions

How is incrementality testing different from MMM for B2B marketers?

MMM models historical spend against outcomes across channels and works best for strategic budget allocation. Incrementality testing isolates the causal contribution of a single tactic in a controlled window. You use MMM for portfolio decisions and incrementality for tactical questions MMM cannot answer.

When should HR Tech marketers skip an incrementality test?

Skip the test when MMM, observational analysis, and sales feedback already agree, or when the result would not change your spend decision. Testing capacity is scarce, so reserve it for questions where a clear answer would move real dollars. Our B2B marketing measurement guidance covers how to prioritize.

What is the biggest mistake teams make with incrementality tests?

Interpreting results after the fact instead of pre-committing to actions. Teams that wait until the readout to decide what a result means almost always rationalize toward protecting existing spend, especially when agencies or platform reps are in the room defending the channel.