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Incrementality test you can actually run and actually read

Leadership wants proof the channel drives incremental revenue. Design the holdout your budget, timeline, and traffic can genuinely support.

The prompt — copy and run it

You are an experimentation designer scoping an incrementality test. I will paste the channel context and constraints. Produce:

A) THE DESIGN: the test type suited to my constraints (geo split, audience holdout, or on/off flighting), the treatment and control definitions, the duration, and the budget it consumes — with the reasoning for each choice tied to my numbers.
B) THE READABILITY CHECK: given my baseline volume and variability, the smallest effect this test could detect, and the verdict — RUNNABLE, RUNNABLE ONLY IF (state the change to duration, budget, or scope), or NOT RUNNABLE AT THIS VOLUME. Show the arithmetic. Never call a test readable to be encouraging.
C) THE PRE-REGISTRATION: the exact metric, the decision rule written before launch, the contamination risks specific to my setup, and the action we commit to for every possible result — including the result where nothing is detectable.

My context: [PASTE: channel, current spend and conversions, period-to-period baseline variability, geography or audience structure, budget available for the test, timeline, measurement stack]

Rules: Do not invent, estimate, or fabricate any statistic, benchmark, or performance figure — if a number is not in the material I give you, write "not provided" and flag it. Mark every claim I should verify in my analytics or source systems before it is published or presented. Never include customer personally identifiable information or client-confidential terms.

How to use this prompt

  1. Copy the full prompt above with the Copy button.
  2. Add your context. This prompt runs as-is — paste it, then add the specific details, data, or files it should reason over.
  3. Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.

Why this prompt works

Most incrementality tests run at volumes that could never have detected the effect being argued about, and the flat result then gets read as proof of nothing rather than proof the test was too small. Putting the minimum detectable effect BEFORE launch, and pre-registering the decision rule, is what makes the result binding instead of renegotiated after the fact by whoever dislikes it.

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Reality guardrail: this prompt makes the model reason from data you paste — it does not source or verify facts for you. Check every claim, keep confidential data out of consumer AI tools, and follow your employer's AI-use policy.

Frequently asked

When should I use this prompt?

Leadership wants proof the channel drives incremental revenue. Design the holdout your budget, timeline, and traffic can genuinely support.

Why does this prompt work?

Most incrementality tests run at volumes that could never have detected the effect being argued about, and the flat result then gets read as proof of nothing rather than proof the test was too small. Putting the minimum detectable effect BEFORE launch, and pre-registering the decision rule, is what makes the result binding instead of renegotiated after the fact by whoever dislikes it.

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.