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Measurement / Practitioner report

Diagnose ad performance before changing spend

Build a hypothesis-driven review from enough data to support a decision.

Approved AI assistantIntermediateOriginal editorial guide

What you’ll produce

A diagnostic memo with observations, possible explanations, and a limited test proposal.

Inputs & connections

  • Approved campaign and conversion exports
  • Unit economics, attribution window, and test constraints

Begin with approved exports or pasted source material. Live access requires separately configured integrations and permissions; this guide does not install them.

Your starting prompt

Replace the bracketed fields. This is our suggested prompt, not a quote from the source.

Review [ad performance data] for [period] against [business objective]. Separate observed changes from hypotheses. Consider spend, volume, conversion quality, attribution delay, and sample size. List missing evidence before recommending a test. Define one bounded experiment with a control, budget limit, stop condition, and review date. Do not modify campaigns or promise a cost reduction.

How to run it

  1. 01

    Check tracking health and the definition of a valuable conversion.

  2. 02

    Prepare comparable time windows and record external changes.

  3. 03

    Generate competing explanations and choose what can be tested.

  4. 04

    Approve a bounded experiment and review its full business result.

KEEP A PERSON IN THE LOOP

Review before you act

The media owner validates attribution, sample size, spend limits, and conversion quality.

Limitations & success checks

  • A lower cost per lead can accompany lower lead quality.
  • One creator’s account-level result is not a general prediction.

Measure: Qualified conversion cost and incremental evidence from approved tests.

Sources & attribution

The sources below support the reported example or a tool capability. They do not validate our prompt or prove the outcome in your environment.

Practitioner reportFacebook ads agent example ↗

May 15, 2026. Reports an advertising-agent experiment. Performance claims describe one account and have not been independently reproduced.

Creator / publisher: Cody Schneider

Editorial review: October 11, 2026. How we label evidence.

FROM A USE CASE TO A WORKING SYSTEM

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