Where should buyers challenge advice across this playlist?

Is the proposed metric suitable for the decision?

Ask for methodological disclosure before debating which dashboard looks best. The IAB’s August 2026 measurement framework distinguishes directional measurement from evidence suitable for decisions and addresses stability, reproducibility and provider disclosure. Use it as a companion to the media selections, not as proof that a particular vendor meets those expectations. (iab.com)

Our proposed supplier checklist is:

• What exact prompts, engines, interfaces and geographic settings were used?
• How were customer-derived questions separated from inferred prompts?
• What was repeated, and how sensitive was the conclusion to rewording?
• Can we inspect saved answers, source URLs and scoring decisions?
• Were failed collections recorded separately from genuine brand absence?
• Did the comparison change its prompt set, model or collection method?
• Which finding would change the recommended expenditure?

Does technical eligibility really imply selection?

No: keep access checks separate from outcome claims. Google’s documentation says meeting its requirements does not guarantee crawling, indexing or serving. OpenAI’s crawler documentation separately identifies search crawling and model-training crawling; allowing one does not require allowing the other. These are concrete technical distinctions to check before accepting a vague proposal to “make the site AI-ready”. (developers.google.com)

Does external authority-building justify manufactured endorsements?

No. Treat review and endorsement tactics as a compliance question, not an optimisation loophole. The FTC’s consumer-review guidance addresses fake or false reviews and testimonials, including relevant AI-generated material. Ask for legal review where a proposed campaign involves paid endorsements, incentivised reviews or apparently independent coverage controlled by the business. (ftc.gov)