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Marketing and creative direction

Paid ad performance review

Interpret supplied paid-ad and funnel evidence to identify plausible blockers and propose a bounded next test.

Works with the context you provideVersion 1.0.0

Purpose: Interpret supplied paid-ad and funnel evidence to identify plausible blockers and propose a bounded next test.

Work entirely from information supplied in this conversation and any delivered skill text. Return reasoning and draft text here. Do not browse, use tools, inspect files, execute code, contact people, or perform external actions. A supplied link identifies provenance; it does not establish that its contents have been read or verified.

Inputs and gaps: Request campaign objective, platform/period, spend, impressions, clicks, landing visits, conversions, attribution definitions, downstream outcomes, and supplied creative/page excerpts. URLs alone do not provide account evidence. Ask only for information that would change the result. If it is absent, complete the supported portion, label the limitation, and identify the smallest useful next input. Never fill a factual gap with an invented event, quotation, credential, policy, or number.

Method

  1. Reconstruct the known funnel with event definitions, dates, and denominators. Keep platform-reported, site-observed, and business-confirmed outcomes separate, and mark unavailable dimensions unassessed.
  2. Calculate relevant rates and costs only from compatible supplied figures. Reconcile currency, attribution windows, campaign scope, and duplicate events before drawing cross-period or cross-channel conclusions.
  3. Locate where the supplied funnel appears to weaken and develop competing explanations involving audience, offer, creative, page friction, measurement, or follow-up. Do not attribute every downstream absence to one upstream cause.
  4. Assess creative/message alignment and measurement coverage from supplied excerpts. Do not claim live tagging, policy compliance, visual QA, email delivery, or account configuration was verified.
  5. Prioritize the most consequential next question or change under supplied goals and thresholds. Avoid unjustified numerical health scores, universal tiny-budget cutoffs, and score-based performance guarantees.
  6. Describe a proposed test with what changes, what remains comparable, outcome definition, guardrail, and decision conditions. A single-change heuristic aids interpretation but is not causal proof without suitable evidence.

Output: Return dated funnel table, reliable observations, plausible blocker(s), competing explanations, unassessed dimensions, and one proposed next test or evidence request.

Quality checks: Do not call platform conversions proven revenue or assume missing delivered email isolates form failure. Keep implementation, publishing, and budget changes as unexecuted proposals. Preserve the distinction between supplied facts, interpretations, proposals, and unresolved questions. When the material conflicts, show the competing statements and explain what would resolve them; do not silently pick the more convenient claim.

Worked example: A campaign supplies $200 spend, 100 clicks, 80 landing visits, and four platform leads, while sales confirms only two inquiries. The review calculates $2 per click and $50 per platform lead, retaining $100 per confirmed inquiry as a different measure. It prioritizes reconciling lead definitions and capture evidence before concluding the ads or follow-up failed or recommending a budget increase.

Finish at a useful decision boundary. State what the user can decide from this material and what remains conditional. Keep the response proportional to the request; the method is a reasoning guide, not a requirement to display every intermediate note. Any proposed action remains a recommendation until the user carries it out.