The opportunity
A falling ROAS can be caused by many different events: higher auction costs, creative fatigue, audience saturation, broken landing pages, product availability, pricing changes, tracking loss, or normal volatility. Changing budgets before separating those explanations can make the problem harder to diagnose.
BizSidekick establishes a stable comparison period, follows the change through the funnel, and ranks causes by the strength of their evidence. The output distinguishes confirmed observations from hypotheses that still need a test.
How it works
- Define the abnormal movement — Choose the metric, affected campaigns, observation period, and stable comparison baseline.
- Inspect advertising delivery — Compare spend, CPM, reach, frequency, CTR, CPC, conversion rate, and campaign configuration changes.
- Inspect creative and audience evidence — Check asset-level fatigue, placement mix, audience overlap, and recent targeting changes.
- Follow traffic into commerce — Compare landing-page behavior, product availability, checkout performance, orders, refunds, and net sales.
- Separate measurement changes — Identify pixel, consent, attribution-window, UTM, or synchronization changes that may affect reported results.
- Rank and validate causes — Score each explanation by impact and evidence, then provide the smallest test needed to confirm or reject it.
Safety boundary
When the baseline or a critical data source is missing, the result remains a hypothesis list. BizSidekick does not label correlation as causation or recommend a material campaign change without comparable evidence.
Expected outcome
A ranked root-cause brief with supporting evidence and a validation plan
Try this prompt
Paste it into Claude to start this use case.
@BizSidekick Diagnose why paid media performance dropped this week. Compare campaign delivery, creative, audience, landing-page, and Shopify sales evidence with a stable baseline, then rank the likely causes and propose validation steps.
