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AI Paid Media Reporting That Never Invents A Number
How performance marketers use AI for paid media reporting without hallucinated metrics: retrieval first, narration second.
Short answer
AI paid media reporting works when structured data is retrieved from the ad platforms first and the model only narrates numbers it was given, never estimates or fills in.
Why paid media reporting is the highest-risk AI use case
One fabricated number in a stakeholder deck can undo months of credibility. Paid media reporting is full of numbers, which is precisely why it is the worst place to let a language model work without structured data in front of it.
Separate retrieval from narration
Build two distinct steps that never merge. Step one pulls spend, impressions, clicks, and conversions from the platform export into a structured file with no model involved. Step two passes that file to the model, which narrates only the numbers it received.
What to automate and what to verify
Automate extraction, anomaly flagging, and plain-English summary generation. Verify by spot-checking three metrics in the AI summary against the raw platform data before the report reaches anyone. Mismatches point at the extraction step, not the summary.
Building a repeatable weekly report
Define the output sections before writing the prompt: spend summary, performance by campaign, anomalies, and recommendations. A fixed structure produces consistent reports, while an open-ended prompt produces a different shape every week.