Your CMO doesn’t have time to debug Meta.
The AI does.

Every Monday the AI Marketing Operator reads your last 7 days of pipeline data, opens its own insights, and writes 3-5 prioritized actions per merchant. Each action gets a rationale that cites specific events, an expected revenue lift, and the evidence backing it.

You open the dashboard. Three platforms green, two yellow, one red. Twelve insights open. EMQ trending down on Meta but you can't tell if it's a real regression or weekend noise. Forty minutes later you've decided to look at it tomorrow.

"Should we push the new bundle SKU to Pinterest?" You don't know. The Boosted Events experiment is still running. Match-quality on Pinterest is unverified. You promise an answer Friday. Friday comes. The campaign goes out untested.

The performance team writes the same plan they wrote last week. Pause the losers, scale the winners, run a new test. Nobody can point at the specific event-level data that justifies any of it. The plan is ritual, not analysis.

An operator-grade weekly report. Not a dashboard. Not a Slack alert. A short list of specific actions that hit revenue, with rationale, evidence, and expected impact. The kind a senior performance hire would write — before you'd had your second coffee.

Meta delivery dropped from 96.4% to 91.2% Tuesday. Auth token rejected on 18% of audience syncs. fbp cookie missing on 31% of checkout events post-cart-redesign. Insight INS-2641 open since 2026-04-22.

Boosted predicted_purchase A/B finished with +11.4% conversion lift (p=0.03, n=782). Shipping the same event to TikTok and Pinterest will likely repeat. Both connectors are healthy.

Audience high-LTV-repeat (4,128 users) has 100% match-rate to Meta. Lookalike 1% on this seed has historically outperformed prospecting by 3.2x. Cost to add: 5 minutes.

EMQ on meta is 7.3 — below the 8.0 floor we expect for paid social. Concentrated in checkout. fbp cookie regression aligns with the cart deploy on Tue.

OAuth refresh token last rotated 89 days ago. Google has been deprecating long-lived refresh tokens — pre-empt the rejection.

Last 7d of delivery_metrics, EMQ scores, audience sync errors, boosted-event lift, open insights, quota trajectory.

GPT-5.5 with a strict-JSON contract. Required: rationale must cite specific data; expected_impact_pct ∈ [0,50]; 3-5 actions exactly.

Email (HTML body) + Slack (priority dots) + dashboard at /ai-operator. Last 12 weeks of action sets persist per workspace.

You mark each action done, scheduled, or dismissed (with reason). The next week's report adapts based on what you did and didn't ship.