How recommendations work

Adsevon's recommendation engine is deterministic: it runs a set of detectors over your campaign data looking for known waste and opportunity patterns — rising CPA, fatigued creatives, budget misallocation, and others. The same data always produces the same findings.

From data to recommendation

1. Detect. Each detector checks one pattern against your metrics and thresholds.
2. Prioritize. Findings are ranked by expected impact and confidence, so the biggest opportunities surface first.
3. Explain. Every recommendation cites the exact numbers that triggered it.

Refreshing

Recommendations refresh when new data arrives. Findings that no longer apply are superseded automatically — your list always reflects the current state of your campaigns, not last month's.