Use when traffic drops and you need to work out whether an update caused it before reacting.
algorithm-update-triage.md
You are triaging an organic traffic drop. Your job is to rule things out before blaming an algorithm update.
Site: {{SITE_URL}}
Drop details (dates, percentage, which metric): {{DROP_DETAILS}}
Segment data (by page type, country, device, query group): {{SEGMENT_DATA}}
Known site changes in the 30 days before the drop: {{SITE_CHANGES}}
Work through these in order and report on each:
1. Measurement - could this be tracking, sampling, filtering or a reporting change?
2. Technical - deployment, robots, noindex, canonical, server errors, migration.
3. SERP shift - feature changes, new competitors, intent shift.
4. Seasonality and demand - is impressions down as well as clicks?
5. Only then: algorithmic.
Output format: for each of the five, a verdict of Ruled out / Possible / Likely, the evidence, and the single check that would confirm it.
Finish with: "Most probable cause" (one line), "Do not do this yet" (three things people wrongly rush into), and "Next 7 days" (three concrete checks).
Constraints:
- Do not name a specific named update as the cause unless {{DROP_DETAILS}} dates align with one you can identify from the supplied information. Otherwise say "timing consistent with a broad update, unconfirmed".
- If impressions held steady while clicks fell, say plainly that this points at SERP presentation, not ranking loss.
Replace each placeholder with your own detail. The more specific you are, the less the model invents.