Diagnose a drop in Google Search traffic before changing a single page

Organic search traffic to my site dropped. Help me work out why before anyone edits a page.

Site: {{domain, what kind of site, roughly how many indexed pages}}
When it started: {{date, and whether it was a cliff overnight or a slide over weeks}}
What changed on our side around then: {{deploys, migrations, redesigns, robots.txt or CMS changes, new templates, or "nothing we know of"}}
Search Console Performance report, last 3 months compared with the previous period: {{totals for clicks, impressions, CTR and average position in both periods}}
The same comparison year over year: {{totals, or "site is under a year old"}}
Pages tab sorted by clicks difference: {{top 20 to 30 rows}}
Queries tab sorted by clicks difference: {{top 20 to 30 rows}}
Country, device and search appearance tabs: {{rows that moved, or "flat"}}
Page indexing and Crawl stats around the drop date: {{anything that spiked, or "not checked"}}
Manual actions and Security issues reports: {{"none", or paste what they show}}

Work through these in order and stop at the first one that explains the drop well enough. Say which step you stopped at.

1. Is the drop real? If Search Console clicks held and only analytics fell, this is a tracking problem (a removed tag, a consent banner change, a filter). Also tell me to check the Search Console data anomalies page for the period.

2. How wide is it? From the pages and queries tables, say whether the loss is site-wide, concentrated in one group (a directory, a template, a content type), or limited to a handful of URLs. Give the share of lost clicks that the ten biggest losers account for.

3. Did impressions fall with clicks?
   - Both down: visibility fell. The candidates are technical (indexing, crawling, a noindex or canonical change on a template), a ranking update, a manual action, a security issue, or falling demand.
   - Impressions steady, clicks down: people still see the result and choose something else. The candidates are a changed title or snippet, a search feature now answering on the page (an AI Overview, a featured snippet, video or shopping units), or a competitor with a richer result. Name the queries that show this pattern.

4. Is it demand? Use the year-over-year comparison to separate seasonality from loss. For the five biggest losing queries, tell me what to look for in Google Trends. If interest fell across the market, the site did not lose ground and there is nothing to fix.

5. Does the timing line up? List what to set against the start date: our own change log, the ranking updates on Google's Search Status Dashboard, and the crawl stats. Do not attribute the drop to a core update on timing alone. Say how strong the overlap is and what else happened in the same window.

6. Verdict: the most likely cause, the evidence for it from what I pasted, the runner-up, and the one export that would tell them apart.

Then sort the actions into three lists.
- Fix now: technical faults with a clear remedy (indexing, robots, redirects, canonicals, a broken template), each with the URL Inspection check that confirms the fix worked.
- Assess, do not rush: for a drop that follows a ranking update, a page-by-page review of the biggest losers against Google's guidance on helpful, people-first content. Note that recovery can take weeks to months and that no single change is guaranteed to move rankings.
- Leave alone: pages that held or grew. Google's own guidance advises against radical changes to pages that still perform well.

If a number I pasted cannot support a conclusion, say so and name the export that would.

Tip: The diagnostic order follows Google Search Central, "Debugging drops in Google Search traffic" (updated December 2025). Search Console keeps 16 months of data; for anything older use the Search Analytics API or the bulk data export. For the steady-impressions, falling-clicks pattern, Pew Research Center measured the effect directly: in March 2025 browsing data from 900 U.S. adults, people clicked a traditional result on 8 percent of visits when an AI summary appeared and on 15 percent when it did not, so a page can lose clicks without losing rank.