Diagnosing a search traffic drop

The goal is a specific, evidenced answer: which pages lost the clicks, and what kind of problem it is. "Traffic is down 20%" is not an answer. "Four pages are 80% of the loss and all four slipped from page one" is.

Before you start

Call list_gsc_sites and confirm which property to use. Do not guess the URL format — https://example.com/ and sc-domain:example.com are different properties with different data, and picking the wrong one silently returns an empty or partial answer.

Ask for the two periods if the user has not given them. If they say something vague like "since last month", propose two concrete equal-length ranges and confirm before running.

Windows must be equal length and should align on weekdays. Comparing 30 days to 28 days manufactures a 7% drop out of nothing. Comparing a period containing five Mondays to one containing four does the same, more subtly.

The diagnosis

1. Attribute the change. Call gsc_traffic_drop with the two ranges, dimension: 'page'.

   Read totalClicksLost and totalClicksGained before the contributor list. If both are large, the site did not simply decline — traffic moved, and that is a different story with a different fix.

2. Find the shape. Look at shareOfDecline across the contributors.

   • A few pages carrying most of the decline is a page-level problem: those specific pages lost rankings, were changed, or were deindexed.
   • The decline spread thinly across many pages is a site-level problem: an algorithm update, a technical regression, or a manual action.

   These lead to completely different investigations. Establish which one you are in before going further.

3. Separate ranking loss from demand loss. For the top contributors, compare impressionsDelta against positionDelta.

   Impressions	Position	Reading
   Down	Worse (positive delta)	Lost rankings — competitors, or a content problem
   Down	Flat	Fewer people searching, or the SERP changed above you
   Flat	Flat, clicks down	An AI Overview or a new SERP feature is absorbing the clicks

   The third row is increasingly the answer and is invisible if you only look at clicks.

4. Check the queries, but only for the affected pages. Re-run gsc_traffic_drop with dimension: 'query'. If the lost queries are all one topic, that is a content or intent problem. If they are scattered, it is more likely technical or sitewide.

Reporting

Lead with the shape and the evidence:

Clicks fell 2,400 (-31%) between the two periods. Four pages account for 78% of that. All four lost rank (average position 4.2 → 11.6), and impressions fell with them, so this is lost rankings rather than lost demand. The affected pages are all in /guides/.

Then give the next step, and be honest about what the data cannot tell you.

What this data cannot answer

Search Console shows what happened, never why. It does not know about algorithm updates, your deploys, your competitors' publishing, or seasonality. Two things follow:

• Always check whether the drop lines up with a known event — a release, a migration, a redesign, a robots.txt change. Ask the user; the data will not volunteer it.
• Never assert a cause you cannot see in the numbers. "This correlates with a rankings loss on these four pages" is supportable. "Google's update hit you" is a guess unless the dates line up and you say so as a hypothesis.

Position is a weighted average across every impression, so a page ranking 3rd for one query and 40th for another does not "rank at 21". Treat large position swings on low-impression pages with suspicion — they are usually a change in which queries matched, not a change in ranking.