Where did clicks fall?
Start with losses that affect traffic, rather than a large percentage on two clicks.
A table of the 10 largest observed click losses, with both baselines.
02 / Use cases
Your Search Console metrics are most useful when they answer a specific decision. These are the analyses worth running first—with your own pages, queries and time periods.
14 days free · No cardLess reporting for reporting's sake. More signals you can act on.
01 / Start with the problem
Pick the signal you want to understand. A click drop and a weak CTR call for different investigations.
Start with losses that affect traffic, rather than a large percentage on two clicks.
A table of the 10 largest observed click losses, with both baselines.
The 500-impression threshold is a working filter; low CTR at position 40 is a different problem.
Five pages with CTR, impressions, position and the queries to inspect.
Use an explicit exploratory threshold, not an invented search-volume estimate.
Ten query–page pairs and the pages to review first.
Agree on the baseline before explaining a change; CTR differences use percentage points.
Clicks, impressions, CTR and position for both periods; absolute and relative click changes.
Check query intent and snippets before assuming the whole page needs rewriting.
Five refresh candidates with evidence and one inspection action each.
Separate facts from hypotheses; AskGSC does not schedule or email this report.
A report in the conversation, with dates, scope and evidence for each recommendation.
02 / How to read the answer
Impressions can grow while clicks fall. Average position can change without the same impact across queries. Put the metrics next to each other before deciding.
Pick one property and a comparable date range.
Pages, queries, countries or devices depending on the question.
Ask the assistant to separate observations from explanations.
03 / Questions worth asking
Copy one, add your property and let the assistant ask for the relevant Search Analytics data.
Compare page clicks for my property over the last 28 days versus the previous 28. Show the largest declines and their impressions.
Show high-impression pages with low CTR in the past 28 days, alongside their average position.
Find queries averaging positions 11–20 with meaningful impressions. Group them by landing page.
Clicks fall 25% while impressions rise 50%. CTR falls by 1 percentage point, not 1%. With the same average position, inspect the query mix and snippets before rewriting the page. These figures do not establish a cause.
Use the same property, complete periods and filters for each comparison. Sort metric thresholds in the returned data: they are analysis criteria, not Search Analytics dimension filters. Missing rows remain unknown, not zero.
| Period | Clicks | Impressions | CTR | Average position |
|---|---|---|---|---|
| Previous | 400 | 20,000 | 2% | 8 |
| Current | 300 | 30,000 | 1% | 8 |
04 / FAQ
Short answers about the data, the MCP connection and what this approach actually does.
No. It analyzes Search Console performance data. It is not a site crawler or a substitute for technical inspection.
Start with comparable date ranges, the same property and the surrounding metrics. Some changes are seasonal or reflect reporting differences.
You can access the properties authorized to your Google account, and analyze them individually. Specify the property you want the assistant to query.
Next step
Give your assistant read-only access to Search Console data instead of exporting another spreadsheet.