AnalyticsSearch Console and SEO analysisIntermediateAnalyses your data

Search Console opportunity finder: queries near page one with low CTR

Finds queries where an improvement is plausible (decent impressions, mid-ranking, low CTR) and suggests page-level actions as hypotheses.

For: Performance marketers, Marketing analysts, Growth marketers · Works with: Google Search Console, Any capable chat model (ChatGPT, Claude, Gemini, others)

Public beta. This prompt was drafted with AI assistance and checked by automated rules, but it has not been reviewed or tested by a person yet. Treat it as a starting point and check the output. It is hidden from search engines while in beta. Use the “Was this prompt useful?” box to tell us what works.

Your prompt

Act as an SEO analyst. Using ONLY the Search Console export below for last 3 months, find optimisation opportunities. Data (query | page | clicks | impressions | CTR | average position): Query | Page | Clicks | Impr | CTR | Position utm builder free | /utm-builder | 220 | 9800 | 2.2% | 6.1 utm parameters meaning | /glossary/utm | 90 | 15400 | 0.6% | 8.7 best utm tool | /utm-builder | 40 | 7100 | 0.6% | 11.4 Site and goal: a free marketing-tools site that wants more tool usage. Tasks: 1. State assumptions, including that average position is an average across impressions and can hide variation, and that anonymised or dropped rows may be missing. 2. Compute CTR from clicks and impressions yourself and check it against the CTR column. 3. Shortlist queries where impressions are meaningful for this site (use the top 50% by impressions as your working definition, stated as an assumption), average position is roughly 4 to 15, and CTR is low relative to others at similar positions in this same dataset (not external benchmarks). 4. For each, propose page-level actions as hypotheses (title and snippet, intent match, content depth, internal links), and say how to measure the result. 5. Group queries by page to avoid conflicting edits. 6. List missing data (competitor results, SERP features, branded vs non-branded split). Rules: do not invent search volumes, rankings or benchmarks. Missing data must be flagged. Verify calculations. Position and CTR relationships are correlational; do not promise ranking gains.

Customize

The fields start with example values so you can see how the prompt works. Everything stays in your browser.

Period of the export.

Paste your export. The default is small fictional sample data so the preview works; replace it with your own export.

Context.

Working definition of 'meaningful'.

Where improvement is plausible.

Example of what to expect

Illustrative only. It describes the kind of result this prompt aims for; real output varies by tool, model and run.

CTR recomputed and checked, a shortlist of queries by opportunity within the dataset, page-level hypotheses grouped by URL, measurement notes and missing data. (Illustrative.)

Expected format: Assumptions, shortlist, grouped hypotheses, measurement plan.

How to use it

  1. Export queries with page dimension from Search Console.
  2. Edit pages one change at a time.
  3. Wait for data before judging changes.

Limitations

  • Search Console data is sampled and delayed; adding page or query dimensions can drop rows.
  • Rankings and CTR depend on SERP features and competitors the data does not show.

Platform notes

Google Search Console

Official docs read · checked 2026-10-11

Search Console data lags by 2-3 days, adding page or query dimensions can drop rows, and the API caps rows per request (per Google's documentation); account for this when comparing recent periods.

General notes on Google Search Console
  • Adding page or query dimensions can drop rows, and data lags by 2-3 days, so recent days look artificially low. Totals computed without page/query dimensions are more accurate.

Any capable chat model (ChatGPT, Claude, Gemini, others)

Official docs read · checked 2026-10-11

Works in any capable chat model. Paste a small anonymised export and recompute the key numbers yourself: chat models can misread columns or miscalculate.

General notes on Any capable chat model (ChatGPT, Claude, Gemini, others)
  • These prompts are plain text and work in any chat assistant. For analytics prompts, paste a small, anonymised export; a chat model can misread columns or miscalculate, so recompute key numbers yourself.

Source, license and attribution

Origin
Original by MarketerTools
Publisher
MarketerTools
License
Original work by MarketerTools, free to copy and use. Informed by the linked documentation; no third-party text is reproduced.
Platform assumptions checked
2026-10-11

Documentation and references behind this prompt

These informed the structure and the platform notes. A reference is not a license, and no third-party prompt text is copied here.

Spotted an attribution error, or are you a source owner with a request? Use the chat button at the bottom right and quote prompt ID ana-019. We will correct or remove it.

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