AnalyticsGoogle Ads analysisIntermediateAnalyses your data

Keyword structure and match-type audit

Reviews keyword lists and match types for overlap, intent mixing and cannibalisation, with the data you need to confirm each finding.

For: Performance marketers, Marketing analysts, Growth marketers · Works with: Google Ads, 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 a paid-search auditor. Audit this keyword setup for an online mattress retailer. Keywords (ad group | keyword | match type | clicks | conversions | cost): Ad group | Keyword | Match | Clicks | Conversions | Cost Mattresses | mattress | broad | 3200 | 14 | 1600 Mattresses | buy mattress online | phrase | 900 | 22 | 540 Mattresses | [buy mattress online] | exact | 450 | 19 | 300 Sale | mattress sale | broad | 1500 | 21 | 700 Campaign goal: online sales at a CPA under 60. Bidding strategy in use: Maximise conversions. Tasks: 1. State assumptions (for example whether duplicated keywords sit in different ad groups or campaigns). 2. Find overlap and duplicate intent across match types and ad groups, and explain what could go wrong (query routing and competing against yourself) in general terms. 3. Group keywords by intent (research, comparison, purchase, brand) and note ad groups mixing intents. 4. Suggest a cleaner structure with the reasoning, keeping it proportionate to the account's volume. 5. List which findings need confirmation from the search-terms report or other data, and why. 6. List missing data. Rules: do not invent search volumes, competition data or quality scores. Missing information must be requested, not guessed. Verify that every keyword mentioned appears in my list. Treat structure recommendations as hypotheses to test, and note that platform behaviour for match types changes over time, so I should confirm current match-type documentation.

Customize

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

What you sell.

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

What the campaign must achieve.

Bidding in use.

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.

Overlap and duplicate-intent findings (for example the same phrase across match types and ad groups), intent grouping, a simpler structure proposal, items needing search-terms confirmation and missing data. (Illustrative.)

Expected format: Assumptions, overlap findings, intent groups, proposed structure, confirmations needed.

How to use it

  1. Confirm findings with the search-terms report.
  2. Restructure gradually.
  3. Document the structure for the team.

Limitations

  • Match-type behaviour evolves; confirm in Google's current documentation.
  • Structure advice depends on volume and bidding strategy.

Platform notes

Google Ads

Official docs read · checked 2026-10-11

Google Ads field names and units (for example cost expressed in micros in the API) must be confirmed in Google's reference; the GAQL overview page we read does not list them.

General notes on Google Ads
  • GAQL uses SELECT/FROM/WHERE/ORDER BY/LIMIT. Confirm resource and field names (for example cost fields, which are expressed in micros) in the API reference; the overview page does not list them.

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-013. We will correct or remove it.

Related prompts

  • AnalyticsIntermediateAnalyses your data

    Google Ads search-terms report: wasted spend and negative keywords

    Groups search terms by pattern, estimates wasted spend from your data and proposes negatives, with a protected 'do not negate' list and match-type cautions.

    Google Ads · Any capable chat model (ChatGPT, Claude, Gemini, others)

  • AnalyticsAdvancedWrites SQL / queries

    Google Ads Query Language (GAQL) query builder

    Gets a GAQL query for a specific report, with explicit instructions to confirm field names, unit conventions and segment compatibility.

    Google Ads · Any capable chat model (ChatGPT, Claude, Gemini, others)

  • AnalyticsIntermediateAnalyses your data

    Google Ads campaign diagnostic against CPA or ROAS targets

    Compares campaigns against your target, separates volume, efficiency and conversion-rate drivers, and highlights what the data cannot explain.

    Google Ads · Any capable chat model (ChatGPT, Claude, Gemini, others)

  • AnalyticsIntermediateAnalyses your data

    Responsive search ad asset performance review

    Reviews headline and description asset reports for patterns and proposes new assets, while flagging how little asset-level data can prove.

    Google Ads · Any capable chat model (ChatGPT, Claude, Gemini, others)