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PARTLY

As of 13 August 2026, AI can only partly build a negative keyword list for your Google Ads.

Most people should hand this to a purpose-built tool.

Can you do it?

5 minutesto a draft.

30 minutesto something you’d act on.

Cost, all in£0

Skill neededchat-fluent

Who has to check ityou

What the alternative costsThe available tool data gives no price for a human paid-search specialist or another comparable alternative.

If this goes wrong, the list can block relevant searches or leave irrelevant clicks running until you notice the change in campaign performance.

What to actually do

  1. Use a tool built for this

    The route this page recommends

  2. Do it yourself

    Second choice

    A chat interface, chat-fluent skill, and roughly 30 minutes until you can act on the result.

    How to actually do it

    1. Open Google Ads and export the latest Search terms report for the relevant campaigns, including the search term, campaign or ad group, clicks, cost and conversions where available.
    2. Write down the products, services, locations and customer types you want the campaign to attract, plus exclusions such as jobs, free resources, training or unrelated products.
    3. Paste that information and the unedited search-term report into the prompt, keeping campaign and ad-group names attached to each term.
    4. Ask the chatbot to produce the proposed list in separate campaign-level and ad-group-level sections, with match type and a reason for every entry.
    5. Compare every proposed negative with your current adverts and landing pages, removing any term that could describe a relevant customer, product or location.
    6. Add only the checked entries to the appropriate Google Ads negative keyword list, then keep the flagged ambiguous terms out of the account.
    7. After the next search-term report is available, compare new irrelevant queries and missed relevant queries with the list and amend it manually.

    Prompt

    Build a proposed negative keyword list for a Google Ads campaign using the information below.

Business and offer: [describe what you sell]
Target customers: [describe who should see the ads]
Campaign goal: [sales, leads, bookings or another goal]
Geography: [locations served]
Important products, services or topics to keep eligible: [list them]
Searches that should be excluded: [list irrelevant audiences, products, jobs, research queries, free information or other exclusions]
Current search-term report: [paste the search terms and, if available, clicks, cost, conversions and campaign or ad-group names]

Return a table with these columns: search term, proposed negative keyword, match type, reason, campaign or ad group, and confidence. Separate campaign-level negatives from ad-group-level negatives. Do not invent search terms, performance data or business facts. Do not recommend a negative if it could block a relevant customer search. Flag ambiguous terms for manual review instead of deciding them. Group duplicate ideas, explain broad, phrase and exact match implications in plain English, and finish with a short list of terms that must not be added without checking the landing page and current campaign structure.

    Open it prefilled in ChatGPT or Claude, or copy it into Gemini, which takes no prefill link.

  3. Hand it to a person

    The distant third

    A person who owns the outcome does this end to end, worth it when the failure is dear.

What it gets wrong

  • AI cannot see your live Google Ads account, current search-term report or campaign structure unless you export and provide them.
  • It cannot know whether an ambiguous query is commercially valuable without your offer, margins, landing page and sales judgement.
  • It can recommend the wrong match type and block relevant searches if you apply the list without checking the surrounding terms.
  • It does not monitor future search behaviour or update the list after the campaign changes.

What caps this at PARTLY: judgement under ambiguity, real time truth and stakes of error.

How we scored this

Five axes, each scored nought to two by hand: ten means AI carries the task cleanly, and the thresholds that turn a total into YES, PARTLY or NO are published in the methodology. Each axis name links to its definition.

AxisScore (0–2)
Output2
Inputs1
Verification1
Liability1
Effort delta2
Total7 / 10

The methodology and its thresholds are published in full.

FAQ

Can ChatGPT create negative keywords for Google Ads?
Yes, it can draft and organise a negative keyword list from your offer, exclusions and search-term report. It cannot access your live account or reliably decide every ambiguous term, so check the draft before applying it.
How do I find negative keywords for my Google Ads campaign?
Export the Search terms report from Google Ads and mark searches that are irrelevant to your products, customers or locations. AI can group those terms and suggest match types, but you must check that each negative will not block a valuable search.
What should I avoid adding as a negative keyword?
Avoid terms that could describe a product, service, location or customer you genuinely want, especially when the wording is ambiguous. Check the complete search query, advert and landing page before adding a broad or phrase negative.
Can AI automatically add negative keywords to Google Ads?
A chatbot cannot safely make account changes without an approved integration, and a generated list still needs human checking. Use AI for the proposed list, then apply only the entries you have matched to the correct campaign or ad group.

Nearby answers

All Paid ads rulings

Assessed by gpt-5.6-luna (gpt-5.6-luna) on 2026-08-13, second-checked by an independent model. Wrong somewhere? Email [email protected] and it gets re-checked.

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