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How to use ChatGPT for Google Ads
Blog · Advertising

How to use ChatGPT for Google Ads

Where an AI assistant genuinely saves hours in a Google Ads workflow, where it quietly invents things, and a repeatable process that keeps the difference clear.

By the Vikilinks team 9 min read Published 27 August 2026
A marketer using an AI assistant on a laptop while reviewing Google Ads campaign performance

ChatGPT will not run your Google Ads account. It will, however, remove several of the slowest hours in the week, and it is very good at exactly the tasks most people dread: writing thirty headline variations, reading a search terms export, and rewriting a landing page so it matches the ad.

It is also confidently wrong about anything numeric. The workflow below is built around that split. Use it for language and pattern-finding, never for data it does not have.

What it is actually good at, and what it is not

Getting this boundary right is most of the skill. Everything on the left is a genuine time saving. Everything on the right will cost you money if you trust it.

Task Trust it? Why
Bulk ad copy variations Yes, with review Pure language generation, and you can verify every line against a character limit.
Keyword themes and intent groups Yes, as a starting point Good at expanding your thinking. Validate every term against real volume before you bid.
Search terms report analysis Yes, this is the best use Pattern-finding across data you supply, so nothing has to be invented.
Negative keyword brainstorming Yes, as a first draft It reliably surfaces the obvious intents you forgot. It will not know your niche exclusions.
Landing page copy and message match Yes, with review Improves Quality Score and conversion together, and you are the judge of accuracy.
Search volume, CPC and competition figures No It has no live data and will produce plausible numbers that are simply not real.
Budget, bidding and conversion decisions No Confident wrong calls here spend real money fast. Keep them human.
Claims about your business or results No It will invent specifics. Every factual claim must come from you.

The workflow, step by step

This is the order we use. Each step feeds the next, and the last one is not optional.

  1. 1

    Give it your account context first

    Before you ask for anything, paste in what you sell, who buys it, your price point, your service area and what a good lead looks like. Generic output is almost always the result of a generic brief, not a weak model.

  2. 2

    Build keyword themes, not keyword lists

    Ask for groups of search intent around your service rather than a flat list of terms. Then check every one against real volume in Keyword Planner, because a language model estimates nothing about search demand.

  3. 3

    Draft responsive search ad assets in bulk

    Ask for 15 headlines under 30 characters and 4 descriptions under 90, each built around a distinct angle: price, speed, proof, risk reversal, locality. Bulk drafting is where the time saving is real.

  4. 4

    Pressure test the angles against your competitors

    Paste in the ad copy currently showing for your terms and ask what claim nobody is making. The gap in the auction is usually more useful than another variation of what everyone already says.

  5. 5

    Generate a negative keyword starting list

    Ask for the intents you do not want: jobs, free, DIY, courses, wholesale, and the neighbouring services you do not offer. Treat it as a first draft to add to, never as a finished list.

  6. 6

    Turn the search terms report into decisions

    Export the report, paste it in, and ask it to group terms by intent and flag likely waste. This is the highest value use of all, because it is pattern-finding across data you already own.

  7. 7

    Write the landing page to match the ad

    Ask for a headline and opening section that echo the ad promise. Message match lifts Quality Score and conversion rate at the same time, and it is the step most people skip.

  8. 8

    Verify everything before it goes live

    Check character limits, claims, spelling and Australian English by hand. Never let generated copy publish unread, because a confident invented claim is the one thing that will cost you more than it saved.

Prompts that actually produce usable output

The difference between useless and useful output is almost entirely in how much context you give. Each of these assumes you have already pasted in your offer, audience and location.

  • Ad copy. "Write 15 headlines of 30 characters or fewer and 4 descriptions of 90 or fewer for this service. Each headline must use a different angle. Australian English. No claims I have not given you."
  • Search terms. "Here is my search terms report. Group these by intent, flag anything that looks like wasted spend for my business, and list candidate negatives with a reason for each."
  • Competitive angle. "Here is the ad copy currently running for these terms. What promise is nobody making, and which of those could we credibly make?"
  • Message match. "Here is my ad and here is my landing page. Where do they disagree, and what would you change on the page so the promise carries through?"

If you want a broader grounding in prompt structure, our guide to the PTCF prompting framework applies just as well here.

The mistakes that cost people money

  • Publishing generated copy unread. It will occasionally invent a guarantee, an award or a price.
  • Trusting invented search volumes and building a budget on them.
  • Accepting American spelling and phrasing into an Australian account.
  • Generating 30 headlines that are all the same angle reworded, which teaches the auction nothing.
  • Improving the ad and leaving the landing page untouched, so the extra clicks bounce.

Not to be confused with advertising on ChatGPT

These two get mixed up constantly. Using ChatGPT for Google Ads means using an AI tool to do your existing work faster. Advertising inside ChatGPT is a separate channel, bought through OpenAI's own Ads Manager, with its own auction and setup. If that is what you were after, start with how to advertise on ChatGPT, or compare the two channels in ChatGPT Ads vs Google Ads.

Getting help with Google Ads

Every step above is something you can do yourself, and the workflow is deliberately written so you can. If you would rather hand it over, our Google Ads management service covers structure, copy, negatives, conversion tracking and ongoing optimisation, with AI used where it genuinely helps and human judgement kept where it matters.

In short

How do you use ChatGPT for Google Ads?

Give ChatGPT your offer, audience and location first, then use it for four things: generating keyword themes to validate later, drafting bulk responsive search ad headlines and descriptions against character limits, brainstorming negative keywords, and grouping your search terms report by intent to find waste. Do not use it for search volume, cost per click, competition data, or budget and bidding decisions, because it has no live data and will produce plausible figures that are not real. Verify every claim and character count before publishing.

Key takeaways

  • Use it for language and pattern-finding. Never for search volume, cost per click or competition data.
  • Analysing your own search terms report is the single highest value use, because nothing has to be invented.
  • Context is everything: a generic brief is the real cause of generic output, not the model.
  • AI copy does not hurt Quality Score. Vague copy and mismatched landing pages do.
  • Using ChatGPT for Google Ads is a different thing from advertising inside ChatGPT.
Questions

ChatGPT and Google Ads, answered

Yes, and it is genuinely good at bulk drafting. Give it your offer, audience and a character limit and it will produce more headline variations in a minute than most people write in an hour. What it cannot do is know your margins, your market or whether a claim is true, so every line still needs a human check before it goes live.

It is useful for generating themes and intent groups, and unreliable for anything numeric. A language model does not have live search volume, competition or cost per click data, and will produce confident looking figures that are not real. Use it to expand your thinking, then validate every term in Keyword Planner or your search terms report.

Not in itself. Google scores relevance, expected click-through rate and landing page experience, and it does not care who typed the words. AI copy hurts you when it is vague, when it does not match the search intent, or when the landing page does not deliver what the ad promised. Those are copy problems, not AI problems.

Three things: drafting large volumes of ad variations quickly, finding patterns in a search terms export, and rewriting landing page copy so it matches the ad. Those are all tasks where speed matters and where you can verify the output yourself. It is weakest anywhere it would need real data it does not have.

No, and it is worth keeping the two apart. Using ChatGPT for Google Ads means using an AI tool to do the work better. Advertising on ChatGPT means buying placements inside ChatGPT itself through OpenAI's Ads Manager, which is a separate channel with its own auction and its own setup.

Not the decisions. Use it for drafting, grouping and analysis, and keep budget, bidding and what counts as a conversion under human control. The failure mode is not that the AI is careless, it is that it is confident, and a confident wrong decision about budget costs real money quickly.

Written and maintained by the team at Vikilinks, an Australian digital agency based in Parramatta, NSW. This is the workflow we actually use on client accounts. AI tools and Google Ads features both change quickly, so treat the specifics as current at the time of writing and confirm character limits and policies in your own account before you launch.

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