How to automate your Google Ads workflow with the ChatGPT API

If you’re still just copy-pasting prompts into ChatGPT to write ad copy, you’re missing the real opportunity – using the ChatGPT API to automate repetitive, time-consuming tasks inside your Google Ads workflow.

At my agency, we’ve used GPT-4o in scripts, Google Sheets, and custom-built apps to solve real problems – from Shopping feed cleanup to search term waste audits to performance reviews across entire accounts. 

This article shows you how to set up the API, use it safely and efficiently, and apply it to high‑impact PPC workflows.

Step 1: Get access to the ChatGPT API

To use GPT in your own scripts or applications, you’ll need access to the OpenAI API. This is not the same as using ChatGPT in a browser – the API gives you direct programmatic control.

Here’s how to get started:

• Create a free OpenAI account: platform.openai.com/signup
• Generate an API key:
  • Go to API Keys.
  • Click Create new secret key.
  • Save the key somewhere secure. You won’t be able to view it again.

Your API key is private and sensitive. Anyone with access can use your account balance, so treat it like a password.

What it costs (and what you should budget for testing)

The ChatGPT API is pay-as-you-go. As of writing, GPT-4o (the fastest and most cost-effective model) costs:

• $0.005 per 1,000 input tokens.
• $0.015 per 1,000 output tokens.

1,000 tokens is roughly 750 words of input/output combined. Most simple prompts cost less than $0.01 per call.

For testing:

• Start by setting a $25–$50 prepaid credit. That’s enough to prototype, build, and even run light production scripts for a few weeks.
• Monitor usage under Billing > Usage.
• Set a usage limit at Billing > Limits to avoid surprises.

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Step 2: Choose where you’ll use the API

You can call the API from different environments depending on your comfort level and workflow:

Tool	Best For	Difficulty
Google Apps Script	Sheets-based reporting, feed work	Beginner
Python	Audit logic, report generation	Intermediate
Node.js	Web apps, dashboards, asynchronous batching	Advanced
Zapier	Lightweight GPT integrations (no code)	Beginner

If you’re working in Google Ads and pulling data into Sheets, Apps Script is an easy entry point.

Step 3: Call the ChatGPT API (example in Google Apps Script)

Here’s a basic implementation of calling GPT-4o from Google Sheets:

function callChatGPT(prompt) {

  const apiKey = 'sk-...'; // Your API key

  const url = 'https://api.openai.com/v1/chat/completions';

  const payload = {

    model: 'gpt-4o',

    messages: [

      { role: 'system', content: 'You are a Google Ads expert.' },

      { role: 'user', content: prompt }

    ],

    temperature: 0.3

  };

  const options = {

    method: 'post',

    contentType: 'application/json',

    headers: {

      Authorization: 'Bearer ' + apiKey

    },

    payload: JSON.stringify(payload)

  };

  const response = UrlFetchApp.fetch(url, options);

  const json = JSON.parse(response.getContentText());

  return json.choices[0].message.content;

}

Then in a cell:

=callChatGPT("Analyze Nike's top 50 non-converting search terms from Performance Max")

Dig deeper: Leveraging generative AI in ad scripts for Google Ads optimization

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Step 4: Efficiency best practices

To keep things running smoothly (and cost-effectively), follow these tips:

• Batch your inputs: Group 5-20 titles or search terms in one request.
• Use system prompts: Set the role clearly (“You are a Google Ads strategist for Nike”).
• Lower temperature (0–0.3): Keeps outputs consistent and avoids hallucination.
• Control response length: Ask for specific output format or word count when needed.
• Test edge cases: Run messy inputs through manually to see how GPT responds.

Real-world use cases for Google Ads

To demonstrate how this works in practice, I’ll walk through some real use cases using Nike as an illustrative example. 

For clarity, I’m not affiliated with Nike, and these examples are hypothetical. 

They’re used to show how these techniques apply to enterprise-level Google Ads accounts with large product catalogs and high-volume campaigns.

Use case 1: Shopping feed optimization

Nike’s product feed is massive – shoes, clothing, gear, accessories – all in dozens of variants. 

Product titles that aren’t well-structured can result in poor visibility or irrelevant impressions.

Using GPT-4o, you can rewrite product titles at scale using this structure:

Rewrite the product title to include gender, product type, main feature, and brand. Format as: [Gender] [Product Type] with [Feature] | Nike.

• Before: “Air Zoom Pegasus 40”
• After: “Men’s Running Shoes with Responsive Cushioning | Nike Air Zoom Pegasus 40”

We ran this workflow in Google Sheets using GPT via Apps Script. 

Output titles were more keyword-aligned, more descriptive, and performed better in Shopping ads – increasing CTR and improving match relevance.

Use case 2: Search term waste auditing in Performance Max

Nike’s Performance Max campaigns generate huge volumes of search term data – much of it irrelevant. 

Reviewing it manually is inefficient and inconsistent.

Our approach:

• Pull in top-spending terms with zero conversions.
• Use GPT to analyze and categorize waste themes.

Prompt example:

• “You are auditing Nike’s Performance Max search terms. Group the following into themes like competitor traffic, job searches, or unqualified queries. Return a summary and examples.”

GPT output:

• Competitor searches: “adidas running shoes,” “under armour basketball gear.”
• Careers: “nike warehouse job application,” “retail jobs at nike.”
• DIY/informational: “how to clean nike shoes,” “best running shoes for flat feet.”

We use this output to generate negative keyword ideas, refine targeting, and create weekly alerts if waste passes a threshold.

Dig deeper: How AI makes paid search audits faster and better

Use case 3: Google Ads audit automation for Nike brand campaigns

We’ve built a tool that combines the Google Ads API with GPT-4o to run full account audits.

In Nike’s case, we used GPT to interpret performance flags pulled from API queries like:

• High-spend keywords with Quality Score < 5.
• Campaigns losing impression share due to budget.
• Device-level CPA imbalances.
• Unused sitelinks or ad extensions.

Prompt example:

• “Nike’s brand campaign has 14 keywords spending over $1,000/mo with a Quality Score of 3. Suggest hypotheses for low performance and what changes we should consider.”

GPT response:

• Ad copy likely missing branded modifiers (e.g., “Nike outlet,” “Nike store near me”).
• Landing page mismatch – queries may be location-based but page is product-focused.
• High mobile traffic + slow load time = poor landing page experience score.

This output is added directly to a Google Slides deck used for internal reviews and client QBRs.

Using the ChatGPT API for high‑impact Google Ads automation

ChatGPT isn’t just a writing assistant – it’s an automation engine.

The key isn’t asking GPT to do your job. 

The key is plugging GPT into the places where repetition slows you down: 

• Cleaning up feed data.
• Summarizing noisy reports.
• Generating hypotheses.
• Providing structured analysis at scale.

You don’t need to be a developer to use the API. Google Apps Script and Sheets are powerful enough to run real workflows today. 

Once you see the time savings – and the quality of GPT-4o outputs when structured correctly – it’s hard to go back.

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