How to Use Claude to Audit Your Google Ads Account in 30 Minutes
- saurav soni
- 6 hours ago
- 3 min read
Most Google Ads accounts have three to five things that are costing serious money — and most of them have been there for months. The problem isn't that they're hard to find. It's that a thorough audit takes time, and time is the thing nobody has. AI changes that equation completely.
Here's the exact process I use — and that you can use — to audit a Google Ads account in about 30 minutes using Claude. This is the same audit that used to take me most of a day before AI tools were part of my workflow.
Step 1 — Pull the right reports from Google Ads (10 minutes)
Before you touch Claude, you need the raw data. Pull four reports from your Google Ads account. First, the Search Terms report for the last 90 days — this shows every actual search that triggered your ads, not just your keywords. Second, the Campaign Performance report — impressions, clicks, conversions, cost, and conversion value broken down by campaign. Third, the Ad Group Performance report with Quality Score data. Fourth, your Conversion Actions list — so you can see what you're actually tracking as a conversion.
Export all of these as CSV files. You don't need to clean them up or format them. Raw exports work fine.
Step 2 — Feed the data to Claude with a structured prompt (5 minutes)
Open Claude and upload your CSV files. Then give it a prompt that tells it exactly what you're looking for. Something like: "You are auditing a Google Ads account for a UK B2B service business. The target CPL is £X. Review the attached reports and identify: 1) the top 10 search terms that are consuming budget but have zero conversions, 2) any campaigns with conversion tracking anomalies, 3) ad groups with Quality Scores below 5, 4) the budget split between campaigns and whether it aligns with conversion performance, 5) any conversion actions that appear to be tracking incorrectly based on volume patterns."
The more specific your prompt, the more useful the output. Generic prompts get generic responses. Tell Claude what kind of business this is, what success looks like, and what you're trying to fix.
Step 3 — What Claude finds that humans typically miss (10 minutes)
The pattern I see most often when I audit accounts this way: wasted spend on irrelevant search terms is almost always higher than the account owner expects. In a recent audit I ran, a B2B services account was spending 34% of its monthly budget on searches that had nothing to do with the service being advertised — terms that were vaguely related but would never convert. That's a third of the budget. Found in ten minutes.
Claude is also good at spotting conversion tracking problems that humans rationalise away. If your account shows 200 conversions last month but only 8 of them resulted in actual sales conversations, something is being tracked that shouldn't be. AI reads the pattern in the data without the cognitive bias of wanting the numbers to look good.
Step 4 — Apply your judgment to the findings (10 minutes)
This is the step that separates useful AI-assisted auditing from just generating output. Claude identifies the patterns. You decide what to do about them based on context Claude doesn't have. Maybe the low-Quality-Score ad group is intentionally testing a new market. Maybe the search terms that look irrelevant are actually bringing in a valuable customer type that hasn't converted yet in the data window. Your knowledge of the business makes the findings actionable.
Go through the findings, mark what you're acting on immediately, what needs more investigation, and what you're consciously choosing to leave. Then build your action list. That list — informed by AI analysis and filtered through real expertise — is what actually improves the account.
What this process consistently finds
Across accounts I've audited this way — B2B services, construction, solar, professional services in the UK — the findings cluster around the same issues every time. Negative keyword lists that haven't been updated in months or don't exist at all. Budget on campaigns running the wrong bidding strategy for their conversion volume. Conversion tracking counting things that don't represent real business outcomes. Ad groups mixing high and low intent keywords so the algorithm optimises for the wrong signals. Fixing these four things alone typically brings CPL down 25 to 40% without touching the budget.
If you'd rather I run this audit on your account than do it yourself — this is literally one of the first things I do with every new client. Takes me about 30 minutes and the findings usually change the entire direction of what we do in month one:
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