How to Identify Bad Search Terms in Google Ads (Step-by-Step)

Every Google Ads campaign leaks budget through bad search terms. These are the queries that trigger your ads but have nothing to do with what you sell—someone searching for a free tool, a DIY tutorial, or a completely unrelated product. The problem is that Google's broad and phrase match settings cast a wide net, and not every catch is worth keeping.

If you're not regularly reviewing your Search Terms Report, you're almost certainly paying for clicks that will never convert. A search term is what a user actually typed into Google. A keyword is what you bid on. These are not the same thing, and that gap is exactly where budget disappears.

This guide walks you through exactly how to identify bad search terms in Google Ads, from pulling the right report to spotting the patterns that signal wasted spend. You'll also learn how to trace bad terms back to the keywords triggering them, categorize what to cut, and act on it without jumping between tabs or exporting spreadsheets.

Whether you're managing one account or dozens, these steps give you a repeatable process you can run every week. If you've ever wondered why your ads are showing for the wrong keywords, this is where the answer lives.

Step 1: Open the Search Terms Report the Right Way

This sounds obvious, but a lot of advertisers end up in the wrong place. The Search Terms Report is not the Keywords tab. These two reports show fundamentally different things, and confusing them means you're looking at what you bid on rather than what actually triggered your ads.

To get to the right place in Google Ads, navigate to your campaign, then go to Search keywords in the left-hand menu, and select Search terms. Note that Google Ads occasionally updates its interface, so if this path has shifted slightly, look for "Search terms" within the Keywords section. That's the report you want.

Once you're there, the first thing to do is set a meaningful date range. At least 30 days of data gives you enough volume to spot patterns. For lower-traffic campaigns, 60 to 90 days is better. Evaluating search terms on less than two to three weeks of data creates false positives and false negatives: you might exclude a term that would have converted with more time, or keep a bad one that just hadn't accumulated enough clicks to look suspicious yet.

Next, apply a filter for impressions greater than zero. This surfaces all triggered queries, not just the ones that received clicks. High-impression, low-click terms still affect your Quality Score and relevance signals, so they're worth seeing even if they haven't cost you much directly.

One important caveat: Google Ads does not show you every search term that triggered your ads. Some queries are grouped under "Other search terms" when they don't meet a privacy threshold. This means you're working with a partial picture, which is all the more reason to be systematic about the data you can see.

At this stage, you're not making any decisions yet. You're just making sure you have the right view, the right timeframe, and enough data to work with before moving on.

Step 2: Filter for the Metrics That Expose Wasted Spend

Now that you're in the right report with a solid date range, it's time to sort and filter the data so the most important problems rise to the top.

Start by sorting by cost descending. This immediately surfaces the search terms that are draining the most budget, regardless of whether they've converted. These are your highest-priority items. A term that has spent a meaningful portion of your budget and produced zero conversions deserves immediate attention.

Flag any search term with significant spend and zero conversions as a priority review item. Don't exclude it automatically yet—that comes later—but mark it for closer inspection.

Next, add a CTR column to your view. Unusually high click-through rate paired with zero conversions is a signal worth paying attention to. It often indicates curiosity clicks: the ad copy matched something in the query that made people click, but the landing page or offer didn't match what they were actually looking for. That's an intent mismatch, and it's expensive.

Add a conversion rate column as well. Search terms with many clicks but a low or zero conversion rate are strong candidates for exclusion, though the threshold varies by industry and campaign goal. Avoid setting a hard numerical cutoff that doesn't account for your specific context.

One common mistake at this stage is ignoring high-impression, low-click terms. If a query is showing your ad thousands of times but almost nobody is clicking, it's dragging down your overall CTR, which affects Quality Score. These terms might not be costing you directly in clicks, but they're costing you in relevance.

A note on data volume: don't exclude a term solely because it has zero conversions if it only has a handful of clicks. Give terms enough data before making a call. The goal here is to identify patterns and priorities, not to make snap judgments on thin data. You're building a shortlist for the next steps, not a final exclusion list.

Understanding why negative keywords matter becomes much clearer once you can see the cost sitting behind these zero-conversion terms in your own account.

Step 3: Spot the Patterns That Signal Bad Intent

Sorting by cost gets the expensive problems in front of you. This step is about reading the actual search terms and recognizing the patterns that tell you a query is never going to convert for your business.

There are a few reliable categories to look for.

Informational intent signals: Words like "free," "how to," "DIY," "tutorial," "what is," "definition," and "example" indicate that someone is researching, not buying. If you sell B2B accounting software and your ad triggered for "free accounting homework help," that's a clear intent mismatch. The person typing that query wants information, not a software subscription.

Audience mismatch signals: Terms like "student," "school," "kids," "cheap," or "used" often indicate a different buyer profile than the one you're targeting. Competitor brand names you're not intentionally bidding on can also appear here, especially with broad match keywords in play.

Product mismatch signals: These are trickier to spot because they share a word with your keyword but describe a completely different product or category. A keyword like "accounting software" could trigger queries about "accounting software for personal use" or "accounting software open source"—queries that share the root phrase but represent a different product category or buyer intent than your campaign targets.

Geography or language mismatches: If your campaign targets a specific region, look for search terms that suggest a user is in a different market. Similarly, if your campaigns run in one language, terms in another language appearing in your report are worth reviewing.

When scanning for these patterns, you're not looking for certainty—you're looking for signals. Some terms will be obvious cuts. Others will need more thought, which is exactly why the next step involves categorizing before you act.

If you're reviewing a large Search Terms Report, scanning for these patterns in a spreadsheet can get tedious fast. Keywordme's in-interface view lets you scan these patterns directly inside the Search Terms Report without exporting anything, which keeps the process moving when you're working through a long list of terms.

Step 4: Trace Bad Terms Back to Their Triggering Keywords

Identifying a bad search term is useful. Knowing which of your keywords caused it to trigger is more useful, because that's what tells you whether the fix is a negative keyword, a match type change, or both.

In the Search Terms Report, look at the Match type and Added/Excluded columns. These columns show you which of your keywords triggered each search term and how it was matched. This is the connection most guides skip, and it's one of the most valuable pieces of information in the report.

Broad match keywords are the most common source of irrelevant search terms. A single broad match keyword can trigger hundreds of unrelated queries because Google's matching algorithm interprets broad match very liberally, factoring in user context, search history, and related topics. If you're seeing a lot of bad terms, there's a good chance one or two broad match keywords are responsible for most of them.

Phrase match can also produce mismatches, particularly when your phrase appears inside a longer query that has different intent. The phrase "accounting software" in phrase match could trigger "best accounting software for college students"—a query that contains your phrase but targets an audience you may not serve.

If one keyword is generating a disproportionate number of bad search terms, you have a few options: tighten its match type, add negative keywords to block the specific bad terms, or pause the keyword entirely if it's consistently driving irrelevant traffic. Often the right answer is a combination of the first two.

Understanding when to use broad match versus exact match and why broad match brings bad traffic can help you make a more informed decision about whether to tighten match types across your campaigns, not just fix individual terms.

Step 5: Categorize Each Bad Term Before You Act

This is the step most guides skip. They go straight from "here are bad terms" to "add them as negatives." But acting without categorizing first leads to over-exclusion, inconsistent negative keyword lists, and decisions you'll regret when a campaign's reach shrinks unexpectedly.

Sort your flagged terms into three buckets before touching anything.

Bucket 1: Definitely exclude. These are terms with clear intent mismatch and zero relevance to your offer. No amount of additional data is going to make "free DIY tutorial" convert for a paid software product. Add these to your exclusion list with confidence.

Bucket 2: Monitor. These terms have low data volume, or they're ambiguous enough that you're not sure yet. Put them on a watch list and revisit them in your next review cycle with more data. Don't exclude preemptively just because a term looks suspicious.

Bucket 3: Investigate further. Sometimes a surprising search term reveals a new audience segment or a product angle you hadn't considered. Before excluding it, ask whether it points to a real opportunity. If it does, it might belong in a separate campaign or ad group rather than on your negative list.

For terms in Bucket 1, you also need to decide the right level for the negative keyword.

Account-level negative lists are the right choice for terms that should never trigger any ad across your entire account. "Free," "jobs," "DIY," and similar terms often belong here if your business model doesn't serve those queries at all.

Campaign-level negatives work well when a term is irrelevant to a specific campaign but might be valid elsewhere in the account.

Ad group-level negatives are the most surgical option. Use them when a term is irrelevant to one ad group but perfectly fine for another within the same campaign.

One practical habit worth building: keep a running log of excluded terms. It prevents you from accidentally re-adding a search term as a positive keyword later, which is an easy mistake to make when building out new keyword lists.

Step 6: Add Negatives and Apply Match Types in One Pass

With your terms categorized, you're ready to act. The goal here is to do everything in a single pass so you're not bouncing between reports and losing your place.

For confirmed bad terms, add them as negative keywords at the appropriate level you determined in Step 5. When choosing the match type for your negatives, use exact match negatives (written in brackets, like [free accounting homework help]) for specific bad terms you've identified. Use phrase match negatives (written in quotes, like "free accounting") for broader patterns you want to block across multiple variations.

Broad match negatives exist but should be used carefully—they can inadvertently block queries you actually want. In most cases, exact and phrase match negatives give you more control.

At the same time, review the search terms that performed well during your audit. Terms with strong conversion data are candidates to add as exact or phrase match positive keywords. Promoting a high-performing search term to a keyword gives you direct control over bidding for that query, rather than leaving it to be triggered incidentally by a broader keyword.

Applying tighter match types to your best-performing search terms also reduces the chance of future irrelevant triggers. The tighter your match types on proven performers, the less work you'll have to do in future audits. For a deeper look at this decision, the guide on when to apply match types in Google Ads covers the tradeoffs in detail.

If you're doing this manually in Google Ads, this step involves switching between the Search Terms Report, the negative keyword tool, and the keyword editor—which adds friction and increases the chance of errors. Keywordme handles this entire step inside the Search Terms Report. You can add negatives, promote search terms to positive keywords, and apply match types with one-click actions, without leaving the interface or opening a spreadsheet. For a more detailed look at negative keyword workflows, the guide on the best way to add negative keywords in Google Ads is worth reading alongside this one.

When you've finished, your account should have a cleaner negative keyword list, a set of newly promoted positive keywords, and tighter match types on your top performers. That's a meaningful improvement in one session.

Make This a Weekly Habit, Not a One-Time Fix

Running through this process once will improve your campaigns. Running through it every week will compound those improvements over time.

Google's matching behavior evolves continuously, and new irrelevant search terms appear regularly—especially after budget increases, match type changes, or when Google rolls out updates to how it interprets queries. A one-time audit doesn't protect you from what triggers next month.

A practical cadence: review the Search Terms Report weekly for active campaigns. After any significant budget increase or match type change, run an audit within a few days rather than waiting for your next scheduled review.

Here's a quick checklist to keep the process consistent:

1. Open the Search Terms Report (Campaigns > Search keywords > Search terms)

2. Set a 30-day date range (or 60–90 days for lower-traffic campaigns)

3. Sort by cost descending

4. Flag zero-conversion spend above your threshold

5. Identify intent mismatch patterns (informational, audience, product)

6. Check which keywords are triggering the bad terms

7. Categorize: definitely exclude, monitor, or investigate

8. Add negatives at the right level and promote high-intent terms to keywords

Over time, a clean negative keyword list compounds. Fewer irrelevant clicks means better CTR across your campaigns. Better CTR contributes to stronger Quality Scores. Stronger Quality Scores can lead to lower CPCs. The work you do in each weekly audit builds on the last one.

Start your free 7-day trial and run your first search term audit directly inside Google Ads. No spreadsheets, no tab-switching—just faster decisions on what to cut and what to keep. After the trial, it's $12 per month per user.