Google Ads Search Terms Report: How to Analyze It and Cut Wasted Spend

When I take over a Google Ads account, the first screen I open is not the campaign overview. It is the search terms report, because only this screen shows where the budget actually went. In this guide I walk you through where the report lives, which columns matter, why some queries stay hidden, how to add negatives and how n-gram analysis turns thousands of rows into a few clear decisions.

What is the search terms report in Google Ads?

The search terms report is a Google Ads report that lists the real queries people typed before your ad appeared. For each query you see the keyword that matched it, the match type, and its impressions, clicks, cost and conversions. In short, it shows which intent your money actually bought, not which intent you planned to buy.

Your keyword list is a statement of intent. The report, in contrast, is the reality check. The gap between the two often explains more about account performance than bids, ad copy or landing pages.

Google describes the report as a view of how your ads performed when actual searches on the Search Network triggered them. You can read the official definition on the Google Ads Help page about the search terms report.

In practice, this distinction matters most when a client tells me, "the ads run, but the phone stays quiet." The keyword list looks perfect on paper. Then we open the report and find a large share of spend going to queries that never had a chance to convert. The problem was not the ad; it was the matching.

How is a search term different from a keyword?

A keyword is the phrase you add to your account. A search term is the exact phrase a person types into Google. For example, the keyword "office furniture" can match "used office furniture", "office furniture factory jobs" or "cheap office chair near me". Each of those queries carries a very different intent.

The gap also grows with broad match. Google connects your keyword to queries it considers related in meaning, so paying for intent you never listed is completely normal. That is also why broad match needs a stronger review routine than exact match.

Put simply, a keyword describes where you aim, and a search term shows where you landed. If you want to choose better targets in the first place, my guide on how to find keywords that drive sales covers that side. The report then audits the result of those choices.

There is also a time dimension. Google's matching systems keep learning. A keyword that looked clean last month can start matching a new family of queries this month. So the report works best as a habit, not as a one-off cleanup.

Where do you find the search terms report in Google Ads?

In the current interface the path is short. Open Campaigns in the left menu, then go to Insights and reports and choose Search terms. You can view the same screen at account, campaign or ad group level.

Once the screen is open, I recommend three quick settings:

• Set the date range to at least 30 days; short ranges hide low volume queries.
• Add the "Keyword" column from the column menu under attributes; it stays hidden by default.
• Sort by cost first, because the most expensive terms deserve the first look.

In practice, menu labels can differ slightly by interface language and account type. Still, the logic stays the same: you go into the reporting area within campaigns and pick search terms. If you want a broader health check first, the Google Ads audit tool gives you a quick starting point.

One more tip: save your filters. For example, build a filter for "cost above a set amount and zero conversions" once. Then every review opens with the same view in one click, and no costly row slips through.

Which columns should you look at first?

You can switch on dozens of columns. However, only a handful drive real decisions. The table below maps each useful column to the question it answers.

Click through rate is a useful supporting signal. On its own, though, it can mislead you. A high rate may simply mean a curious audience with no plan to buy.

I also add conversion value in e-commerce accounts. Two terms can bring the same number of orders while one brings far larger baskets. If you only count conversions, you miss that difference. In other words, your business question decides which columns you need.

What does the match type column tell you?

This column shows how closely the search term relates to your keyword. You will see exact match, phrase match and broad match labels. You will also meet "close variant", which means Google treated the query as having the same meaning as your keyword.

My practical reading goes like this. Exact match rows rarely cause trouble. Phrase match keeps the meaning of the keyword, yet words before or after it can change the intent. Broad match brings the widest variety, so broad match ad groups need the most frequent review.

If the same query shows up under several match types, your keywords may compete with each other. To test how each match type behaves, try the keyword match type tool.

Watch out for one trap. The match type label describes closeness, not quality. An exact match term can still burn money without a single conversion. That is why you read match type together with cost and conversion columns, never alone.

Why are some search terms missing from the report?

Google leaves out terms that do not reach enough query volume, in line with its data privacy standards. As a result, the rows in your table rarely add up to the full campaign cost. The difference belongs to low volume queries you cannot see one by one.

In long tail industries this hidden share can grow large. Spare parts, legal services and healthcare, for instance, attract thousands of unique phrasings. So reading visible rows gives you only part of the picture.

I use two ways to interpret the hidden part. First, search terms insights group queries into themes, including an "other queries" bucket, without exposing individual searches. Second, I extract recurring word patterns from visible rows with n-gram analysis and cover those patterns with negatives. That way, the same negatives also filter many hidden queries.

During audits I always measure this gap. I add up the cost of visible rows and compare it with the campaign total. When the hidden share is very high, match types are often too loose, because broad match opens the door to more unique queries.

How do you see search terms in Performance Max?

For a long time Performance Max felt like a closed box. Today you can review search terms and theme level search terms insights for this campaign type too. Google notes that this data helps you understand which search terms led to conversions.

Negatives changed as well, so the old workarounds matter less. According to Google's page on negative keywords in Performance Max, you can add campaign level negatives, and they apply to Search and Shopping inventory only. The same page also states that negative keyword lists are not yet available for this campaign type.

Keep one more limit in mind. Search term data covers the search side of Performance Max. Placements on Display, YouTube or Gmail do not appear in this table. So judging a Performance Max campaign only by its search terms gives you an incomplete view.

For these reasons I manage the account level negative list with extra care when an account runs Performance Max. That list applies automatically to all eligible Search and Shopping inventory.

How should you start a search terms report analysis?

Reading the report row by row works in week one. Then the account grows and the method breaks. That is why I run every analysis in the same order:

1. Pick the scope: start with one campaign and a range of 30 to 90 days.
2. Sort by cost: a small number of terms usually takes most of the budget.
3. Isolate non converting spend: flag terms above a cost threshold with zero conversions.
4. Label intent: tag each term as buyer, researcher or irrelevant.
5. Find patterns: use n-grams to spot recurring words instead of single rows.
6. Log every action: note each negative and new keyword with a date.

Set your threshold relative to the account's average cost per conversion. For example, a term that spent twice that average without a result clearly deserves a closer look. If you do not know your average conversion rate, the conversion rate calculator gives it to you in seconds.

At the end you should hold two lists: negative candidates and new keyword candidates. Review both before you apply anything. Above all, check that no brand or product name slipped into the negative list by mistake.

Which search terms should become negative keywords?

Not every non converting term deserves a negative. Some terms, for example, simply need more data. You decide by reading intent and numbers together.

These groups end up on a negative list in almost every account I manage:

• Job and career intent: "jobs", "salary", "internship", "hiring".
• Free and do it yourself intent: "free", "free download", "how to make".
• Products or services you do not sell: used, rental or a different model.
• Regions and languages you do not serve.
• Competitor names, unless you run a deliberate competitor campaign.

On the other hand, I never exclude words like "price", "best" or "reviews" by reflex. In most industries they signal research that sits close to a purchase. I check the data first and decide after that.

My test question is simple: can the person who typed this term buy my offer at my price? If the answer is clearly no, the term becomes a negative. If the answer is unclear, I give it more time. This way a hasty decision does not cut future demand instead of waste.

How do negative match types work?

Negative keywords behave differently from regular keywords. Google's page about negative keywords states it clearly: negatives do not match close variants or other expansions.

Here is the short version of the three types. With a negative broad match, your ad will not show if the search contains all the negative terms, in any order. For negative phrase match, the ad stops when the terms appear in the same order. With negative exact match, only the same phrase without extra words blocks the ad.

The practical consequence matters. You need to add singular and plural forms, synonyms and common spellings yourself. For example, if you exclude "job", think about "jobs" too. Google still handles casing and some misspellings on its own.

Choose the type by the nature of the pattern. For a phrase like "job openings", which is irrelevant in any context, phrase match is safe. When you want to block one specific query only, exact match fits better. Single word broad negatives are the most powerful option and also the riskiest.

What are negative keyword lists for?

Lists save you from adding the same negatives to every campaign by hand. According to Google's page on negative keyword lists, you can create up to 20 lists per account, with up to 5,000 negatives in each list.

In addition, account settings hold a single account level negative list with a limit of 1,000 negatives. That list applies automatically to all eligible Search and Shopping inventory.

I organize lists by theme:

• Careers and job seekers.
• Free, education and do it yourself.
• Out of scope products.
• Geography and language.

When you launch a new campaign, you attach the four lists and start with clean traffic on day one. Review the lists at least twice a year, though. If you add a new product line, a word you excluded long ago might now bring sales, and an old list would silently block it.

What is n-gram analysis and why does it beat reading rows?

N-gram analysis splits search terms into word patterns and sums cost and conversions for each pattern. A single word is a 1-gram, a two word pattern is a 2-gram, and a three word pattern is a 3-gram.

Here is why it works. The word "free" might appear inside a hundred different search terms. Each one gets a few clicks and never stands out. N-gram analysis, however, rolls those hundred rows into one line. Suddenly you see that "free" spent real budget and brought zero conversions.

N-grams also give you indirect protection against hidden queries. When you find a bad pattern in visible terms and exclude it, you also filter hidden queries that contain the same pattern. In short, row by row reading shows you the trees, and n-grams show you the forest.

Start with single words, but do not stop there. For instance, "course" alone might look irrelevant, while "course prices" converts well in the same account. Two and three word views reveal the nuance a single word hides.

How do you read the report with an n-gram tool?

Doing this by hand in a spreadsheet, however, takes hours. That is why we built a free search terms n-gram analyzer on this site. The workflow looks like this:

1. Open the search terms screen in Google Ads and choose your date range.
2. Download the table and make sure it includes search term, cost, clicks and conversions.
3. Paste the data into the tool or upload the file.
4. Sort the 1-gram results by cost first.
5. Mark expensive patterns without conversions, then switch to 2-gram and 3-gram views.
6. Move the results to a negative candidate list and check each one for intent once more.

Do not skip the last step. For example, "rental" is waste for a company that only sells equipment. For a company that also rents, however, it may be the main source of revenue. The tool shows patterns; you make the call because you know the business.

Save each export as well. In the next review you compare pattern costs and measure the effect of your negatives. If a pattern that topped the 1-gram list last month has dropped off, your action worked.

How do you turn winning search terms into keywords?

The report is not only a cleanup tool. The same screen shows terms that convert but do not exist as keywords yet. These are often the most valuable findings in the whole analysis.

When you find a converting term, consider adding it as a separate keyword in exact or phrase match. Then you control its bid on its own and write ad copy for that exact query. Google's help page notes that you cannot add keywords directly from the report, so you add them from the keywords screen instead.

If a strong term carries a different intent, a new ad group is the cleaner choice. Also make sure the landing page answers that query. For the logic of assigning keywords to pages, see my guide on how to do keyword mapping.

You can also bring winning terms into your ad copy. People respond when they see their own words in a headline. Because relevance improves, click through rate often improves with it.

How often should you review the search terms report?

First of all, frequency depends on spend and campaign age. In a new campaign you look often during the first two weeks, because leaks peak early. Mature campaigns need a calmer but steady rhythm.

As budget grows, you tighten the rhythm. Consistency matters more than frequency, though. Put a fixed review day in your calendar, otherwise busy weeks push the report aside and leaks pile up. For budget planning across campaigns, see how to set a Google Ads budget.

What are the most common analysis mistakes?

I see the same mistakes again and again in account audits. The most common ones:

• Too short a date range: seven days of data turns coincidence into a false pattern.
• Over excluding single words: a broad negative like "price" also blocks ready buyers.
• No change log: without notes, you cannot explain a traffic drop later.
• Broken conversion tracking: faulty tracking makes good terms look bad.
• Only hunting for waste: you forget to promote winning terms.

The second mistake causes the most damage. As Google itself warns, too many negatives can mean your ads reach fewer customers. So before each new negative, ask one question: has this pattern ever converted?

Another frequent error is judging terms only at account level. The same term can fail in one campaign and succeed in another. Check where it causes trouble, then add the negative only to that campaign if needed.

How do search term insights help your SEO?

Search terms show the raw language people use when they look for you. On the SEO side, that language is one of the most reliable inputs for content planning. It is not a guess; it is a real query, and it comes with conversion data attached.

For instance, if a question pattern keeps appearing, you can turn it into an FAQ entry or a blog post. A service phrase that converts well becomes a candidate for your service page title. So your paid search budget also funds free research for organic growth.

It works the other way too. If you already rank strongly for some queries organically, you can reconsider ad spend on those terms. Brand safety and competitor pressure still count, of course. My team and I run both channels together; for the organic side, see SEO consulting.

Should B2B accounts read the report differently?

Yes. B2B searches have low volume, and a single conversion can carry high value. That is why you set a more patient non converting threshold.

Intent words also differ. Terms like "wholesale", "supplier", "manufacturer" and "quote" are usually valuable. On the other hand, "retail", "single unit" and patterns that point to private buyers are often negative candidates.

Conversion definitions also matter even more here. A form fill does not always equal a sales opportunity. If possible, feed lead quality from your sales team back into the account. Then you judge search terms by real pipeline, not by form count. I covered B2B setup in detail in Google Ads search campaigns for B2B.

How do you show the impact of your search terms work?

Proving the effect of your cleanup matters as much as the cleanup itself. I track three indicators each month: the share of spend going to non converting terms, the contribution of newly added winning keywords, and the hidden term share. Together they show the concrete result of search terms report work.

If the non converting share falls month over month, your negative strategy works. If conversions fall with it, however, you may have been too aggressive. For a wider view on reading performance data, see how to read a digital marketing report.

How do my team and I run search terms analysis?

In the accounts we manage, search terms analysis is never a one-off cleanup. We build themed negative lists for every account, repeat n-gram analysis on a fixed schedule and log each change with its date.

I own the strategy and the responsibility for results, while experienced specialists on my team handle execution. This gives you a review rhythm that is both fast and consistent. If you want to know how your account looks from this angle, reach us through the Google Ads management page.

To sum up, an account that reads its search terms regularly earns cleaner traffic over time. As a result, you get more qualified demand from the same budget. Every review also teaches you a little more about your customers and their language, and that knowledge pays off in sales and content as well.