Search Term Analysis for Agencies: How to Manage Client Campaigns at Scale

If you're running PPC for multiple clients, you already know the feeling. Monday morning, you open five different Google Ads accounts, and each one has a search terms report packed with queries you've never seen before. Some are obviously irrelevant. Some look promising. Most are somewhere in between. And you have to make smart decisions about all of them—fast—before the week's budget bleeds out on the wrong clicks.

This is the reality of search term analysis for agencies. It's not glamorous work, but it's where a meaningful chunk of client budget is either protected or wasted. Done poorly, it's a weekly grind that never quite catches everything. Done well, it's one of the highest-leverage activities in your entire PPC operation—surfacing wasted spend before it compounds and uncovering keyword opportunities your competitors haven't found yet.

This guide is written for practitioners who already understand Google Ads fundamentals. You know what the search terms report is. You've added negatives before. What you need is a scalable, repeatable process for doing this work consistently across many accounts without your team burning out or important signals slipping through the cracks. That's exactly what we're going to build here.

Search Terms vs. Keywords: Why the Distinction Matters for Agency Work

Let's start with the terminology, because this distinction causes real problems when it gets blurred—especially at agency scale.

A keyword is what you add to a Google Ads campaign. It's the trigger you set, the signal you give Google to indicate what searches you want to compete for. A search term is the actual query a user typed into Google that caused your ad to show. These two things are often very different, and the gap between them is where budget leaks happen.

Match type behavior is what drives this gap. With exact match, the relationship between keyword and search term is tight—Google will show your ad for queries that are identical or very close in meaning to your keyword. With phrase match, that relationship loosens. With broad match, Google has significant latitude to match your keyword against queries that share what it considers to be the same intent, which can mean queries that look quite different from your original keyword on the surface.

For a solo advertiser managing one account, a broad match keyword that pulls in some irrelevant traffic is a manageable problem. For an agency managing twenty accounts, each with broad match keywords running across multiple campaigns, the same issue is multiplied across every account simultaneously. A keyword that's slightly too broad in one campaign might be pulling in irrelevant traffic across dozens of ad groups before anyone notices.

There's another agency-specific risk here. When a misunderstanding about match type behavior goes unchecked in one client account, it often gets replicated. If a team member builds a campaign structure for Client A using broad match in a way that generates a lot of irrelevant search terms, and that structure becomes the template for Client B and Client C, you've scaled the problem. The search terms report is where you catch this—but only if you're reviewing it with enough regularity and enough attention to what the data is telling you about your keyword and match type decisions, not just about individual irrelevant queries.

The practical implication: when you're reviewing search terms, you're not just looking for bad queries to exclude. You're auditing the relationship between your keyword strategy and what Google is actually doing with it. That's a more useful frame, and it leads to better decisions.

Reading the Report: Signals Worth Acting On

The search terms report contains three categories of signals that matter for agency work. Knowing what you're looking for before you open the report makes the analysis faster and the outputs more consistent.

Waste signals are the most obvious category, but they're worth defining precisely. A high-spend, zero-conversion search term is the clearest example—money is going out, nothing is coming back. But waste signals also include branded competitor terms you're not intentionally targeting (you're paying for clicks from users who were looking for a competitor by name), irrelevant industry verticals (a B2B software client showing up for consumer queries), and audience segments that clearly don't match the client's customer profile. Each of these warrants a negative keyword addition, but the right level of application—ad group, campaign, or shared list—depends on how broadly the irrelevant term is appearing across the account.

Opportunity signals are where the real upside lives. When a search term has generated conversions but isn't yet in your keyword list as an exact or phrase match keyword, you have a proven query that you're not fully controlling. Adding it as a targeted keyword lets you set a specific bid, write more relevant ad copy, and direct it to the most appropriate landing page. These converting search terms are often the best source of new high-intent keywords because they're not hypothetical—they've already demonstrated performance in your specific account context.

Structural signals are the most underused category, and they're particularly valuable for agency practitioners. A structural signal is when a cluster of irrelevant or off-target search terms all trace back to the same keyword. This isn't a random collection of bad queries—it's a pattern that tells you something about the keyword itself. The keyword may be too broad for the campaign's intent, the match type may be too permissive for the competitive environment, or the keyword may be attracting a different audience segment than intended. When you see this pattern, the right response isn't just adding more negatives. It's reconsidering the keyword or its match type. Negatives treat the symptom; a structural fix treats the cause.

One important note on the report itself: Google does not show every search term that triggered an ad. Queries with very low volume are withheld for privacy reasons, which means the report is a useful but incomplete picture. This doesn't change the analysis process, but it's worth keeping in mind when evaluating coverage.

Building a Repeatable Process Across Multiple Client Accounts

The biggest difference between agencies that do search term analysis well and those that do it inconsistently isn't knowledge—it's process. A clear, documented process is what makes this work scalable across a team and across many accounts.

Review cadence tied to spend, not habit. Not every account needs weekly attention. A client spending a few hundred dollars a month generates far fewer search terms than a client spending several thousand. A practical approach: set weekly reviews for accounts above a spend threshold that makes weekly analysis worthwhile, bi-weekly for mid-tier accounts, and monthly for lower-spend accounts. Adjust the cadence when campaign activity increases—a new campaign launch or a significant budget change is a reason to move to more frequent review temporarily, regardless of where the account normally sits.

Standardize the outputs of every review session. Every time someone on your team reviews a search terms report, three things should come out of it: a list of negative keywords to add (with the appropriate level noted—ad group, campaign, or shared list), a list of search terms to evaluate as new keyword candidates, and any match type adjustments flagged for discussion. This structure keeps reviews focused and ensures that analysis translates into action rather than just observation.

Document decisions per account. This is the piece most agencies skip, and it's the piece that creates the most problems over time. When you add a negative keyword, log it—what the term was, why it was excluded, and at what level. When you decide not to add a search term as a keyword, note the reason. This running record serves two purposes: it prevents the same bad terms from slipping back into the account after a campaign restructure, and it gives new team members the context they need to make consistent decisions without starting from scratch. A simple shared document or a dedicated field in your project management tool works fine. The format matters less than the habit.

With this foundation in place, the analysis itself becomes faster and more consistent. Your team isn't reinventing the approach for each account—they're applying a known process and using account-specific context to make the right calls.

Negative Keywords: Turning Analysis Into Immediate Budget Protection

Negative keywords are the most direct output of search term analysis, and understanding how to apply them correctly across an agency's account portfolio is one of the clearest ways to demonstrate ongoing value to clients.

Google Ads allows you to apply negative keywords at three levels, and choosing the right level matters. Ad group-level negatives are the most surgical option—they block a specific term only within a specific ad group, leaving other ad groups unaffected. This is the right choice when a term is irrelevant in one context but could be legitimate in another part of the same campaign. Campaign-level negatives block a term across all ad groups within a campaign. Use this when a term is clearly irrelevant to the campaign's entire scope. Shared negative keyword lists allow you to apply a set of negatives across multiple campaigns simultaneously, and they can be updated centrally so that any change propagates automatically to every campaign using that list.

For agencies, shared lists are particularly powerful. Once you've built a master exclusion list for a client's industry or business type—competitor brand names, irrelevant audience segments, geographic terms that don't apply—you can apply that list to every campaign in the account and maintain it in one place. When a new irrelevant term surfaces, you add it once and it's excluded everywhere. This is significantly more efficient than managing negatives campaign by campaign, especially as accounts grow in complexity.

Match types for negative keywords are worth understanding carefully, because they behave differently from match types for positive keywords. Negative exact match blocks only queries that match the term exactly (or very closely). Negative phrase match blocks queries that contain the phrase in order. Negative broad match blocks queries that contain all the words in the negative keyword in any order—but it does not use the same broad interpretation that positive broad match does. Choosing the wrong negative match type can either over-block legitimate traffic or fail to catch the irrelevant queries you were trying to exclude. When in doubt, negative phrase match is often a practical middle ground for most exclusions.

One discipline that pays off over time: review your negative keyword lists periodically to check for conflicts. A negative keyword that blocks a term you're actively trying to target with a positive keyword is a common source of unexplained performance drops, and it's easy to introduce when multiple team members are managing the same account.

Turning Search Term Data Into Keyword Strategy

Search term analysis isn't only about exclusion. The same data that surfaces irrelevant queries also surfaces queries that are working—and those are the foundation of a stronger keyword strategy.

The most direct opportunity is converting search terms that are already generating results. When a search term has driven conversions but isn't in your keyword list as an exact or phrase match keyword, you're relying on a broader keyword to capture it, which means you have limited control over the bid, the ad copy, and the landing page experience for that specific query. Adding it as a targeted keyword gives you that control. You can set a bid that reflects its actual value, write ad copy that speaks directly to that query, and route it to the landing page most likely to convert for that intent. This is one of the clearest ways search term analysis feeds directly into campaign performance improvement.

Beyond individual keyword additions, search term clusters can reveal structural opportunities. When you notice a group of related high-performing search terms all being captured by a single broad keyword, that cluster may justify its own dedicated ad group. A tightly themed ad group with its own ad copy and landing page will almost always outperform a generic ad group trying to serve a wide range of queries. The search terms report is essentially showing you where Google's users are finding value—and where your campaign structure has room to meet them more precisely.

Search term data also informs match type decisions at the keyword level. If a phrase match keyword is consistently pulling in high-quality, relevant search terms, that's evidence the keyword is well-calibrated and the current match type is appropriate. If a phrase match keyword is pulling in a wide range of loosely related queries with mixed performance, it may be worth tightening to exact match for the best-performing terms while adding negatives to filter the rest. Conversely, if an exact match keyword has limited reach and the search terms it does trigger are all closely relevant, the data might support testing a phrase match version to capture more volume safely.

The key discipline here is treating search term data as ongoing input to keyword strategy, not just a cleanup task. The best-performing keywords in a mature account are often ones that were first spotted as search terms and then deliberately promoted to targeted keywords based on demonstrated performance.

Speeding Up the Work Without Losing Rigor

Search term analysis is time-intensive by nature. The goal isn't to rush through it—it's to eliminate the parts that don't require judgment so you can spend more time on the parts that do.

Sort by impact, not by default. The Google Ads search terms report, by default, doesn't sort by the metrics that matter most. Before you start reviewing, sort by cost to surface the highest-spend terms first. A $200 search term with zero conversions deserves more attention than twenty $2 terms with the same profile. You can also filter by conversion data to quickly isolate terms that are performing well and haven't been added as keywords yet. This simple step means your analysis time is weighted toward the decisions that have the most effect on client outcomes.

Use bulk editing and shared lists to apply decisions at scale. Once you've decided that a category of terms is irrelevant for a client—say, all queries containing a specific competitor's brand name—you don't need to add each variant individually. Shared negative keyword lists let you apply that decision across all relevant campaigns at once. When you add a new term to the shared list, it's excluded everywhere the list is applied. Similarly, when you identify a batch of new keyword candidates from the search terms report, bulk adding them as exact or phrase match keywords is faster than processing them one at a time.

Work directly in the interface where the data lives. One of the most common sources of friction in search term analysis is the workflow itself: export to spreadsheet, make decisions, go back into Google Ads, apply changes, repeat. Every context switch adds time and introduces the risk of errors in translation. For teams doing this work inside Google Ads, Keywordme's Chrome extension addresses this directly. It lets you take actions—adding negatives, adding positive keywords, applying match types—directly within the search terms report with a single click, without leaving Google Ads or opening a spreadsheet. For agencies processing search terms across multiple accounts, that reduction in workflow friction adds up meaningfully over a week of reviews. It's worth noting that Keywordme doesn't make changes autonomously; you review and approve every action, which keeps human judgment in the loop where it belongs.

The underlying principle across all of these approaches is the same: protect your team's analytical time by automating or streamlining the mechanical parts of the process. The judgment calls—whether a term is truly irrelevant, whether a cluster justifies a new ad group, whether a match type adjustment is safe—those still require an experienced practitioner. Everything else should be as fast as possible.

Putting It All Together

Search term analysis is one of those tasks that's easy to deprioritize when accounts are busy and client requests are coming in from every direction. But it's also one of the tasks where consistent, disciplined execution creates the most compounding value over time. Every irrelevant term you catch and exclude is budget that stays in the account for queries that actually convert. Every converting search term you promote to a targeted keyword is an opportunity to improve performance with more precise bidding and messaging.

For agencies, the stakes are higher because the scale is larger. The same process that protects one client's budget, applied consistently across ten or twenty accounts, has a significant effect on aggregate performance—and on the agency's ability to demonstrate that its ongoing management work is worth the fee.

The core process is straightforward: review on a cadence tied to spend volume, categorize what you find into waste signals, opportunity signals, and structural signals, take action through negatives and keyword additions, and document decisions so the work compounds rather than resets. Build shared lists, standardize your outputs, and use every tool available to reduce the mechanical friction so your team can focus on the decisions that actually require their expertise.

If you're looking to do this work faster without leaving your Google Ads account, Start your free 7-day trial of Keywordme and see how much time your team can reclaim on search term reviews across every client account. After the trial, it's $12 per user per month—a straightforward addition to any agency's optimization workflow.