What's the Best Way to Structure Campaigns and Ad Groups? A Practical Guide for Google Ads

**TL;DR:** The best way to structure Google Ads campaigns and ad groups is to organize campaigns around what needs separate control—like budget, location, or bidding strategy—and build ad groups around tightly themed keyword clusters that can share the same ad copy. Campaigns typically align with product lines, geographic markets, or funnel stages (branded vs. non-branded), while ad groups contain 10-20 closely related keywords that trigger the same ideal message. The goal is balance: granular enough for relevance and control, but consolidated enough to actually manage without losing your mind.

If you've ever stared at a Google Ads account wondering whether to split that ad group into three separate ones or just throw everything into a single campaign, you're not alone. Most advertisers face this tension constantly—too granular and you're drowning in tabs and spreadsheets, too broad and you're watching budget evaporate on irrelevant clicks.

Here's what usually happens: someone builds an account structure based on a template they found online, runs it for three months, realizes it doesn't match how their business actually works, then spends weeks restructuring everything while campaigns tank. Sound familiar?

This guide walks through a practical framework you can apply immediately, whether you're managing your first campaign or your fiftieth client account. We'll cover what belongs at the campaign level, how to build ad groups that actually improve Quality Score, and real examples that work across different business models.

The Campaign-Level Decision: What Should Each Campaign Represent?

Think of campaigns as your control centers. Every setting you apply at the campaign level—budget, location targeting, bid strategy, ad schedule, network selection—applies to everything underneath it. This is where most structure decisions should start.

The fundamental question is: what needs separate control in your business?

In most accounts I audit, campaigns get structured around one of these frameworks. Product or service lines work well when different offerings have different margins or conversion rates—you wouldn't want your high-margin consulting services sharing a budget with your low-margin downloadable guides. Geographic markets make sense when you serve distinct regions with different budgets or competitive landscapes. A local service business might run separate campaigns for each city, while a national retailer might split by state or metro area.

Funnel stage separation is probably the most common approach I see working well. Branded campaigns (searches including your company name) typically convert at much higher rates and lower costs than non-branded generic terms. Keeping these separate lets you allocate budget appropriately and prevents your brand traffic from subsidizing expensive competitive keywords.

Some advertisers structure by match type—broad match in one campaign, phrase and exact in another. This approach has fallen out of favor as Google's match type behavior has changed, but it still makes sense when you want to test different bidding strategies or budgets based on query expansion tolerance. Understanding how keyword match types work is essential before deciding on this structure.

The mistake most agencies make is creating too many campaigns too early. Every campaign you add creates another budget pool to monitor, another set of settings to maintain, another performance report to review. The budget threshold principle helps here: if a product line or market can't support at least $300-500 per month in spend, it probably doesn't need its own campaign yet. Combine smaller categories until they hit that threshold.

Performance isolation is the other deciding factor. If you need to measure ROI separately—say, comparing performance between two product lines for strategic planning—separate campaigns make that analysis cleaner. But if you're just splitting campaigns because it "feels" more organized, you're probably creating work without performance gains.

What usually happens in practice is you start with broader campaigns, then split as budget and complexity grow. A new account might begin with just two campaigns: branded and non-branded. Six months later, when you've identified which product categories drive the most value, you split those out. This evolutionary approach beats trying to build the perfect structure on day one.

Ad Group Architecture: The Tightly Themed Keyword Cluster

Here's the single theme rule that solves most ad group structure questions: all keywords in an ad group should be able to trigger the same ideal ad without sounding weird or irrelevant.

Let me show you what this looks like in practice. Say you sell project management software. You might have one ad group for keywords like "project management software," "project management tools," "project management platform," and "project management system." All of these can share an ad that talks about comprehensive project management solutions.

But "free project management software" doesn't belong in that group—it signals different intent and needs different ad copy highlighting your free tier. And "project management software for construction" definitely needs its own ad group with industry-specific messaging.

The practical range I recommend is 10-20 tightly related keywords per ad group. Fewer than 10 and you're probably over-segmenting, creating management overhead without meaningful performance differences. More than 20 and you're likely mixing themes that would perform better separated. Following best practices for keyword clustering helps you find this balance.

In most accounts I manage, the sweet spot is around 15 keywords per ad group. This gives you enough query volume to generate meaningful data while keeping themes coherent enough that your ads stay relevant.

Naming conventions matter more than most advertisers realize, especially when you're scaling beyond a handful of ad groups. I use a hierarchical system: Campaign Name | Ad Group Theme | Match Type (if relevant). So you might see "Software - Non-Branded | Project Management Tools | Phrase" as an ad group name.

This naming structure lets you instantly understand what's in an ad group when you're looking at a performance report six months later. It also makes bulk editing and filtering dramatically easier—you can pull all "Project Management" ad groups across campaigns with a simple filter.

The mistake I see most often is using vague names like "Ad Group 1" or overly creative names that made sense when you created them but mean nothing three months later. Your naming system should work at scale—what makes sense for 5 campaigns should still make sense at 50.

Another practical consideration: resist the urge to create separate ad groups for every possible keyword variation. "Project management software" and "project management softwares" (with the typo) don't need separate ad groups. Google's close variant matching handles this. Focus your segmentation on genuine intent differences, not minor phrasing variations.

Real-World Structure Examples for Different Business Types

Let's look at how this actually plays out across different business models, because the theory only helps when you can see it applied.

E-commerce Example: An online retailer selling outdoor gear might structure campaigns by product category—one for tents, one for backpacks, one for sleeping bags. Within the backpacks campaign, ad groups would split by specific product types and buying signals. You'd have separate ad groups for "hiking backpacks," "travel backpacks," "laptop backpacks," and "kids backpacks"—each with their own product-specific ads and landing pages. A separate branded campaign would capture searches for the company name plus product terms.

What usually happens in e-commerce accounts is advertisers create ad groups that mirror their website navigation too literally. Just because you have a "Backpacks > Hiking > Daypacks" category structure on your site doesn't mean you need that same hierarchy in Google Ads. Structure around how people actually search, not how your site is organized.

The shopping intent layer matters too. An ad group for "best hiking backpacks" (comparison/research intent) should be separate from "hiking backpack sale" (transaction intent) even though both relate to the same product category. The ads and landing pages need to match where the searcher is in their decision process.

Service Business Example: A multi-location dental practice might organize campaigns by location first—one campaign per office location since each has its own budget and service area. Within each location campaign, ad groups would split by service type: "teeth whitening," "dental implants," "emergency dentist," "cosmetic dentistry." Each ad group contains keywords specific to that service plus location modifiers.

The buyer intent signal becomes crucial here. Someone searching "dental implants cost" is in research mode and needs educational content, while "dental implants near me" is ready to book. These belong in separate ad groups with different ad copy and landing pages, even though they're both about the same service.

In service accounts, I often see the mistake of combining all services into one ad group per location. This creates ads that try to mention everything—"We offer teeth whitening, implants, cleanings, and more!"—which sounds generic and doesn't address the specific need someone searched for.

Agency/Multi-Client Perspective: When you're managing dozens of accounts, templated structures save massive amounts of time. I use a core template that works for most clients: campaigns split by branded vs. non-branded, then by major product/service categories. Ad groups follow the 10-20 keyword rule with consistent naming conventions across all accounts. Using software for managing multiple ad accounts makes this scalable.

The template approach doesn't mean every account looks identical—you adapt based on client specifics—but having a starting framework means you're not reinventing structure for every new client. It also makes it easier to train team members and maintain consistency in how you approach optimization.

Common Structuring Mistakes That Drain Your Budget

The "one giant ad group" trap is probably the most expensive mistake I see in new accounts. Someone creates a campaign, dumps 200 keywords into a single ad group, writes one generic ad, and wonders why their Quality Score sits at 4/10 and their CPCs are double the industry average.

Here's what happens: Google's auction system rewards relevance. When someone searches "emergency plumber Boston" and your ad says "Plumbing Services - All Types - Call Now," you're competing against ads that say "Emergency Plumber in Boston - 24/7 Response." The more specific ad wins, gets the higher Quality Score, and pays less per click. By mixing emergency plumbing keywords with general plumbing keywords in one ad group, you've made it impossible to write relevant ads for either.

The flip side—over-segmentation—creates different problems. I've audited accounts with 300 ad groups, each containing 2-3 keywords, where the advertiser spent more time managing structure than actually optimizing performance. When ad groups are too granular, you spread your data too thin. It takes months to accumulate enough clicks and conversions to make meaningful optimization decisions.

The practical test I use: if two ad groups would have essentially identical ads and landing pages, they should probably be combined. Splitting "plumber Boston" and "Boston plumber" into separate ad groups doesn't add value—the search intent is identical.

Another common mistake is building structure in a vacuum, then never adjusting it based on actual search behavior. Your search terms report is telling you exactly how people are finding your ads. If you're seeing lots of queries about a specific sub-topic you didn't anticipate, that's a signal to create a dedicated ad group for it. Understanding search term optimization helps you leverage this data effectively.

What usually happens is advertisers set up their structure, run it for months, and only look at search terms when performance tanks. By then, you've already wasted budget on irrelevant clicks that a better structure would have prevented.

Ignoring negative keyword strategy during structure planning creates similar waste. Each ad group should have a clear negative keyword list that prevents it from triggering on searches better suited to other ad groups. Without this, your ad groups compete with each other, showing the wrong ad for many searches. Learning how to structure a negative keyword strategy is essential for preventing this internal competition.

Maintaining and Optimizing Your Structure Over Time

Structure isn't a set-it-and-forget-it decision. The best-performing accounts I manage get quarterly structure audits where we look for signals that things need adjustment.

Your search terms report is the primary diagnostic tool. Pull the last 30-60 days of search term data and look for patterns. Are you seeing clusters of related queries that don't fit cleanly into any existing ad group? That's a signal to create a new one. Are multiple ad groups triggering on similar queries? Time to tighten up your negative keyword strategy or consolidate those groups. Knowing where to find negative keywords accelerates this process.

The specific things I look for during quarterly audits: ad groups with fewer than 50 impressions per month (probably too granular or targeting something nobody searches), ad groups with CTRs significantly below campaign average (likely a relevance mismatch between keywords and ads), and ad groups with high impression share but low conversion rates (attracting the wrong traffic).

When to restructure completely versus making incremental adjustments is a judgment call. If your fundamental business model has changed—you've added new product lines, entered new markets, or shifted pricing strategy—a full restructure might make sense. But if you're just seeing some performance variations, targeted adjustments usually work better and cause less disruption.

The rise of Smart Bidding and Responsive Search Ads has changed some structure thinking. These automation features work better with more data, which sometimes argues for broader ad groups. But the core principle of thematic coherence still matters. A Responsive Search Ad can test different headline and description combinations, but it still needs all its possible variations to be relevant to the keywords in that ad group. Understanding how to choose the right bid strategy helps you make these decisions.

In most accounts I audit, the balance point is slightly broader ad groups than we used five years ago—maybe 15-20 keywords instead of 5-10—but still maintaining clear thematic boundaries. You're giving the algorithm room to optimize while keeping human-driven strategic structure in place.

The maintenance cadence that works for most advertisers: weekly search term reviews to add negatives and identify new keyword opportunities, monthly performance reviews to spot ad groups that need attention, quarterly structure audits to assess whether your overall architecture still matches your business reality.

Putting It All Together: Your Structure Checklist

When you're building or evaluating account structure, use this decision framework. At the campaign level, ask: does this need separate budget control, different geographic targeting, or a distinct bidding strategy? If yes to any, it probably deserves its own campaign. If no to all, consider combining it with a related campaign. Understanding the difference between campaign-level and ad group-level settings clarifies these decisions.

At the ad group level, apply the single theme test: can all these keywords trigger the same ad without sounding irrelevant? If yes, they can share an ad group. If no, split them based on intent differences or topic variations.

Signs your current structure is working: Quality Scores averaging 7+ across most ad groups, CTRs meeting or exceeding industry benchmarks for your business type, conversion rates that justify your CPC, and manageable day-to-day optimization workload. You should be spending more time optimizing bids and testing ads than reorganizing structure.

Signs your structure needs attention: Quality Scores stuck below 5, declining CTRs even with good ad copy, high impression share but low conversion volume, or spending hours every week just trying to understand what's happening in your account. These indicate structural problems that tactical optimization can't fix. Following best practices for managing Google Ads campaigns helps you identify and address these issues early.

The next steps for implementation depend on where you're starting. If you're building a new account, start with the minimum viable structure—probably 2-4 campaigns and 10-20 ad groups total. Run it for 30-60 days, collect search term data, then refine based on actual performance.

If you're restructuring an existing account, don't try to fix everything at once. Identify the highest-spend campaigns or the ones with the worst performance metrics, restructure those first, measure the impact, then move to the next priority area.

Moving Forward with Smarter Campaign Architecture

The best campaign and ad group structure is the one you can actually manage and optimize consistently. Start with a framework that matches your business logic—whether that's product lines, geographic markets, or funnel stages. Keep ad groups tightly themed around 10-20 related keywords that can share relevant ad copy. Then let performance data guide your refinements.

What separates accounts that scale profitably from those that waste budget is this ongoing optimization discipline. Structure creates the foundation, but the real performance gains come from continuously analyzing search terms, testing ad variations, and adjusting based on what the data tells you.

The most successful advertisers I work with treat structure as a living system. They build intentionally, measure constantly, and adjust strategically. They don't chase the perfect structure—they build one that's good enough to start, then make it better through iteration.

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