- Build Search campaigns around service lines first, not geography; fragmenting by city too early starves each campaign of the data it needs to perform.
- Add one "umbrella" campaign for broad category searches that don't map to a single service, paired with educational landing page content.
- Layer Performance Max on top as a single cross-service campaign split by audience segment (e.g., small accounts vs. multi-location accounts), not duplicated by service.
- Launch geographic targeting narrow, starting with the highest-demand sub-region, then widen the same campaigns' location settings in phases as data comes in, rather than targeting the full service area on day one.
- Only split out a specific city or sub-region into its own campaign once it shows enough volume and distinct enough dynamics to justify it.
Most Google Ads accounts are built around a single city or a single service. But a lot of real businesses don't fit that mold. Think of a commercial compliance or maintenance provider that covers dozens of cities across several counties, serving everything from small independent locations to national retail chains. For businesses like this, "where is the customer" matters just as much as "what do they need," and most standard Google Ads advice doesn't say much about how to handle that second dimension.
We recently worked through this exact problem for a regional service business covering a sprawling, multi-county metro area. The approach we landed on is a useful template for any business that's local in nature but regional in footprint: split by service first, layer in audience-based automation, and treat geography as something you expand into deliberately rather than something you turn on all at once.
Start With the Services, Not the Geography
The instinct with a large service area is often to build the account around locations: a campaign for each city or county. In practice, that fragments budget and data before you have any signal about where demand actually concentrates. A newer or lower-volume market can't teach you anything if its campaign never accumulates enough clicks to be statistically meaningful.
A better starting point is the services themselves. If the business offers four or five distinct service lines, each one becomes its own search campaign, with ad groups underneath it that split out the different ways customers search for that service: general interest, compliance or inspection-driven searches, and urgent or emergency needs, for example. This does two things well. It keeps budget and bidding independent per service, so a slow month for one line doesn't starve the others. And it makes ad copy and landing pages easy to match precisely to the query, which is what keeps Quality Scores healthy and cost-per-click down.
It's also worth carving out one additional "umbrella" campaign for the broader category terms that don't map cleanly to a single service: the searches from someone who knows they have a problem but doesn't know which of your services solves it. This is often where informational or educational content on the website (a compliance guide, a "how it works" resource) pays double duty: it's the natural landing page for that umbrella campaign, and it does SEO work in parallel.
Add Performance Max as a Complement, Not a Replacement
Performance Max is genuinely useful for filling in the gaps that manually-built Search campaigns miss: the display, YouTube, and Discovery inventory that a service business would otherwise ignore entirely. But it works best as a single, well-targeted layer on top of a solid Search foundation, not as a substitute for it.
Rather than mirroring the service-line split from Search, we found it more useful to organize the PMax asset groups around audience segments, for instance, one asset group for smaller independent customers and another for larger multi-location accounts, since those two audiences respond to very different messaging (speed and personal service versus consistency and centralized reporting across sites). One PMax campaign spanning the full service area, split this way, tends to outperform several narrower ones competing against each other for the same signals.
Treat Geography as a Rollout, Not a Launch Setting
This is the part that's easy to get wrong. When a business's service area is genuinely large, spanning multiple counties or an entire region, the temptation is to target all of it from day one, since the business technically serves all of it. The better move is to launch narrow and expand on a schedule tied to what the data tells you.
In practice, that means:
Phase 1: Launch every campaign, Search and PMax, targeting only the one or two sub-regions with the highest expected demand (usually the most populous or highest-competition metro core). This is where you'll generate enough volume, fastest, to make real decisions.
Phase 2 and beyond: Widen the location targeting on the same campaigns to adjacent sub-regions once you have a few weeks of performance data. You're not building new campaigns for each phase; you're expanding the geographic footprint on infrastructure that's already proven out.
Later, selective splits: Once a specific city or sub-region shows enough volume and its own distinct dynamics, such as a different regulatory environment, a different competitive landscape, or pricing that needs to flex, that's the signal to break it out into its own campaign or ad group, not before.
Setting location bid adjustments to "observation" mode during the early phases is a simple way to watch performance by sub-region without committing budget unevenly before you have the data to justify it.
Why This Structure Works for Regional Service Businesses Specifically
The businesses this applies to best share a few traits: a service area too large to treat as one market, several distinct service lines rather than one product, and a mix of small and large customers who need different messaging. Structuring the account by service first prevents any one offering from getting lost inside a geography-first structure. Layering PMax by audience, rather than duplicating the service split, captures the incremental reach it's good at without cannibalizing Search. And treating geographic expansion as a phased rollout means every dollar of early budget goes toward learning fast, rather than being spread thin across markets you don't yet understand.
None of this requires a bigger budget than a flatter, less-organized account would need. It just requires deciding, upfront, which dimension (service or geography) should drive the account architecture, and being deliberate about the other one instead of defaulting to "target everywhere, sort it out later."
The Takeaway
For a regional or multi-location service business, the account structure that scales is built around services first, with audience-based automation layered on top and geography expanded in phases as the data earns it. Get that sequencing right, and the account grows in a way that keeps teaching you something at every stage, instead of guessing at a dozen markets simultaneously and hoping the budget stretches far enough to tell you anything useful.