How should I structure an ad account to reduce waste?

Why structure decides how much you waste

Account structure is the chassis every other optimization rides on. A clean structure makes waste visible inside an hour of audit time. A messy structure hides waste under blended averages for months, sometimes years. The platforms don’t care which structure you pick, because their revenue rises either way. The fix is upstream of bidding, creative, and landing page work.

These six decisions cover the structural choices that most often separate accounts running clean from accounts leaking budget. Read the Wasted Ad Spend hub for how the diagnostic signals connect.

Decision 1: segment campaigns by query intent, not by product

A common default is one campaign per product line or one campaign per service. That bundling collapses four intent tiers into a single ROAS number. Branded queries (someone searching the company name), non-branded category queries (someone searching the category with no brand in mind), generic top-funnel queries (someone searching a problem), and competitor queries (someone searching a rival) behave nothing alike. Branded converts far better than generic. Competitor traffic usually costs more per click than branded and rarely converts at the same rate.

The right pattern is one campaign per intent tier you pay for. Non-branded category sits in its own campaign with the bulk of the budget and conversion-based bidding. Generic and competitor run as separate test campaigns with strict CPA caps. Brand doesn’t get a campaign by default. My rule is to stay out of the auction for the client’s own name: the brand name and its misspellings go in as phrase negatives across the account, and the organic listing takes those searches. Pulling them out shows how much of the blended result was brand demand quietly covering the losses on competitor and generic.

The one exception is a competitor’s ad holding your brand search above your organic result. Then a brand campaign is worth testing, with a capped budget and exact match, kept separate so it can’t inflate non-brand numbers. Move the brand negatives from the account level to a shared list applied to every non-brand campaign, or they’ll block the brand campaign too. High CPC without sales covers that test.

Network settings belong in the same decision, because they decide which auctions each campaign enters. Across 30 Google Ads accounts I manage, 30 days to October 21, 2026, Search Partners was on in 1 of 51 Search campaigns, carrying 1.1% of spend, and Display expansion was on in none. A Search campaign that also buys partner and Display inventory reports one number for three kinds of traffic.

Decision 2: one match type per ad group on tighter accounts

Mixed match types inside a single ad group create internal auctions. The broad keyword cannibalizes the exact match keyword, the system optimizes against whatever bid is highest, and the search terms report becomes hard to read. On accounts under twenty thousand a month, the surface area is small enough that this matters every week.

The right pattern on smaller accounts is one match type per ad group. Exact match ad group, phrase match ad group, broad match ad group, each with the same keyword theme but different intent thresholds. Negative keywords flow up the funnel: exact match terms become negatives in the phrase ad group, phrase match terms become negatives in the broad ad group. The search terms report now reads cleanly per match type, and the cannibalization stops. Larger accounts above fifty thousand a month can sometimes run mixed match types inside Smart Bidding ad groups, but only with a weekly search terms review. Skip the review and the broad keyword eats the budget inside thirty days.

Keyword sprawl hides a second cost. In my Q3 2026 Google Ads benchmarks, a median 38% of keyword spend ran on keywords with no Quality Score reported, and a median 4% sat on QS 7 to 10 (N = 31). Unscored keywords give you no read on ad relevance or landing-page fit, so an ad group full of them can’t tell you which half to rewrite. Fewer keywords per theme, each with enough traffic to earn a score, makes the structure readable.

Decision 3: split Performance Max asset groups by audience tier

A Performance Max campaign with a single asset group treats every product and every audience the same. The campaign reports one ROAS, the algorithm picks its own winners, and there’s no way to see whether the spend went against best-sellers shown to existing customers or against new SKUs shown to cold prospects. That’s exactly how Performance Max budget pools end up over-indexing on retargeting that was already going to convert.

The right pattern is asset groups split by audience tier. One asset group for prospecting with cold-only audience signals and no customer-match lists attached. A second for retargeting with site-visitor and cart-abandoner signals. A third, sometimes, for existing-customer expansion with purchaser lists. Each asset group gets its own creative set, its own product feed segment if the catalog supports it, and its own performance read. On a Shopify account running Performance Max, this split can show prospecting costing far more per sale than the blended ROAS suggested, while retargeting ran above target. The fix is reallocating budget. The campaign stays. Furniture brands running PMax hit this same asset-group split with one extra tier for catalog-heavy SKUs.

Decision 4: separate geographies when service areas matter

Service businesses with distinct service areas often run a single campaign targeting all of them. Cost per click in a dense urban market can run several times the cost per click in the surrounding suburbs. A blended campaign hides that. Worse, when one market has lower conversion intent than another, the campaign optimizes against the cheaper clicks regardless of close rate.

The right pattern is one campaign per service area when close rates or unit economics differ. A roofing company serving a metro and three suburbs runs four campaigns, each with its own budget scaled to demand and capacity. A multi-location retail brand runs one campaign per distribution radius. The threshold to skip the split is when the markets have nearly identical CPC, conversion rate, and lifetime value.

Whichever split you choose, check the location option on every campaign. Google’s default reaches people searching about a place as well as people in it. Across 30 Google Ads accounts I manage, 30 days to October 21, 2026, 50 of 51 Search campaigns use Presence targeting, which reaches only people in or regularly in the targeted area. A service business that can’t work outside its area has no reason to pay for the rest. For Shopify brands shipping nationally, geographic separation matters less except where shipping cost or seasonal demand swings hard between regions. On legal accounts with practice areas across markets, the segmentation tightens further because intake teams can’t handle blended jurisdictions.

Decision 5: scope budgets at the campaign level, not the shared pool

Shared budgets across campaigns sound efficient. They almost never are. A shared budget lets the platform shift spend toward whichever campaign it scores highest, and platform scoring favors volume and click-through rate over revenue quality. A high-CTR campaign, such as a brand campaign run under the competitor exception, pulls spend away from the non-branded campaign that produces incremental revenue.

The right pattern is campaign-level budgets that match the strategic priority for each intent tier. Non-branded gets the bulk allocation. An exception brand campaign gets a capped budget sized to the brand searches the competitor is contesting, with overflow blocked. Test campaigns (generic, competitor, new geography) get explicit small budgets that fail fast if performance doesn’t clear the bar. Shared budgets belong only on portfolio bid strategies where two campaigns target the same intent and the same audience, which is rare in practice. A campaign-level budget also lets each campaign carry the bid strategy its intent needs. Across the 51 Search campaigns in the accounts I manage, 30 days to October 21, 2026, 35 run Maximize Conversions, 8 Maximize Clicks, 4 Maximize Conversion Value, 3 Manual CPC and 1 Target Impression Share. A pooled budget makes campaigns on different strategies compete for one pot. The Wasted Spend Calculator gives a directional dollar figure for what the current structure is leaking, from your monthly spend and red-flag count.

Decision 6: a naming convention that surfaces structure in every report

The deepest cause of structural drift is unreadable account history. Six months into an account, the original builder has often left, and the campaign names look like Campaign 1, Campaign 1 (copy), Final Campaign, and Test 3. Audits take days instead of hours because nobody can tell what each campaign was supposed to do.

The right pattern is a naming convention that encodes intent, geography, match type, and date in every campaign and ad group name. A workable format: Platform | Intent | Geography | MatchType | LaunchDate. So Google | NonBranded | Metro | Phrase | 2026-05 reads cleanly in any column. Pivot tables and Looker Studio reports group automatically. New media buyers onboard in an afternoon instead of a week. The convention itself costs nothing. The absence of it costs every future audit hour.

Where to start

Apply decision one first. The intent split surfaces where the real money is going inside the first week and makes the next five decisions easier to scope. Decision four matters only for service businesses with real geographic spread. Decision six pays back every audit cycle for the life of the account.

Founders who want a senior pair of eyes on the structure can request my free written audit: 5 to 7 pages, back within 24 hours of read-only access, no call needed. If you’d rather work it yourself, grab the free 25-page Setup Checklist first.

The same six-decision sweep is the first thing I check in every account I audit.

When to bring me in

Bring me in when cost per lead keeps rising and the fixes above haven’t moved it, when you can’t tell which campaigns produce booked work, or when the search terms report shows money going to searches you’d never pick.

I'm Conner Crowe, and I write every audit myself. Send the free audit request and add me as a read-only user, and within 24 hours of access you'll have a written read on where the spend leaks and what to fix first. No call needed, and nothing in your account or store changes.

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