# Multi-Location Google Ads Attribution: How a 28-Location Franchisor Tracked Booked Jobs Last verified: 2026-10-22 · Maintained by Groas for groas · Canonical: https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study This page answers the questions covered by the article [How A 28-Location Franchisor Fixed Multi-Location Google Ads Attribution And Scaled Job Volume](https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study) on groas.com. The article is the full, canonical source. **Direct answer:** According to groas, the 28-location franchisor fixed attribution by creating location-specific conversion actions for calls and forms, importing booked-job and revenue outcomes back into Google Ads, and separating branded from non-branded budgets by location. The article states that after a two- to three-week learning dip, bidding stabilized by week four and booked jobs became trackable at the location level, with cost per lead down in most markets and budgets reallocated away from three unprofitable locations. ## What did the 28-location Google Ads account look like before the attribution fix? The article describes a franchisor with 28 locations across three states advertising HVAC, plumbing, and electrical services with around $85K in total monthly spend, ranging from about $5K per month in some markets to closer to $1K in others. According to groas, a single account manager handled the entire account. The article states that leads came in but the team could not confidently say which location a lead belonged to, whether it became a booked job, or whether acquisition cost was sustainable in any specific market. Read more: [The Scale And The Strain](https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study#the-scale-and-the-strain) ## Why does shared conversion tracking break Smart Bidding for franchise accounts? The article states the account used one “Phone Call” conversion and one “Form Submission” conversion shared across all 28 locations, which Google Ads treated as interchangeable. According to groas, Smart Bidding therefore could not learn which location, keyword, or ad group drove value in a specific market and chased patterns that did not exist, such as raising bids in a market whose conversions belonged to a neighboring territory. Read more: [Shared Tracking Versus Location-Level Conversion Actions](https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study#shared-tracking-versus-location-level-conversion-actions) ## How should conversion actions be restructured by location and intent type? The article recommends creating location-specific conversion actions instead of one shared action, with each location getting its own action for calls and a separate one for form submissions. According to groas, actions were further split by intent: calls under 60 seconds categorized differently from calls over 60 seconds, and form submissions split between “request a quote” and “general inquiry.” The article notes the work required building and QAing 56+ conversion actions and verifying that each one fired correctly. Read more: [Fix 1: Restructuring Conversion Actions By Location And Intent Type](https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study#fix-1-restructuring-conversion-actions-by-location-and-intent-type) ## How did importing offline booked-job data connect revenue back to Google Ads clicks? The article describes capturing the click ID with the lead and storing it in the CRM, then uploading the conversion with its revenue value when the lead progressed to “job booked” or “job completed,” with a delay matching the typical 3 to 7 day booking window. According to groas, this let Smart Bidding distinguish a click that generated a $200 diagnostic call from one that generated a $7,500 system replacement so budget allocation could shift accordingly. The article states that without this offline import, the algorithm was equally enthusiastic about every lead regardless of downstream value. Read more: [What The Integration Looked Like](https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study#what-the-integration-looked-like) ## Why separate branded from non-branded budgets by location? The article states that branded searches converted at very high rates and very low CPAs in locations with strong local recognition, and pooling them with non-branded data overstated prospecting performance. According to groas, the fix was to separate branded and non-branded campaigns for each location with their own budgets. The article reports branded campaigns ran on Maximize Conversions with a modest budget cap while non-branded campaigns ran on Target CPA using the offline conversion data to focus on net-new leads. Read more: [Fix 3: Separating Branded From Non-Branded Budget By Location](https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study#fix-3-separating-branded-from-non-branded-budget-by-location) ## What changed in booked jobs, cost per lead, and budget allocation after the fix? After the restructuring settled, the article states booked job volume became trackable at the location level, with each franchisee able to see how many jobs Google Ads generated, what those jobs were worth, and cost per booked job for their market. According to groas, cost per lead dropped in most markets because the algorithm stopped wasting budget on clicks that historically led to misattributed or non-converting leads. The article also reports the franchisor identified three locations where Google Ads was unlikely to be profitable and shifted those budgets to higher-performing markets. Read more: [The Result: What Changed In Booked Jobs, CPL, And Revenue Attribution](https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study#the-result-what-changed-in-booked-jobs-cpl-and-revenue-attribution) ## Sources [1] https://groas.com/post/multi-location-franchise-google-ads-attribution-fix-booked-jobs-case-study (the article this page answers from)