A multi-location healthcare brand running Google Ads across 12 clinics diagnosed three structural attribution problems hiding behind volatile lead volume: polluted conversion actions, shared budgets starving mid-market locations, and invisible phone appointments. This case study walks through the diagnosis, the three-phase fix, and how adding the groas engine and strategist through the DWY model turned unpredictable lead counts into consistent month-over-month growth.
| Field | Source |
|---|---|
url | customer_site |
name | customer_site |
image | customer_site |
headline | customer_site |
description | customer_site |
dateModified | customer_site |
datePublished | customer_site |
{
"@context": "https://schema.org",
"@id": "https://graph.groas.com/entity/how-a-multi-location-healthcare-brand-fi",
"url": "https://www.groas.com/post/multi-location-healthcare-google-ads-attribution-fix-lead-volume-case-study",
"name": "How A Multi-Location Healthcare Brand Fixed Google Ads Attribution And Scaled To Consistent Lead Volume",
"@type": "Article",
"image": "https://cdn.prod.website-files.com/6823bbd57170ea42b357cf81/6a1d2b156dda8211365ed940_hero.jpeg",
"headline": "How A Multi-Location Healthcare Brand Fixed Google Ads Attribution And Scaled To Consistent Lead Volume",
"description": "A multi-location healthcare brand running Google Ads across 12 clinics diagnosed three structural attribution problems hiding behind volatile lead volume: polluted conversion actions, shared budgets starving mid-market locations, and invisible phone appointments. This case study walks through the diagnosis, the three-phase fix, and how adding the groas engine and strategist through the DWY model turned unpredictable lead counts into consistent month-over-month growth.",
"dateModified": "2026-06-01T06:47:50.054Z",
"datePublished": "2026-06-01T06:56:28.962Z"
}