Case studies / From nearly-invisible to #1 in their market
From nearly-invisible to #1 in their market.
A Florida weight-loss clinic with two busy locations was drawing about 5,000 search impressions a month and fewer than 50 clicks. It had two location pages, and both sat outside the top 10 for the terms that mattered. We rebuilt the site the way AI reads the web, and the searches followed.
The short version
We don't name clients. Here's exactly what happened anyway. A clinic with two locations was drawing about 5,000 search impressions a month and fewer than 50 clicks, with both of its location pages outside the top 10. We rebuilt the site around structure machines can parse, launched it on May 16, and in the ten weeks that followed it logged 36,753 impressions and 533 clicks, with the clinic at position 1 in both cities for brand-and-city searches.
Research: what we found
The clinic was real and busy. Two locations, full calendars, a loyal patient base built on referrals. Online it may as well not have existed.
The old site was drawing roughly 5,000 search impressions a month and fewer than 50 clicks. Almost nobody who saw it in a results page had a reason to choose it. It had two location pages already, but both ranked outside the top 10 for the terms that mattered, and the site carried no structured data a crawler could resolve into a business, its clinics, and its services.
The surrounding map ecosystem was in worse shape. Our audit found 23 separate business profiles across the directories, apps, and data providers that feed the map results, and they disagreed with each other: one platform had four listings instead of one, including a duplicate at a wrong street address. A social profile carried a generic name with no brand in it at all. A local chamber listed two different phone numbers, both wrong. Machines resolve a business by matching its name, address, and phone across sources. This business did not match itself.
Plan: what we told them
We told them the website had to be rebuilt before anything else would work. Not refreshed. Rebuilt, with the structure machines look for: a page per location, entity-level structured data for the business and each of its services, and question-and-answer content written the way patients actually search.
We were equally clear about what would not work. More social posting would not fix invisibility, because the clinic already had attention; what it lacked was legibility to machines. And in a regulated health category we would not market treatment outcomes, because that is a compliance problem waiting to happen. The plan was rankings and structure, nothing else.
Execute: what we did
A new site with dedicated pages for each location and each service, structured data covering the business, both clinics, and every service offered, and clean fast pages that crawlers and AI assistants can parse without guessing.
One canonical name, address, and phone number, verified against the state business registry, published consistently on the new site so every downstream data source has a single authority to reconcile against.
Every profile across the map ecosystem checked line by line: duplicate listings, a wrong address, wrong hours on two platforms, wrong phone numbers, and an unbranded social page, all documented in a corrections list now being worked through.
The result, ten weeks in
- Search impressions~5,000 per month 36,753 in ten weeks Improved
- Clicks from searchUnder 50 533 Improved
- Brand-and-city searches Both citiesNowhere Position 1 Improved
- Location pagesTwo, outside the top 10 Two, both ranking Improved
The impressions were never the problem. People were already being shown this clinic about five thousand times a month and almost none of them clicked, because nothing on the page told a machine, or a patient, which clinic this was or what it did.
Monitor: what we watch now
Search performance is pulled weekly. Brand-and-city searches sit at position 1 in both cities. The non-branded category searches rank mid-page and are the next front, so the listings corrections and continued content work target them. We report those numbers to the client as they are, including the weeks they dip.
The rankings held.
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