Google Ads Case Study: 8.82K Conversions for Gauld Foot & Ankle

Ad examples

Scripted office video and call tracking for Gauld Foot and Ankle. Auto-scrolls - hover to pause.

The situation

Gauld Foot & Ankle is a mid-ticket practice relative to the vein clinic in the same group. Custom orthotics and foot pain are the offer on the ads, with booking at gauldfootandankle.com. The cities named on the ads are Marietta, Buckhead, and East Cobb.

Several competitors in the area sell a similar visit. What Gauld actually does, and which office can take the appointment on a given day, is what the account had to learn. Doctors are not in every office all day. A lead that arrives when that office has no doctor is not a booking the practice can use.

The insight

A scan of competitor ads and offers showed what nearby clinics were selling, and where Gauld was different. That only helps if the keywords follow Gauld's own services, location by location.

The second constraint is the clock. Search intent shows up on particular days and hours. The media plan had to follow those hours, and it had to follow the doctor schedule, because the two do not line up by themselves.

What we deployed

We read competitor ads for what they were actually selling in this area, then lined that up against Gauld's own services. The overlap is real: foot pain and orthotics are common offers. The useful part was the difference, including which problems this practice treats and which office can take them. Keywords followed that difference. A competitor's headline was not copied into a Gauld ad group just because it was getting impressions nearby.

Bids and ad scheduling followed two clocks at once. One is when search intent shows up, by day and by hour. The other is when a doctor is actually in that office. The practice does not staff every doctor, all day, in every location, and the services are not identical from office to office. Filling the book meant asking which hours still had open appointments, then putting spend on the queries that appear in those hours. The work used the doctors' schedules. It was not one daypart applied to the whole account.

The same weekly script used on Gauld Vein and on Sona splits search terms into high-performing and low-performing tiers. Daily term checks feed that weekly split. The script does most of the sorting. This page is only the foot and ankle practice.

Meta ads in the files repeat the orthotics offer and the three cities. Google is where the schedule and the query work happened.

Search-term sorting like this sits under AI automation. The media plan sits under paid advertising. Other studies are on the case study index.

Facebook used the same offer as the Google account, shot as scripted video in the local offices so the practice showed up in the area it actually serves. A virtual phone number records the calls. The team can play the recording, and AI helps identify the call and helps with the response. The account optimizes to 20-second calls and to direct calls. Campaigns that held the cost target were the ones that received more budget.

Results

Google Ads, May 31, 2023 through Jan 31, 2025, 16 campaigns: 8.82K conversions, 55K clicks, $4.06 cost per conversion, and $35.8K cost. The screenshot has no prior period, so this page does not claim a lift.

Lead quality and volume came up for the locations they staff. The screenshot is an account total. It does not break results out by office, by doctor, or by hour, so this page does not either.

Meta Ads, account Gauld Foot & Ankle, Jan 1, 2024 through Mar 18, 2025. The filled top-of-funnel row is a lead campaign: 37 results measured as 20-second calls, reach 32,404, frequency 2.42, $46.88 per 20-second call. A bottom-of-funnel website-call row shows 1 call at $11.83. The other rows in that export are blank, so they are not added in. The 37 and the 1 are the volume this page reports for Facebook.

Why it worked

Competitor language had to match Gauld Competitor language was used only where it matched a service Gauld sells. The rest of the local noise stayed out of the keyword list. Volume without that filter would have filled hours that had a doctor and hours that did not.

The doctor schedule was part of the buy Demand on a day the office cannot see a patient is the wrong demand, even when the query is right.

The script sorted by hour and office The two-tier script kept the weekly edit list short. High-performing terms stayed. Low-performing terms were the ones to negative or rewrite, including terms that only looked fine until you checked the hour and the office.

Recorded calls decided the scale The virtual number made a 20-second call something the team could hear. AI helped identify the call and the response. Budget moved to the campaigns that held the cost target.

← All case studies · Related service →