Case study · Local vehicle-accessory fitting

A fitting shop stopped paying for leads it could never convert.

A Cape Town towbar and vehicle-accessory fitting shop was running Google Ads through a manager who had set it up and left it. The phone rang, but too often with people who lived too far away to ever become customers.

Abstract illustration: scattered light trails converging into a single tight cluster

Industry

Towbar and vehicle-accessory fitting

Market

Cape Town — a local service area a customer has to physically drive to

Starting point

An inherited live account, previously managed by someone else

Engagement

Ongoing Google Ads management

Headline result

Click-through rate up from roughly 2% to roughly 7.5%; cost per lead down 20%

The challenge

Leads were trickling in, but a large share of them came from outside the service area. A fitting shop cannot help a customer who cannot drive to it. Every out-of-area click was money spent on someone who could never become a customer, and every out-of-area phone call was time spent on an enquiry that could only end one way.

The owner’s instinct was that something was wrong. He was right, and the account turned out to be worse than he thought.

What we found

The campaign list gave the game away before we looked at a single metric. A Cape Town business was running separate campaigns aimed at Johannesburg and Pretoria — cities well over a thousand kilometres away, where the shop cannot fit anything to anyone. Those campaigns had been quietly spending for a long time.

Sitting alongside them was a Smart campaign. That is a campaign type that hands targeting, bidding and placement decisions to Google’s automation and gives the advertiser almost no visibility into, or control over, any of them. It is a reasonable choice for a business with nobody to manage the account. It is a poor choice for a business paying somebody to manage the account.

Underneath that, four structural problems:

Location targeting far wider than the business could serve

The account was buying clicks across regions the shop had no ability to service.

No control over which searches triggered ads

Ads were matching to irrelevant and low-intent queries, with no systematic negative-keyword programme holding the line.

A flat structure with no separation by intent

Everything sat together. Someone searching for a specific vehicle fitment and someone idly researching towbars were treated identically — and because nothing was separated, nothing could be optimised.

Ads and landing pages that did not match the search

The copy did not reflect what the shop actually offered, and traffic was being sent to a generic homepage regardless of what had been searched for.

The approach

The account could not be fixed with tweaks. It was rebuilt — but in stages, because the urgent problem and the structural problem were not the same problem.

Stop the bleeding

Location targeting was locked to the real service area and the out-of-province campaigns were switched off. A systematic negative-keyword programme went in behind it. The effect is visible in the account and it looks alarming at first glance: monthly impressions fell by close to 90%. That was the point. Impressions are not the goal — relevant impressions are, and the ones we removed were never going to produce a customer.

Rebuild the structure around intent

The account was rebuilt into campaigns separated by what the searcher actually wants: core products, competitors, vehicle models, brand, and secondary products. Each has its own ad groups, match types and copy. This is what makes ongoing optimisation possible at all — you cannot improve what you cannot isolate.

Rewrite the ads and match the landing page

New ad copy was written against each campaign’s intent, and service-specific landing pages were built so that the page a visitor lands on answers the search they actually made.

Hand bidding to the machine — but only once the data was clean

The account was moved to conversion-based smart bidding after the structure, targeting and tracking were sound. Smart bidding optimises against the data you give it. Give it dirty data and it will optimise, efficiently, toward the wrong thing.

The results

Click-through rate is the clearest single signal that an account is showing ads to the right people. It sat between 2% and 3% through the first half of 2025. After the cleanup it settled between 6% and 8%, and it has held there.

Cost per lead followed. Comparing the four months before the cleanup with the two months after it, the blended cost of producing a recorded lead fell by 20%.

Click-through rate

~2% → ~7.5%

roughly tripled, and holding

Cost per lead

−20%

~R206 → ~R164

Out-of-province campaigns

Switched off

targeting locked to the service area

What we are working on now

This is a live account, not a finished project. Search-term hygiene is reviewed on a cadence so the account does not drift back into the waste it started in, and the structure is being extended beyond pure search — there is now a seasonal demand-generation campaign running alongside it.

The honest position on an account like this: the big win was early and structural, and the work since has been the slower business of compounding it.

The takeaway

Cheap management is expensive. Paying for the ads and paying someone who is not really managing them produces bad results from both. For a local service business, location targeting is not a setting you check once — it is the difference between a lead and a wasted phone call. And structure is not housekeeping: it is the thing that makes every future improvement possible.

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All figures are taken from live Google Ads accounts and were last verified on 14 July 2026. Client identity withheld by request. Results reflect specific market conditions and business context; individual outcomes vary.