Cutting a contractor's cost per lead by 58% — starting with the tracking
A home-services contractor was spending steadily on Google Ads with no idea what worked. Fixing measurement first, then rebuilding around buyer intent, more than halved the cost per lead in a quarter.
Client: Home-services contractor
- cost per lead in the first quarter
- -58%
- return on ad spend
- 4.7×
- to first booked jobs from the rebuilt account
- 2 weeks
The situation
A home-services contractor — bathrooms, kitchens, general refurbishment — had been running Google Ads for two years through a previous provider. The monthly invoice was consistent; the results were anyone's guess. Some months the phone rang, some months it didn't, and nobody could say which campaigns, keywords or pounds were responsible either way.
The owner's question was the right one: "am I buying jobs, or am I buying clicks?"
What was holding them back
The audit answered it quickly:
- Conversion tracking counted page views. The "conversions" the account had been optimising towards for two years included visits to the contact page — not calls, not form submissions. Google's automated bidding had been diligently optimising for the wrong thing the whole time.
- One campaign, every service, broad match. Bathrooms, kitchens, emergency repairs and tiny handyman jobs all shared one budget and one keyword pot — so the high-margin work subsidised clicks for jobs the owner didn't even want.
- Every ad landed on the homepage. Someone searching "bathroom fitters near me" arrived at a general page about the company and had to navigate onwards. Most didn't.
- No negative keywords worth the name. The search terms report — unopened for months — showed spend leaking to "jobs", "courses", "DIY" and other-town searches outside the service area.
What we did
Weeks 1–2: measurement before money. Call tracking installed, form submissions wired as real conversions, page-view "conversions" deleted, and the service area geotargeting corrected. No optimisation until the account could tell the truth.
Weeks 2–4: restructure around intent and margin. Separate campaigns per service line, budgets weighted to job value. Exact and phrase match on buyer-intent terms ("[service] + fitter/installer/cost/quote/near me"), with a negative list built from two years of wasted search terms — and grown weekly since.
Weeks 3–6: landing pages that finish the ad's sentence. One page per service line: the promise from the ad, local proof, photos of real work, and two actions — call or request a quote — visible at every scroll depth.
Ongoing: test, prune, scale. Weekly search-term reviews, ad copy tests with decision rules, and budget moved continuously from the campaigns that produced enquiries to the ones that produced booked jobs — a distinction only visible because the tracking now captured it.
The results
| Measure | Before | After one quarter |
|---|---|---|
| Cost per lead | baseline | −58% |
| Return on ad spend | unknown (untracked) | 4.7× |
| Time to first booked jobs | — | 2 weeks from rebuild |
The same monthly budget, redirected by honest data, produced more than twice the leads — and for the first time, the owner could see cost and return per service line and decide where to grow.
What made the difference
Refusing to optimise before the measurement was fixed. Every improvement downstream — the restructure, the landing pages, the bidding — only worked because the account was finally optimising towards jobs instead of page views. In PPC, tracking isn't admin; it's the steering wheel.
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