Case study · Home services · Google Ads + funnel rebuild
From 234 to 667 monthly leads in 4 months (Home Services)
A regional home services company wanted to grow lead volume without blowing up cost per lead. By rebuilding their Google Ads structure, tightening tracking, and reallocating budget, we grew from 234 to 667 leads per month in four months while holding cost per lead and platform ROAS inside agreed guardrails.
Lead volume
234 → 667 leads / month
~4 months from first rebuild to stable scale.
Efficiency
≈$33.55 CPL
Maintained cost per lead while scaling volume.
Return
≈2.32× platform ROAS
ROAS kept inside agreed guardrails as we scaled.
Market & goal
A regional home services company came in with a simple brief: increase lead volume from paid search without losing control of cost per lead. They were already spending across Google Ads but performance was fragmented and hard to read. Different services, locations, and intent types were blended together, and reporting couldn’t reliably answer “what’s actually working?”
The goal was to move from a blended, channel-first setup to a service-line system where budgets, bids, and creative could be controlled — and then scale into the segments that produced healthy economics.
What wasn’t working before
- Blended campaigns. Brand, non-brand, and competitor terms were mixed, making it hard to see which parts of the account were actually producing incremental leads.
- Limited intent control. Ad groups weren’t tightly mapped to specific services, so queries and ads didn’t always match the jobs the client actually wanted to book.
- Tracking noise. Calls and forms weren’t consistently deduped or value-tagged, so “conversions” in platform didn’t always line up with the real pipeline.
What we changed
1. Rebuilt to service-line structure
We rebuilt campaigns and ad groups around service-line intent: Brand, Non-Brand, and Competitor. That let us set different bids, budgets, and guardrails for high-intent search terms versus defensive or exploratory segments.
2. RSAs, DKI & location insertion
Each ad group received refreshed responsive search ads using dynamic keyword insertion and location insertion. This lifted ad relevance and click-through rate for the core “service + city” terms the client cared about most.
3. Tight geos, schedules & queries
We constrained campaigns to the right service areas, added dayparting based on historic lead quality, and ran weekly search term sculpting with negatives to keep spend focused on real buyer intent.
4. Brand-excluded PMax with guardrails
We layered in Performance Max for incremental reach, explicitly excluding brand where appropriate and capping budgets so search remained the main driver of predictable volume.
5. Conversion hygiene & value tracking
Calls and forms were deduped and mapped to a clean conversion set. We aligned conversion value tracking to the platform “Conv. value” fields so ROAS calculations reflected actual lead value, not just raw form fills.
6. Weekly pacing & guardrails
Every week we reviewed spend, volume, CPL, and platform ROAS by service line. We only added budget where guardrails held, which is how we reached 667 leads per month without losing cost control.
Results
- Lead volume: scaled from 234 to 667 monthly leads in about four months across the account.
- Efficiency: held cost per lead around $33.55 CPL while increasing volume.
- Return: maintained roughly 2.32× platform ROAS inside the client’s agreed guardrails.
- Clarity: service-line structure and clean conversions gave the client a much clearer view of which campaigns, services, and geos actually produced profitable work.
Why this worked
- Service-line thinking, not channel thinking. We treated each service and intent band as its own mini P&L, then allocated budget where the economics held up.
- Clean enough data to make calls. Deduped conversions and value tracking meant “good” or “bad” was based on numbers, not hunches.
- Guardrails instead of gambling. We scaled only where CPL and ROAS stayed inside agreed bounds, which let the client get volume without losing sleep over risk.
Want to see if we can do this in your market?
If you’re a home services company already spending on paid search and you want more leads without losing control of cost per lead, the Revenue Decision Review is the starting point. We’ll stand up Engine v1 on top of your data, then come back with a Cut / Fix / Double plan grounded in your actual funnel.