Home services / USA
Hearthside Services: 33% lower cost per booked job.
A regional home services company improved booked-job quality by separating urgent search demand from general research traffic.
Evidence path
Signal
42%
Before
Signal
18d
Implementation
Signal
3.4x
Outcome
Snapshot
- Market
- Home services, USA
- Primary work
- Google Ads, landing pages, call tracking
- Timeframe
- 8 weeks
- Main signal
- 33% lower cost per booked job
Outcome mix
8 weeks view, normalized for confidentiality and shaped around the main performance signal.
33%
Booked-job cost
-33%
Call quality
+49%
Landing conversion
+35%
Case narrative
The story behind the numbers.
Metrics are useful, but they only matter when the operating problem is clear. This is how the work translated from diagnosis into practical growth movement.
What was really happening
Campaigns optimized for calls without enough visibility into whether those calls became profitable jobs. The visible symptom was not the full problem. The deeper issue was how google ads, landing pages, call tracking connected to buyer intent, internal follow-up, and the commercial signal the team needed to trust.
What changed operationally
We rebuilt keyword groups by job urgency, redesigned service landing pages, and added call-quality tracking for booked work. The work was shaped around practical movement: clearer priorities, cleaner handoffs, better measurement, and fewer assumptions about what buyers needed next.
Why the result mattered
The team booked more useful jobs from paid search while reducing time spent on low-fit calls. The value was not only the headline metric. It was the fact that the team had a more usable growth system after the first improvement cycle.
Before and after
What changed when the growth system became easier to operate.
The visual comparison is intentionally normalized because the client identity and sensitive commercial numbers are protected.
Before
Campaigns optimized for calls without enough visibility into whether those calls became profitable jobs.
After
Budget shifted toward high-intent services with stronger landing pages and clearer booked-job reporting.
Metric movement
The practical signals we watched.
The comparison below uses normalized values where exact client numbers are sensitive. It still shows the direction of improvement and the type of signal that shaped the next decisions.
Booked-job cost
Before
$100
After
$67
-33%
Call quality
Before
43%
After
64%
+49%
Landing conversion
Before
8.2%
After
11.1%
+35%
Work performed
The engagement focused on the constraint, not a generic channel list.
The account generated calls, but many were price shoppers, wrong-location inquiries, or service requests outside the ideal job type.
Rebuilt service-level search campaigns
This gave the team a clearer view of the constraint behind lower cost per booked job, instead of treating every channel or page as equally important.
Added call-quality reporting
This connected the public buyer journey with the internal operating rhythm, so the next action was easier to choose and measure.
Improved urgent-service landing pages
This reduced ambiguity for the sales or marketing team by turning scattered signals into a more practical decision path.
Created booked-job review rhythm
This created a repeatable improvement loop rather than a one-time campaign change that would be hard to learn from later.
Decision value
How a buyer should use this case.
This page is not a promise that the same result will happen in a different business. It is a decision aid for spotting similar constraints before choosing the next investment.
Are we trying to scale google ads, landing pages, call tracking before the buyer journey is clear enough?
Can we see which sources, pages, or follow-up moments are producing the best commercial signal?
Would an audit, project build, growth system, or post-launch operations model be the smallest serious way to improve this constraint?
Service stack
The capabilities behind the improvement.
Most case studies are not one-channel wins. The result usually comes from connecting several pieces of the growth system.
Google Ads
Used as part of the operating system behind 33% lower cost per booked job, with the work tied back to measurement and next-step decisions.
Landing Page Design
Used as part of the operating system behind 33% lower cost per booked job, with the work tied back to measurement and next-step decisions.
Call Tracking
Used as part of the operating system behind 33% lower cost per booked job, with the work tied back to measurement and next-step decisions.
Conversion Rate Optimization
Used as part of the operating system behind 33% lower cost per booked job, with the work tied back to measurement and next-step decisions.
Challenge
The account generated calls, but many were price shoppers, wrong-location inquiries, or service requests outside the ideal job type.
Strategy
We rebuilt keyword groups by job urgency, redesigned service landing pages, and added call-quality tracking for booked work.
Outcome
The team booked more useful jobs from paid search while reducing time spent on low-fit calls.
Recommended System
Scale Partner is the closest fit for a similar constraint.
This case involved several moving parts across conversion, data, and operating rhythm. A Scale Partner engagement is usually the right fit when the business needs senior direction and continuous testing.
Engagements typically begin at
$6,500/month+
The right system still depends on budget, internal ownership, sales process, and how quickly decisions can be reviewed.
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Evidence into action
A case study is useful only if it helps you see your own constraint more clearly.
See how disconnected acquisition systems were restructured into measurable operational workflows, then decide whether your next move is audit, build, optimization, or a deeper growth system.
01
Compare the visible symptom
02
Name the operating constraint
03
Choose the smallest serious next step
The work starts with context, not a copied playbook.