Google Search Ads: Driveway Paving & Repair Case Study
A Real Campaign Review, Not a Polished Marketing Story
Client:
Residential driveway paving and driveway repair company
Services Provided:
How Much Did Paving Ad Campaign Cost?
A quick breakdown of cost and high level metrics:
- ~$2000/month in Google Ad Spend
- $395/month for Google Ads Management
- Avg Cost Per Lead $22
- Conversion rate: ~25%
- Revenue attributed to Google Ads ~$360,000
Introducing What This Is
This case study is based on an internal call between Adam (Senior Google Ads Strategist) and Stephen (Co-Founder at Salt Water Digital), reviewing live Google Ads data for a residential driveway paving and repair company.
Rather than presenting a polished “before and after,” this is a walkthrough of how the campaign was structured, how it evolved, and why it performed as well as it did. We hope you find this style of case study informative and entertaining.
For a full summary, click here.
Let’s Get Started
Stephen: “So it’s driveway paving and repair. Residential. Syracuse, New York.”
Adam: “Yeah, fixing up driveways. We’re running Google Search only — during the season.”
The account was intentionally simple:
- One primary non-branded Search campaign
- Budget: ~$58/day (~$1,700–$1,800/month)
- Two ad groups:
- Driveway paving
- Driveway repair
- One branded Search campaign
- Budget: ~$7–$8/day
- Purpose: brand protection and clean conversion data
Stephen: “The client decided he didn’t want to advertise sealing. Smaller jobs, lower margins.”
That decision mattered. From the start, the account was optimized around revenue per job, not just lead volume.
Why Brand Was Broken Out Separately
Stephen:
“A lot of advertisers just include branded search terms in their evergreen ad groups and let it drive the cost per conversion down.”
Adam:
“Yeah, and it looks great on paper — but it’s not real.”
Brand traffic was targeted and isolated for two reasons:
- Competitors were actively bidding on the client’s brand name
- Mixing brand and non-brand would have artificially lowered CPL
Adam:
“If we had rolled brand into the main campaign, the CPL would look like $5. But that’s misleading.”
The branded campaign converted extremely well (as expected), with CPCs around $0.88, but it was kept separate to maintain honest performance reporting.
Performance: What the Numbers Actually Looked Like
Stephen:
“The conversion rate here is kind of insane.”
From June 1 to October 31 (peak season):
- Average cost per lead: ~$20–$23
- Conversion rate: ~25–26%
- Average CPC (paving): ~$5
- Majority of spend prioritized toward driveway paving
Adam:
“Google’s average conversion rate is what — five to eight percent?”
Stephen:
“Yeah. So this is way above that.”
Even if competition increased and CPCs doubled or tripled, the campaign would remain profitable because of how efficiently traffic was converting.
Bidding Strategy: How It Actually Evolved
This campaign did not start with automation.
Adam:
“When we launched in 2024, we started with manual CPC.”
Stephen:
“Right. No data yet — you want control.”
Manual CPC was used to:
- Control early cost per click
- Avoid low-quality traffic
- Establish realistic performance baselines
Once conversion data was consistent, the campaign transitioned to Maximize Conversions, followed by a target CPA.
Adam:
“We tried a $20 target CPA, but it was too tight.”
Stephen:
“Yeah, it just starts to choke spend.”
The target CPA was adjusted to around $30 — not because the client was willing to pay more per lead, but to avoid restricting volume unnecessarily.
The Real Bottleneck: Not Ads
Adam:
“The limiting factor here wasn’t performance.”
Stephen:
“It was operations.”
The campaign could have scaled further, but the client didn’t have the capacity to handle more leads.
Stephen:
“If he had more crews, he could’ve tripled the budget.”
The campaign didn’t stall because of rising costs or inefficiency — it stalled because demand outpaced fulfillment.
Revenue Impact
Adam:
“What was the revenue again?”
Stephen:
“About $360,000.”
- Revenue attributed to Google Ads: ~$360,000
- Total ad spend: ~$15K–$16.5K
Even using conservative attribution, the return landed in the 20–25× range.
Why This Campaign Worked
Adam:
“If you had to sum it up?”
Stephen:
“Very high conversion rate and a very low cost per lead.”
That didn’t come from shortcuts or inflated metrics. It came from:
- Clear service prioritization
- Separating brand and non-brand traffic
- Introducing automation only after data existed
- Landing pages aligned with real search intent
Measuring success in revenue, not vanity metrics
Who This Is For
This approach works best for:
- Residential home service businesses
- High-ticket or project-based services
- Seasonal operators
- Owners who care about profitability, not just lead volume
Final Thought
Adam:
“I wish all campaigns were like this.”
Stephen:
“Yeah — but this is what happens when structure and reality line up.”
This is what Google Ads looks like when it’s run as a business system, not a traffic experiment.
Summary
This case study reviews a Google Search Ads campaign for a residential driveway paving and repair company operating in a seasonal market.
Rather than relying on broad automation or blended performance metrics, the campaign was built around a simple principle: prioritize high-value services, control early costs, and scale only when lead quality and conversion data justified it.
The account was structured with a single non-branded search campaign focused on driveway paving and repair, supported by a separate branded campaign to protect the client’s name and keep performance reporting accurate. Lower-margin services were intentionally excluded to ensure every lead had meaningful revenue potential.
During peak season (June through October), the campaign consistently produced leads at approximately $20–$23 per conversion, with conversion rates around 25–26%—well above typical home service benchmarks. Average cost per click remained around $5 on the primary paving keywords, leaving substantial margin even if competition increased.
Over the course of the year, approximately $15,000–$16,500 in ad spend was attributed to roughly $360,000 in revenue. Performance did not plateau due to inefficiencies in advertising, but rather because the client reached their operational capacity and could not handle additional demand.
The key driver behind the campaign’s success was a very high conversion rate combined with a low cost per lead. This outcome was achieved through disciplined account structure, early cost control, intent-matched landing pages, and the deliberate introduction of automation only after sufficient performance data existed.
This campaign demonstrates how Google Ads can function as a predictable revenue system for home service businesses when managed as a business operation rather than a traffic experiment.
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