An Ontario roofing company came to us. They promoted roofing and siding services in a limited geographic area. The niche was highly competitive and strongly seasonal. During winter, demand dropped significantly, and weak ad setup made the problem worse.
Our goal was not just to improve Google Ads metrics, but to build a system where decisions could be made based on qualified leads, closed sales, and revenue.
In the end, we cleaned up the account, achieved strong advertising profitability, and built a transparent connection between ads, qualified leads, sales, and revenue. For every $6 in marketing spend, the business generated about $100 in revenue.
"We went from guessing to knowing exactly where every dollar was going and what it was bringing back."— Project Lead, Ontario Roofing
What We Changed
First, we rebuilt the account.
Campaigns were segmented by service lines so each one could be managed separately. We tightened traffic control, used phrase match, and applied aggressive negative keyword management to filter out junk queries and reduce irrelevant inquiries.
We also launched a separate competitor campaign. This let us evaluate whether that segment could generate quality conversions and capture demand from users already comparing contractors.
Most importantly, we built a system that allowed the business to scale based on real numbers, not assumptions.
End-to-End Analytics and Qualified Leads
The key shift was moving to end-to-end analytics.
We connected advertising to the CRM and started optimizing not for raw leads, but for qualified leads. This let us see which campaigns produced not only volume, but also quality.
Every metric is under control, both in the Google Ads account and in the client dashboard.
After that, we went further and set up offline conversions. Sales data started flowing back into the ad platform at the campaign and keyword levels.
As a result, we could clearly see:
- the cost of every keyword;
- the revenue generated by every keyword;
- which campaigns actually paid off;
- where average order value was higher;
- what share of revenue was being spent on marketing.
