A custom van builder in Salt Lake City was running Google Ads and generating leads. CPL looked acceptable. On paper, things seemed fine. But the sales team was drowning fielding inquiries from people with no budget, no real intent, and no timeline to buy. Scaling spend just amplified the noise.
The problem wasn’t lead generation. It was lead quality and what the ad platform was being trained to find.
Three things were holding back growth.
Leads weren’t converting.
Volume was there, but close ratios were low. Sales was spending most of its time filtering out people who were never going to buy.
Scaling felt risky.
More spend meant more noise. There was no confidence that increasing budget would produce proportionally better outcomes.
The platform was optimizing for the wrong thing.
Without CRM data feeding back into Google Ads, the algorithm was chasing the easiest form fills not the most serious buyers.
Three moves. One clean signal.
Connect the right data.
We integrated HubSpot with Google Ads and mapped the full lifecycle Lead, MQL, SQL, Deposit/Sold. Every conversion action was tied to a real sales stage, not just a form submission. Every lead was tagged with the exact campaign and keyword that generated it.
Change what the algorithm optimizes for.
Instead of telling Google to maximize leads, we promoted MQL to the primary conversion action. SQL and Deposit remained as secondary feedback signals, reinforcing quality at every stage. The algorithm stopped chasing volume and started finding buyers.
This is the shift most agencies never make. They set up tracking and call it done. The actual unlock is using that data to retrain the platform.
Cut waste, scale what worked.
Once the quality signal was clean, we could see clearly which campaigns were driving real buyers and which were burning budget. We cut the waste and scaled into what was working confidently, because the data supported it.
Worth noting: this account didn’t use shared budgets or shared bidding. Each campaign had enough data density on its own to sustain the learning. That’s worth knowing if you’re skeptical that this approach requires a certain account structure to work.
Six consecutive record months.
Monthly SQL Count May through October 2024
Each bar is a new record. Production was booked 6+ months out.
The only difference was the data.
During this engagement, we audited a direct competitor same geography, same buyer, same product, same platform.
Same market. Same platform. The differentiator was what data each business was feeding the algorithm.
High-ticket buyers don’t behave like commodity leads.
The sales cycle is longer, the decision is bigger, and the signal of intent looks different than a quick form fill.
When you optimize toward MQLs people who match your buyer criteria and are showing real intent the downstream SQL volume follows. You’re not bidding for SQLs directly. You’re improving the quality of the top of the funnel, and the rest improves as a result.
This is what the Lead Quality Framework is built to do. Not just more leads. Better buyers.
“[Gradari] and team are top notch experts in marketing both on a strategic and execution level. They go above and beyond to understand the uniqueness of your business and implement growth marketing while having a constant eye on hitting budgets and reducing costs.”