Enterprise Services Provider
-41%
Cost Per Sales-Qualified Lead
Step 1
The Problem
An enterprise services provider was spending heavily on Google and LinkedIn but generating a flood of unqualified leads that wasted sales team time. Cost per sales-qualified lead was unsustainable, and the marketing team couldn't justify additional budget without proving pipeline quality improvement.
Step 2
Our Approach
We restructured campaigns around intent signals rather than volume. Wayfinder AI built a lead scoring model from historical CRM data, identifying which keyword and audience combinations produced leads that actually closed. This model fed directly into platform bidding strategies.
Wayfinder AI in Action
CRM-Trained Lead Quality Scoring
Wayfinder AI trained on historical CRM close-rate data to score leads at the keyword-audience level, then fed quality signals back into platform bidding.
Step 3
The Impact
Cost per SQL dropped 41% while SQL volume held steady. Sales team efficiency improved dramatically as they stopped chasing dead-end leads, and marketing earned back budget credibility.
-41%
Cost Per SQL
Acquisition Cost
+89%
Lead-to-SQL Rate
Efficiency
-18 days
Sales Cycle Length
Efficiency
Performance Timeline
How We Tracked It
CRM-integrated offline conversion tracking. Lead quality measured from MQL to SQL to closed-won, with revenue attribution at the campaign and keyword level.
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