The challenge
The existing lead scoring was based on arbitrary rules that hadn't been updated in years. Good leads got ignored. Bad leads got attention. Sales managers couldn't see what was actually happening in the pipeline.
Case study
RevBoost CRM
RevBoost's sales team was drowning in leads but closing almost none of them. They had Salesforce, but nobody trusted the lead scoring—it was basically random. Reps wasted hours on leads that would never convert.
7 monthsMarketing & Sales
Sales Productivity
3x
Better Conversion
40%
Less Manual Work
60%
Our solution
Built a custom CRM with ML-based lead scoring trained on their actual conversion data. The system learned which signals actually predicted success for their specific business, not generic best practices.
Results
Outcomes that changed the operating picture.
Lead conversion up 40%
Sales team productivity 3x
Manual data entry reduced 60%
Pipeline visibility went from guesswork to real-time
Technology stack
Frontend
ReactTypeScriptRecharts
Backend
PythonFastAPIPostgreSQL
Cloud
AWSSageMakerLambda
Other
Scikit-learnOpenAI APITwilio
