Using Faraday’s predictive lead scoring to prioritize leads for follow up, a national solar company dramatically boosted their team’s sales efficiency
Momentum Solar sought to optimize lead scoring to reduce customer acquisition costs and improve conversion rates
They used a rules-based system with limited data points, leading to static and incomplete lead prioritization
Momentum implemented Faraday’s predictive lead scoring, leveraging machine learning to rank leads based on their probability of conversion
Leads were categorized into red, yellow, and green groups, with predictive models updating scores dynamically as new data was collected
The new system led to a 33% reduction in calls-per-appointment, with significant improvements in conversion rates for higher-priority leads
