The client is a leading insurance company and is supported by a patented sales technology platform. They have a distinctive approach to generate and buy leads through branded, non-branded but owned, lead, and traffic vendors. They wanted to optimize the process of lead buying to improve marketing ROI.
Sigmoid mapped the entire lead journey and built multiple classifications, regression models, and an attribution model to calculate a lead’s propensity to buy a policy and estimated value for the lead. The score generated enables the client to make real-time decisions on their lead buying and servicing strategy to optimize their marketing ROI.
Our ML-based approach to lead buying delivered 80% precision improvement and a double-digit lift in revenue per marketing dollar.