Lead Conversion Modeling
InsuranceBusiness Impacts
Enabled lead prioritization
Interpretable reasons, valuable insights
Customer Key Facts
- Location : North America
- Industry : Insurance
Problem Context
The customer is one of the largest providers of supplemental insurance in the United States, providing financial protection to more than 50 million people worldwide. They were facing problems in identifying the leads who have a higher likelihood to convert. They ultimate goal was to help their call center prioritize the leads, in terms of who to contact first, based on likelihood of conversion.
Challenges
- Data set available was highly imbalanced
- Enhancement of solution by minimizing the tuning time
- Providing support reasons for the identified metrics which potentially affect the probability of conversion
Technologies Used
Python
Tableau
Teradata
Prioritizing The Incoming Leads Which Are Being Contacted Based On The Likelihood Of Conversion
Solution
Quantiphi created a lead conversion model and developed a real-time dashboard that enabled the client’s call center employees to identify the potential leads which should be contacted first.
Result
- Real-time leaderboard displays the probability of conversion of leads batchwise on a weekly basis
- Dashboard supports the scores by providing interpretable reasons and meaningful insights
