Customer Lifetime Value Model
InsuranceBusiness Impacts
+5
Points increase in average net promoter score (NPS)/sentiment score
10%
Increase in average customer life span with targeted customer outreach
50%
Time reduced in customer interaction with personalized touch
10%
Growth in revenues from existing customer base compared to acquisition costs for new customer
Customer Key Facts
- Location : North America
- Industry : Insurance
Problem Context
The customer is a leading pet health insurance company in the U.S. and Canada that provides insurance for pet owners to cover veterinary bills. Their Marketing team wanted to focus on high-value customers and make data-driven business decisions for improved targeted marketing.
Challenges
- Uncertainty in data source
- Lack of rule set to classify high-risk customers
- Difficulty in integration of customer churn, spend forecasting, and customer segmentation models
- Identifying the correct attribution of the customer
Technologies Used
Google Cloud SQL
Zeppelin Notebooks
Tableau
Google Cloud Storage
Google Compute Engine
Google's BigQuery
Developing a Customer Lifetime Value Model to Identify High-Value Customer Groups For Improved Targeted Marketing
Solution
Quantiphi built a Customer Lifetime Value prediction model to help the Marketing team identify the lifetime value of a customer by comparing the profitability and cost per action (CPA) data. Tableau dashboards were also created for them to visualize the data and identify customer buckets responsible for high loss.
The Marketing team can better understand the customer journey and identify the right target groups of customers. In turn, increasing customer retention rates by evaluating the current and the future value of the customers and identifying the types of insurance policies that lead to customer retention.
Result
- Improved customer targeting
- Enhanced business decisions
- Minimized revenue loss
