Estimating Customer Lifetime Value for Subscription Models

Requirements Clarification & Assessment

1. Understanding the Business Model:

   • Identify the subscription model types (monthly, yearly, etc.).
   • Determine the billing cycle and any discounts or promotions offered.
   • Recognize the churn rate and its impact on LTV.

2. Data Collection:

   • Customer Demographics: Age, gender, location, etc.
   • Subscription Details: Plan type, start and end dates, payment history.
   • Usage Patterns: Frequency of service use, engagement metrics.
   • Financial Data: Revenue per customer, discounts, refunds.
   • Churn Data: Historical churn rates, reasons for churn.

3. Objective Clarification:

   • Define what constitutes "lifetime" for the business: 1 year, 3 years, etc.
   • Determine the acceptable accuracy level for LTV predictions.
   • Identify stakeholders and their expectations from the LTV model.

4. Technical Requirements:

   • Availability of historical data and its quality.
   • Tools and platforms for data analysis (e.g., Python, R, SQL).
   • Reporting and visualization tools for presenting insights.

5. Constraints:

   • Data privacy and compliance regulations.
   • Budget and time constraints for model development.