Data Interview Question

Estimating Customer Lifetime Value for Subscription Models

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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.