Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data

ArXiv ID: ssrn-2701093 “View on arXiv”

Authors: Unknown

Abstract

The growth of subscription-based commerce has seen a change in the types of data firms report to external shareholders. More than ever before, companies are dis

Keywords: Subscription Economics, Financial Reporting, Corporate Disclosure, Revenue Recognition

Complexity vs Empirical Score

• Math Complexity: 4.5/10
• Empirical Rigor: 6.5/10
• Quadrant: Street Traders
• Why: The paper employs moderate statistical modeling (e.g., retention, acquisition models) and valuation mathematics (DCF) but is heavily grounded in applying these models to real-world, publicly available data from companies like Dish Network and Sirius XM, focusing on practical implementation and backtesting against disclosed metrics.

  flowchart TD
    A["Research Goal: Value Subscription Businesses Using Public Customer Data"] --> B{"Key Methodology"}
    B --> C["Data: Public Disclosures<br/>Subscribers, Churn, ARPU, LTV"]
    C --> D["Computational Model<br/>Discounted Cash Flow DCF"]
    D --> E["Estimate Customer Lifetime Value<br/>Model Revenue & Churn Dynamics"]
    E --> F["Key Findings/Outcomes"]
    F --> G["1. Methodology improves valuation transparency"]
    F --> H["2. Public data can approximate internal metrics"]
    F --> I["3. Non-GAAP metrics are value relevant"]