Valuing Subscription-Based Businesses Using Publicly Disclosed Customer Data
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"]