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Media verified Verified Outcome TRL 9

Propensity-to-Pay Engagement Modeling

domain Client: A leading international financial newspaper handshake Provider: Internal Build (Data Science) schedule Deploy: Q4 2023 (Review)
88 Impact
Enterprise Ready
Evidence Score: 5/10
Strength: High

Executive Summary

ANALYST: COI RESEARCH

Moving from an advertising-led to a subscription-led model, the publisher developed a proprietary metric called 'RFV' (Recency, Frequency, Volume). This engagement score predicts a user's likelihood to subscribe or churn. The data feeds dynamic paywalls that tighten or loosen access based on the user's predicted value.

rate_review Analyst Verdict

"A best-in-class implementation of predictive analytics in media. By focusing on a single 'North Star' metric (RFV) rather than vanity metrics (page views), the entity successfully navigated the digital transition, achieving over 1 million paying subscribers."

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Full Audit Report Available Includes Risk Register, Technical Specs & Compliance Data.

warning The Challenge

The decline of print advertising revenue necessitated a shift to digital subscriptions. However, a rigid 'hard paywall' deterred casual readers, while a porous 'metered paywall' was easily circumvented. The publisher needed a way to identify high-value prospects and target them specifically.

psychology The Solution

The data science team built a propensity model analyzing user behavior (time spent, articles read, device usage). This model assigns an 'RFV' score to every cookie. High-scoring non-subscribers are presented with subscription offers, while low-scoring users might see more free articles to build habit.

settings_suggest Technical & Deployment Specs

Integrations
Subscription Management System (Zuora), CRM
Deployment Model
On-Prem / Cloud Hybrid
Data Classification
Behavioral / Transactional
Estimated TCO / ROI
Medium
POC Summary (2015-01-01 to 2016-01-01)

"Initial testing of RFV metric correlation to churn."

shield Risk Register & Mitigation

Risk Factor Severity Mitigation Strategy
Model Decay Medium Regular retraining of propensity models to account for changing reading habits.
Cookie Deprecation High Shift to first-party registration strategy.

trending_up Impact Trajectory

Audited value realization curve

Growth to >1 million paying subscribers Verified Outcome
Primary KPIThreefold increase in digital subscription revenue
Audit CycleReduction in acquisition cost (CPA) via targeted friction

policy Compliance & Gov

  • Standards: GDPR
  • Maturity (TRL): 9
  • Evidence Score: 5/10
  • Data Class: Behavioral / Transactional

folder_shared Verified Assets

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Verified Case Study
PDF • Version 1
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Technical Audit
PDF • Audited
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Security Architecture

The "Blind Verification" Protocol

How we verified these outcomes for A leading international financial newspaper without exposing sensitive IP or identities.

Private
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1. Raw Evidence

Audit ID: #PRIV-766
Evidence: Direct SQL Logs
Public
public

2. Verified Asset

Outcome: Verified
Ref ID: #COI-766

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