Retail/Consumer

Subscription Churn Data

Buy and sell subscription churn data data. Who cancels, when in their lifecycle, and what they say on the way out. Every subscription business needs churn benchmarks.

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Overview

What Is Subscription Churn Data?

Subscription churn data captures which customers cancel their subscriptions, at what point in their lifecycle, and their reasons for leaving. This dataset includes user-specific information such as joining dates, payment history, device usage, plan duration, and subscription expiration dates. For subscription businesses, churn data is essential for understanding customer retention patterns, identifying at-risk segments, and benchmarking performance against industry peers. The median churn rate across all subscription business verticals in 2024 was 7.44%, though rates vary significantly by vertical, geography, and business model.

Market Data

7.44%

Median Churn Rate (All Verticals)

Source: Slicker / Subbly

41.3%

Disney+ Non-Renewal Rate (Sample)

Source: ResearchGate

28–35%

Involuntary Churn in Beauty Boxes

Source: Slicker

25–30%

Involuntary Churn in Fitness Subscriptions

Source: Slicker

$200M+ (year-over-year)

Reactivation Revenue from Paused Subscribers

Source: Recurly / Slicker

Who Uses This Data

What AI models do with it.do with it.

01

Subscription Box & Replenishment Services

Retailers selling consumable subscriptions (beauty boxes, pet supplies, food) use churn data to identify cart-abandonment patterns, payment failures, and seasonal drop-offs. Replenishment and curated box services show superior retention rates and are key buyers of competitive benchmarks.

02

Streaming & OTT Platforms

OTT and digital content businesses analyze churn to understand engagement and perceived value. Digital content models show the highest top-quartile churn (16.7%), making churn data critical for optimizing content strategy and pricing.

03

Fitness & Wellness Subscriptions

Fitness subscription providers use churn data to track involuntary churn from card expiry and payment issues (25–30% involuntary churn), and voluntary churn from seasonal disengagement. Localized retention strategies are essential given geographic variations.

04

SaaS & Membership Platforms

Membership and B2C SaaS businesses leverage churn data to benchmark retention, segment by cohort lifecycle, and optimize pricing. Memberships boast the lowest churn rates, while subscription boxes have the highest.

What Can You Earn?

What it's worth.worth.

Benchmark Reports & Vertical Analysis

Varies

Aggregated churn benchmarks by vertical, business model, and geography. High demand from mid-market merchants ($0–$10MM revenue).

Granular Cohort Data (Lifecycle Churn)

Varies

Customer-level churn data by join date, plan duration, and payment history. Premium for high-volume datasets with rich feature flags.

Involuntary Churn Intelligence

Varies

Payment failure data, card expiry rates, and churn reason attribution. Critical for retry engine optimization and payment processors.

Geographic & Seasonal Churn Patterns

Varies

Regional churn variations and month-over-month trends (e.g., Q1 spike post-holiday). Localization strategy data commands premium.

What Buyers Expect

What makes it valuable.valuable.

01

Accurate Lifecycle Dates

Buyers require precise join dates, last payment dates, plan durations, and calculated expiration dates. Data integrity is critical for survival curve and cohort analysis.

02

Rich Churn Attribution

Churn reason labeling (involuntary vs. voluntary, primary failure cause) is highly valued. Datasets that distinguish between payment failures, card expiry, and true engagement churn command premium pricing.

03

Vertical & Model Segmentation

Buyers expect data segmented by subscription model (replenishment, boxes, access, content), vertical (beauty, fitness, SaaS), and geography. Unsegmented data is of lower value.

04

Privacy & Compliance

All datasets must comply with GDPR, CCPA, and payment processor requirements. PII must be hashed or anonymized. Buyers verify encryption and audit trails.

05

Scale & Freshness

Datasets covering thousands of merchants and updated monthly or quarterly are most valuable. Trailing data (3–12 months) is preferred for trend analysis.

Companies Active Here

Who's buying.buying.

Subscription Management Platforms (Subbly, Recurly, Stripe Billing)

Aggregate churn benchmarks from thousands of merchants to create comparative reports and identify best practices by vertical and geography.

Payment & Retry Engines (Slicker, etc.)

Purchase involuntary churn data to train AI-driven retry mechanisms and card update workflows. Use vertical-specific churn breakdowns to optimize retry success rates.

Streaming Platforms (Disney+, Netflix, et al.)

Analyze competitor and internal churn data by geography, device, subscription tier, and audience segment. Use machine learning to predict high-risk cohorts.

Direct-to-Consumer (D2C) Retailers

Benchmark churn against peers in their vertical (beauty, pet, replenishment). Identify seasonal patterns and pricing elasticity to optimize retention budgets.

FAQ

Common questions.questions.

Is there a correlation between subscription price and churn?

No. Churn data reveals virtually no correlation between Average Order Value (AOV) and churn rates—customers are equally likely to maintain a $10/month subscription as a $100/month one. Factors like market positioning, targeting accuracy, and perceived value matter far more than price alone.

What is involuntary vs. voluntary churn?

Involuntary churn occurs due to payment failures (expired cards, insufficient funds, billing address changes) and accounts for 15–35% of total churn depending on vertical. Voluntary churn reflects true disengagement. Involuntary churn is recoverable through retry engines and automated card updates.

Which subscription models have the lowest churn?

Memberships show the lowest churn rates, while replenishment services and curated boxes demonstrate superior retention compared to digital content (16.7% top-quartile churn) and access subscriptions. Geography and localized retention strategies also significantly impact churn.

How can I use churn data to improve retention?

Segment churn by cohort lifecycle, vertical, geography, and payment method. Identify seasonal patterns (e.g., Q1 post-holiday spikes, lower September churn). Invest in platform feature adoption and pricing optimization tailored to local markets. Implement AI-driven retry engines to recover involuntary churn—which can reduce churn by up to 40%.

Sell yoursubscription churndata.

If your company generates subscription churn data, AI companies are actively looking for it. We handle pricing, compliance, and buyer matching.

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