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Do I need ModernLTV for my business?

As a B2C subscription business, deeply understanding your customers is mission critical to combatting churn and retaining revenue. But it's much easier said than done. That's why ModernLTV is here to help.

Zack Babin
February 23, 2024
5 minutes

Powered by proprietary intelligence and purpose-built for marketing and business teams, ModernLTV unifies customer data, unlocks predictive insights, and automates critical workflows to combat churn and maximize LTV — without a single line of code. Let's start with the highlights of the platform:

  • Unified customer data with zero code

  • Proprietary, revenue-driven intelligence

  • Purpose-built for subscription businesses

Below is a side-by-side comparison of the current solutions:







Largely descriptive analytics

Comprehensive and high performance

Descriptive, focused on payments

Descriptive, focused on payments

Predictive & descriptive


Low code, requires engineering

Requires significant development

Low code, requires engineering

Requires significant development

Zero engineering required


Large businesses, enterprise

Large businesses, enterprise

Small to medium businesses

Medium to large businesses

Small to medium businesses

vs. Customer data platforms (CDPs)

Example: Segment, Tealium, HighTouch, Hubspot

While these platforms can serve as the source of truth for your customer data, they offer limited to no predictive intelligence to combat churn and require ongoing engineering support.


  • Unifies all your customer data in one place
  • Low code integration
  • Integrates with all downstream tools


  • Requires on-going engineering resources
  • Focused on user identity resolution, not intelligence
  • Cost increases as customer base scales

vs. AI / ML platforms (MLaaS)

Example: Pecan AI, Retina AI

These platforms offer AI/ML models as a service, allowing data teams to eliminate the time-consuming steps of building and training a model and focus on the aspects that differentiate their product.


  • Increases speed of model development
  • Access to high performance, battle-tested models
  • Improves productivity of data science teams


  • Built for highly technical users
  • Onboarding requires time & development
  • Limited utility or application across business

vs. Retention tools (RaaS)

Example: Butter Payments, Churn Buster, RedFast, FlexPay

These platforms do offer value-added solutions for specific types of customer churn (e.g. payment failures), but have limited predictive capabilities that allow you to combat churn before it happens.


  • Low code integration
  • Offer configurable dunning logic
  • Whitelabel UI for cancellation flows


  • Targets payment failures, a small percentage of churn
  • Limited insights to predict churn before it happens
  • Requires some engineering resources

vs. Subscription management (SSaaS)

Example: Stripe Billing, Recurly, Recharge, Bold

Every business needs to collect and process payments and many subscription businesses choose to layer on Recurly, Recharge, etc to handle all the subscription-related functionality. That said, while they provide off-the-shelf payment recovery solutions, they don't have nearly the range of functionality to comprehensively address customer churn.


  • Handles all subscription management
  • Source of truth for customer churn
  • Off-the-shelf payment recovery features


  • Requires engineering resources
  • Focused on payment infrastructure, not intelligence
  • Handles payment failures, a small percentage of churn