Maximize LTV, Minimize Churn
See which acquisition channels bring subscribers who stick. AI that learns your retention patterns and predicts LTV within 8% accuracy.
Subscription Growth Has a Retention Problem
You're optimizing acquisition while churn silently erodes your unit economics. The real question isn't how many subscribers you get, it's how many stay.
High CAC on low first-order value
Subscription economics depend on retention, but you're acquiring based on first-purchase metrics. CAC payback periods are invisible.
Churn eats into LTV projections
Your LTV models assume steady retention, but real cohort decay is nonlinear. Month 3 and month 6 are cliff edges you can't predict with spreadsheets.
Hard to separate trial from loyal
Promo-driven subscribers look identical to organic ones at acquisition. By the time you know who sticks, you've already optimized for the wrong audience.
Channel-level LTV is a black box
You know overall LTV. You don't know LTV by acquisition channel. Meta subscribers might retain 2x better than TikTok, but you're treating all channels equally.
Four Agents That Learn Your Retention Patterns
AI that understands subscription economics, not just ad metrics. Learns which acquisition strategies drive lasting subscribers.
Felix
Forecast IntelligenceLearns your cohort decay curves and seasonal retention patterns. Predicts subscriber LTV by channel within 8% accuracy after 90 days.
- LTV forecasting by acquisition channel and cohort
- Cohort decay modeling that learns YOUR retention curves
- Revenue forecasting factoring in churn rates
- Accuracy improves 78% → 91% → 95%+ over time
Parker
Performance & AttributionShows which channels bring subscribers who stick vs. ones who churn after trial. True incremental subscriber acquisition, not platform-inflated numbers.
- Incremental subscriber attribution by channel
- Separates promo-driven from organic subscribers
- True CAC per retained subscriber, not just acquired
- De-biases platform self-reported conversion data
Sam
Scenario PlanningModel the LTV impact of shifting acquisition spend before committing budget. Test whether TikTok subscribers retain as well as Meta subscribers.
- Simulate channel mix changes with LTV projections
- Model promo vs. full-price acquisition trade-offs
- Test scaling scenarios with retention-adjusted ROAS
- Compare strategies with confidence intervals
Dex
Delivery & AlertsCatches churn spikes and retention anomalies in real-time. Auto-delivers cohort reports to Slack and Sheets.
- Real-time churn spike detection
- Automated cohort retention reports
- Alerts when CAC payback period exceeds threshold
- Delivers insights to Slack, Sheets, and email
Also includes Maya (memory), Dana (data), and Olivia (creative) — meet all 7 agents →
Your Subscription Metrics, Transformed
Flat LTV assumptions across all channels and cohorts. Surprised when retention drops.
Felix models per-channel, per-cohort decay curves. LTV predictions within 8%.
Optimize for lowest CAC. No idea which subscribers actually retain.
Parker shows retention-adjusted CAC. Optimize for subscribers who stick.
Treat all channels equally. Discover retention differences months later.
Sam models retention-adjusted ROAS by channel before spending.
Notice cohort degradation in monthly review. Weeks of wasted acquisition spend.
Dex catches churn spikes in real-time. Alerts before damage compounds.
Subscription Metrics That Move
Frequently Asked Questions
Felix learns your cohort decay curves and identifies which acquisition channels bring subscribers who retain vs. churn after trial. Parker shows true incremental subscriber value by channel, so you can shift budget to sources that drive lasting customers.
Yes. Felix models per-channel, per-cohort LTV using your actual retention data. After 90 days of learning, LTV predictions are within 8% accuracy, factoring in your specific decay patterns rather than industry averages.
Parker's attribution model tracks subscriber quality by source, distinguishing promo-driven from organic acquisitions. This reveals retention gaps of 2-3x between subscriber segments, letting you optimize for quality over volume.
Cresva integrates with Shopify and its subscription ecosystem. Combined with Meta, Google, and TikTok ad data, it builds a unified view of acquisition cost through retention and LTV.
Connect in ~5 minutes via OAuth. First cohort insights in 48 hours. Retention-adjusted LTV predictions within 90 days as the system learns your specific decay curves.
See It Learn Your Retention Curves
30-min demo with your subscription data. Live.