Your churn dashboard tells you what happened — not why, and not what to do about it
A structured analysis of your churn cohorts, voluntary vs involuntary split, and lifecycle drop-off points — with a prioritized retention plan built on leading indicators you can actually intervene on before customers leave.
You know your churn rate. You don't know your churn cause.
Churn rate is a lagging indicator. By the time it shows up in your dashboard, the customers are already gone. The companies that reduce churn consistently aren't reacting to the number — they're acting on the signals that precede it.
Voluntary and involuntary churn look the same in your reports
Failed payments (involuntary churn) and deliberate cancellations (voluntary churn) require completely different interventions. Dunning sequences fix the first. Product, pricing, or experience changes fix the second. Running the wrong playbook on either is wasted effort.
You don't know when in the lifecycle customers are leaving
Churn that happens in month one has a different cause than churn at month six or month twelve. Without cohort-level analysis, you can't identify the moment in the customer lifecycle where retention breaks down — and you can't build an intervention for a moment you haven't identified.
Your retention efforts are generalized instead of targeted
Check-in emails, discount offers, and success calls sent to everyone are the sign of a retention strategy without a churn model. Targeted interventions sent to customers showing specific leading indicators of churn outperform blanket campaigns at a fraction of the cost.
What you walk away with
A cohort-level analysis of when and why customers leave, a model of the leading indicators that precede churn, and a prioritized retention plan built around interventions you can actually execute.
Pre-Session Questionnaire & Data Review
You complete a structured intake and share access to your subscription data, churn cohorts, product usage data, and any exit survey responses. I review the raw data before the kickoff call to identify the patterns worth digging into.
Kickoff + Delivery
A 30-minute kickoff call to align on your customer segments, your current retention metrics, and which churn questions are most urgent. I conduct the full cohort analysis between calls. A 60-minute delivery call to walk through the churn model, the leading indicators, and the retention plan.
Churn Analysis & Retention Plan
A written document covering: voluntary vs involuntary churn breakdown and dunning recommendations, cohort-level analysis showing when in the lifecycle customers leave, the leading behavioral indicators that precede churn, and a prioritized retention plan with specific interventions ranked by expected impact. Session transcript included.
Three steps from churn rate to retention plan
Two calls bracketing the cohort analysis. From raw subscription data to a prioritized retention plan in under two weeks.
You share your subscription and usage data
After booking, you complete a structured questionnaire and share access to your subscription data, cancellation records, and product usage data. The more granular the data, the more specific the leading indicators we can identify.
We align on segments and churn priorities
A 30-minute kickoff call to confirm your customer segments, your current churn rate and trend, and which retention questions are most pressing. I then conduct the full cohort analysis and build the churn model between calls.
You get a model and a plan
A 60-minute delivery call to walk through the cohort analysis, the leading indicators, and the specific retention interventions. The written retention plan follows within 48 hours — prioritized by expected impact, ready to brief your product and success teams.
Sound like your situation?
Churn analysis matters most when you have enough history to see patterns — typically 6+ months of subscription data with meaningful cancellation volume. Here are the most common situations.
"Our churn rate has been creeping up for two quarters and we can't explain why"
Gradual churn increases are usually structural — a product gap that's widening, a pricing change that's wearing on customers, or a competitive alternative that's getting better. This engagement identifies which structural cause is driving the trend and what to do about it.
"We're losing customers in the first 90 days and we can't tell if it's activation or fit"
Early churn is usually either an activation problem (customers didn't reach value fast enough) or a fit problem (the wrong customers are signing up). Cohort analysis separates the two — and the fix is different depending on which it is. Getting this wrong means fixing the wrong thing.
"We suspect a lot of our churn is failed payments but we haven't quantified it"
Involuntary churn from failed payments is recoverable — but only if you have a dunning sequence designed to recover it. If you haven't separated it from voluntary churn, you may be spending retention resources on a problem that dunning and payment recovery logic would solve more efficiently.
"We're spending on customer success but we can't measure whether it's reducing churn"
Customer success spend without a churn model is hard to justify. This engagement builds the model — identifying which customer behaviors predict churn, which segments are at highest risk, and whether your current success activities are reaching the right customers at the right time.
One analysis. A retention plan built on leading indicators.
Reducing churn by 1% on $1M ARR is $10,000 in recovered revenue — compounding every month. This engagement costs $1,800 and typically surfaces interventions worth multiples of that in the first year of implementation.
Churn & Retention
30-min kickoff + 60-min delivery call
- Pre-session questionnaire + review of subscription and usage data
- Voluntary vs involuntary churn separation and dunning gap analysis
- 30-minute kickoff call to align on segments and churn priorities
- Full cohort analysis conducted between calls
- 60-minute delivery call to walk through findings and retention plan
- Written report: churn cohort analysis, leading indicator model, prioritized retention interventions
- Session transcript included
Frequently asked questions
What makes you qualified to analyze churn and retention?
I've worked on retention and churn reduction across multiple B2B SaaS products — including subscription lifecycle management at 3dcart, payments and involuntary churn recovery at Shift4, and customer retention strategy at Gorgias. I approach churn analysis empirically: start with the cohort data, separate voluntary from involuntary, identify when in the lifecycle the drop happens, and build interventions around leading indicators rather than lagging ones. The goal is a model you can act on before customers decide to leave.
Can we sign a mutual NDA before you review our subscription data?
Yes — happy to sign a standard mutual NDA before you share revenue data, subscription records, or cohort information. I can send a short one or sign yours. Just request it during scheduling.
What data do you need before the kickoff call?
The most useful inputs: subscription start and end dates by customer (exported from your billing system), cancellation reasons if you collect them, product usage data by customer if available (login frequency, feature usage), and your current MRR and churn rate trend. If you use Stripe, Chargebee, or Recurly, an export covers most of what I need. We can work with whatever level of granularity you have.
We're a small team — do we have enough data for cohort analysis to be meaningful?
Cohort analysis is most useful with 6+ months of data and meaningful cancellation volume — typically 20 or more cancellations across the period. Below that, patterns are hard to distinguish from noise. If you're early-stage with limited cancellation history, the engagement can still produce a voluntary vs involuntary breakdown, a dunning audit, and early warning indicator recommendations — just with lighter cohort depth. Note this in the questionnaire and I'll calibrate accordingly.
Should I do Churn & Retention or Customer Feedback & CX first?
If churn is the primary concern and you have subscription data to analyze, start here. The churn analysis will surface feedback patterns as a component — you'll see which product gaps and experience failures correlate with cancellations. Customer Feedback & CX goes deeper on the qualitative side and is most useful when the churn analysis has identified friction points but you need more specificity on what's driving them.
Can I get follow-up help implementing the retention plan?
Yes. Retention improvements compound over time — the interventions in the plan will perform better as you iterate based on what the data shows. The most common next step is B2B SaaS Advisory, starting at $750/month, for ongoing input as you implement and measure the interventions.
How soon can we meet after I book?
Usually within one to two weeks. I schedule the kickoff call within 5–10 days of receiving your questionnaire and data. The delivery call follows 5–7 days after the kickoff.
Find out why customers leave before they decide to
One analysis. Leading indicators. A retention plan built on what the data actually shows.