Your MRR isn't just churning. It's bleeding.
I worked with a dozen SaaS founders and every single one was treating two different problems as one, so I built Recurflux.
Over the last couple of years I worked with a bunch of SaaS founders in the $30k-$100k MRR range. Different products, different markets, different processors. But I kept running the same numbers and kept landing in the same place.
Cards failing at the processor level. Roughly 2% of MRR every month, failing silently. No alert, no email, nothing.
The subscription just... stops. At $50k MRR that's $1,000/mo gone. About $630 of it recoverable in 72 hours if the retry logic is actually tuned to the failure code. Most of the time it wasn't.
Then cancellations on top of that. $1,500/mo of MRR walking to the cancel button every month at that same scale. No intercept, no pause offer, nothing between the customer and the door. About $450 of that saveable if something was in the way.
So $1,080/mo. Leaking. Every month. And every single founder was calling it "churn" and blaming the product.
That's what got me. Not one client. All of them. Same misdiagnosis, different company.
So I looked at the tools. Properly this time.
Churnkey is genuinely good for cancellation flows. But it's $250+/mo and does nothing when a card fails silently. Churnbuster and Stunning handle the dunning side. But they do nothing when a customer actually hits cancel. To get full coverage today you're paying $250+ for one problem and $200+ for the other.
$450+/mo. For both halves of the same problem.
And honestly, that price makes no sense for a founder at $50k MRR where the whole point is that the tool should cost a fraction of what it recovers. There was just... nothing there. Nobody doing both at a price that fit.
So I built Recurflux.
A cancellation flow that sits in front of the cancel button. Reason survey first, then a tailored offer based on why they're actually leaving - pause, discount, downgrade, whatever fits. No engineering on your end. The pause option specifically changes the math a lot: paused customers resume at 40-60%. Win-back after they've already cancelled is 10-15%. Catching them before they leave is a completely different situation.
Smart retry logic tuned to 30+ specific decline codes. Not the same retry on a timer. insufficient_funds on a Tuesday morning hits differently than do_not_honor, the timing and approach need to be different. Retry count matters less than retry logic.
Card health monitoring that scans every active subscription for cards expiring in the next 30 days and sends a branded update link before the charge runs. The failure never happens. No dunning needed, no retry wasted.
than retry logic.
Card health monitoring that scans every active subscription for cards expiring in the next 30 days and sends a branded update link before the charge runs. The failure never happens. No dunning needed, no retry wasted.
A dispute rate monitor tracking your rate against Visa and Mastercard thresholds in real time. Most founders find out they're near breach when the formal letter arrives. This one alerts before that.
And it works across Stripe, Paddle, Razorpay, and RevenueCat for mobile. Every other tool I found picks one processor.
If you're on Paddle or building a mobile subscription on RevenueCat, you basically have nothing right now. That gap kept coming up with clients too.
I'm looking for 3 founders to connect their processor, pull 90 days of real recovery and retention data, and share the results as a case study.
In return: code EARLY40 at checkout - 40% off, so $35/mo instead of $59, plus direct access to shape what gets built next. Your feature requests go to the top of the queue. That access goes away once I'm past 10 customers.
Plug in your MRR and processor, it'll show you exactly what's leaking and how much is recoverable:
https://recurflux.com/resources/recovery-calculator
What stands out to me here is how dangerous aggregated metrics can become once multiple failure states collapse into the same label.
Most founders see “churn” on a dashboard and instinctively treat it like one operational problem, when in reality they are often looking at completely different mechanisms stacked together:
The moment those all compress into one number, decision quality starts degrading because teams optimize against the label instead of the mechanism creating the label.
That is why the “same misdiagnosis, different company” line hits so hard.
You are not just recovering revenue here. You are restoring distinction inside the metric itself.
This is a sharp wedge because you’re separating two failures most founders lazily bucket together as “churn.”
A cancelled customer and a recoverable payment failure are not the same problem, and treating them the same usually leads to bad decisions on product, support, and retention.
The card-health piece is especially strong. Preventing the failure before dunning even starts is a much better story than just saying “we retry smarter.”
I’d be curious which insight resonates more in sales conversations:
You found a real leak most founders misclassify.
The strongest part here is not “reduce churn.”
It’s separating silent revenue failure from actual customer dissatisfaction.
Those are completely different operational problems and most founders absolutely blend them together.
But the interesting part is the product already feels more infrastructure-grade than the current brand frame.
Recurflux explains the motion, but it still sounds slightly like a recovery plugin.
The product itself is moving closer to revenue infrastructure:
retry intelligence,
processor-layer recovery,
subscription health monitoring,
dispute threshold protection,
cross-processor retention logic.
That’s a much heavier trust category.
Especially once you start selling into larger SaaS teams, the naming layer starts carrying more weight than most founders expect in billing/revenue tooling.
Something like Exirra.com or Davoq.com would hold that positioning far more naturally than Recurflux if the product keeps expanding deeper into subscription infrastructure.