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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

on May 7, 2026
  1. 1

    "Blaming the product" for involuntary churn is one of the most expensive misdiagnoses in early SaaS. You build features nobody needed because the real problem was a Tuesday morning insufficient_funds hitting the wrong retry window. The tooling gap is real $450+/mo to cover both sides of one problem is just bad unit economics at this stage. Curious what your false-positive rate looks like on the pause offers wrong intercept at the wrong moment can accelerate the cancellation.

    1. 1

      We separate the two signals — billing failure and cancel intent get different treatments entirely. No overlap, no wrong-moment intercepts.

  2. 1

    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:

    • save failed payments
    • intercept cancellations
    • or the unified view that both are revenue leakage, just from different layers
    1. 1

      The unified view actually lands hardest because it reframes the conversation from "fix this one leak" to "you have two separate revenue drains and most of your stack is blind to one of them." Curious what your current setup looks like for catching payment failures before they even hit dunning, that tends to be where the biggest invisible losses are sitting. What does that layer look like for you right now?

  3. 1

    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.

    1. 1

      Appreciate the thought on positioning, and the infrastructure framing is something we think about a lot. That said, Recurflux is intentional. Founders immediately understand the motion, and in early GTM that recognition speed matters more than category prestige. As the product deepens, the brand earns its weight through the outcomes it delivers, not through a name that sounds heavy before it has proven it. What does your current revenue recovery stack look like?

      1. 1

        Yash, one thought from our Recurflux thread that stuck with me.

        I agree with your point that early GTM needs recognition speed. Recurflux explains the motion quickly, and that matters.

        The harder question is whether the current brand and landing-page frame will still carry trust once the buyer moves beyond founder-led SaaS into billing, finance, revenue ops, and risk-sensitive teams.

        That is where I think a focused positioning audit would be useful.

        Not a rename push. More like a buyer-trust audit for Recurflux: current name perception, category frame, revenue-infrastructure trust signals, where the copy may still feel like a recovery plugin, and how to make the product feel safer for larger SaaS teams without losing the simple early-GTM clarity.

        I’m doing a few focused naming/positioning audits at $99 while refining the format.

        For Recurflux specifically, I’d make it about keeping the name but strengthening the enterprise trust layer around it.

        If useful, connect here and I can give you a sharp outside read:

        https://www.linkedin.com/in/aryan-y-0163b0278/

      2. 1

        Fair. For early GTM, recognition speed does matter.

        I’m not running a revenue recovery stack myself. I’m looking at this from the positioning and buyer-trust side.

        The reason I pushed on the name is because billing infrastructure is one of those categories where the buyer is not just asking “do I understand it?”

        They’re also asking:
        do I trust this near revenue movement?

        Recurflux gives quick comprehension.
        That part works.

        The question is whether it keeps working once the buyer shifts from founder-led SaaS to larger teams where billing, finance, and risk all care about trust.

        That’s the layer I’d keep pressure-testing.

  4. 1

    This comment was deleted 20 days ago.

    1. 1

      Exactly this.Most teams are essentially trying to fix a broken engine by staring at the fuel gauge. Recurflux was built specifically to break that compressed "churn" label apart and surface which mechanism is actually firing, because the recovery action for a failed payment looks nothing like the one for an expectation mismatch. Would love to hear what failure state is costing your team the most right now.

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