Most SaaS founders can quote their latest MRR screenshot from memory, yet their eyes glaze over when you ask about failed charges and recovery.
I get it, staring at billing logs is not nearly as exciting as shipping a new onboarding flow or posting that smug revenue chart on social.
However, your mrr lost to failed payments might quietly equal a full growth channel that you never even budgeted for.
If that sounds dramatic, that is because money quietly walking out the door tends to deserve drama.

The tricky part is simple to describe and surprisingly annoying to track without a plan.
Invoices fail for reasons that feel random and deeply boring, from expired cards to fraud rules on perfectly normal customers.
Over weeks, the trickle adds up, and then you wake up one quarter wondering why MRR feels flatter than your acquisition numbers suggest.

Why failed payments are a silent churn engine

When people talk about churn, they usually speak about customers who actively cancel.
Those users log in, click the cancel button, maybe leave a grumpy comment, and then disappear forever.
You see that churn in your dashboards immediately, so everyone talks about it, sometimes a bit too much.

What sits in the shadows is involuntary churn driven by failed payments.
These are customers who would happily stay, but their bank or card sabotages the relationship.
If your dunning logic and follow up are weak, that customer vanishes, and it feels like bad luck instead of preventable revenue loss.

From a finance angle, mrr lost to failed payments behaves like a quiet tax on growth.
You invest in marketing, onboarding, and product, yet a percentage of that hard earned revenue evaporates.
As a founder, I would rather argue with a tough customer than lose a happy one to a random bank rule.

The three core numbers you must understand

Before you can recover lost mrr, you need a clean way to measure the leak.
That means turning vague billing anxiety into three very concrete metrics that anyone on the team can read.

Those three metrics are straightforward, and you probably already have the raw data somewhere.

  1. Invoices at risk

  2. Failed payment recovery rate

  3. Recovered MRR compared to at risk MRR

Once you track these consistently, the conversation shifts from “payments are messy” to “we improved recovery by several points this month.”
That shift alone can justify better tooling, sharper copy, and a simple culture change around billing hygiene.

What “invoices at risk” really means

Let us start with invoices at risk because everything else flows from that number.
An invoice at risk is any subscription invoice that has failed at least once and still has the potential to recover.
These invoices sit in a limbo state, usually marked as unpaid, past due, or something similarly ominous in your billing system.

A simple working definition looks like this in plain language.
Invoices at risk equals all subscription invoices this month that failed and remain unpaid, minus any that you have already written off or cancelled.
Basically you are counting active customers whose latest charge did not go through and still might be saved.

To get a usable figure, you usually want two slices.

  • Count of invoices at risk

  • Total MRR value represented by those invoices

If you run this once, you get a scary snapshot.
If you run it every week, you get motion, and motion is where you can do something smart.

How to calculate invoices at risk in practice

In most billing setups you only need a simple query or filtered export.
You look for all subscription invoices in a specific date range with a status like failed, past due, or unpaid.

From there, you exclude cancelled subscriptions and any invoices you already marked as bad debt.
What remains is your current stack of invoices at risk along with the corresponding MRR value.
When I did this the first time for a product, the team quietly stopped joking for a moment, which tells you something.

Once you know that number, you can set a baseline.
For example, invoices at risk this month equals ten thousand in MRR, which might represent three percent of your total.
That baseline will frame every improvement you make with better dunning emails and smarter recovery flows.

Understanding your failed payment recovery rate

Next, you need to know how well you actually recover from those failures.
The failed payment recovery rate tells you what percentage of at risk invoices eventually get paid within a chosen time window.

In simple terms, the formula is straightforward.
Failed payment recovery rate equals recovered invoices during the window divided by total invoices that went at risk during that same window, multiplied by one hundred.
You choose the window based on your billing rhythm, often thirty or sixty days for subscription products.

This single percentage reveals a lot about your operations.
If recovery is high, your emails, retries, and support workflows probably do their job.
If recovery is low, you are leaving obvious money on the table, which should irritate every founder with a calculator.

Why recovered MRR versus at risk MRR matters more than emotion

Emotionally, a failed charge feels bad, and a recovered one feels good.
Unfortunately, feelings do not show up on your revenue chart, so you need a clean ratio.

Recovered MRR versus at risk MRR simply compares the value you saved to the value that was threatened.
The formula reads like this in normal language.
Recovered MRR rate equals total MRR recovered from previously failed invoices divided by total MRR that was at risk in that same period.

If you had ten thousand in MRR at risk, and you eventually recovered six thousand of it, your recovered MRR rate sits at sixty percent.
That number tells you that your payment recovery analytics are moving beyond vibes into something your finance team will actually respect.
As someone who has stared at ugly spreadsheets late at night, I can confirm that respect is deserved when you lift that rate even a little.

A simple workflow to measure mrr lost to failed payments

Now let us put the pieces together into a repeatable routine.
You want a monthly rhythm that does not require hero projects or complicated manual tracking.

A practical workflow could look like this.

  • Pull all invoices that failed at least once during the month and remain unpaid

  • Sum the MRR on those invoices to find total MRR at risk

  • Track which of those invoices eventually get paid inside thirty or sixty days

  • Sum recovered MRR and count recovered invoices

  • Calculate failed payment recovery rate and recovered MRR rate from those totals

Once you run this for a few months, you will see trends.
You might notice that recovery drops when you skip dunning emails, or rises after you improve subject lines.
This is the moment where recover lost mrr stops being a vague goal and becomes a measurable lever in your funnel.

How Revello turns recovery analytics into a live dashboard

Doing these steps once in a spreadsheet feels fine, although slightly boring.
Doing them every month by hand becomes exactly the sort of chore that busy teams quietly postpone.

Revello connects to your Stripe account and treats recovery as a first class concept.
In the recovery analytics view, you see invoices at risk, failed payment recovery rate, and recovered MRR versus at risk MRR in one place.
Instead of stitching together exports, you get a dashboard that updates as Stripe events come in.

You can still export raw data if your finance team loves their spreadsheets, which many do, and I say this with affection.
The key difference is that the heavy lifting lives inside Revello, not on some abandoned tab in a shared drive.
You plug in your email flows, set your retry logic, and watch the recovery curves move instead of guessing.

Using data to improve your failed payment flows

Once the numbers sit in front of you, you can start experimenting with confidence.
Rather than rewriting every email blindly, you can target specific weak points.

For example, if invoices at risk spiked this month, you might investigate whether new card types are failing more often.
If recovery lags for annual plans, maybe those customers need clearer invoices and friendlier explanations for large charges.
You are no longer arguing over opinions; you are responding to live patterns in your recovery analytics.

Over time, several levers usually make the biggest difference.

  1. Clearer copy in failed payment emails with direct update links

  2. Sensible retry schedules that respect bank rules and user patience

  3. Easy access to a billing portal where customers can update details themselves

  4. Human support for complex or high value accounts that justify deeper attention

Each tweak changes the shape of your mrr lost to failed payments curve.
By watching the dashboard in Revello, you relate those tweaks directly to recovery rate changes, which keeps everyone focused.

Conclusion: stop guessing and start measuring the leak

If you never measure mrr lost to failed payments, it simply blends into general churn noise.
Your team blames the market, competition, or product gaps, while quiet card failures steal a predictable slice of revenue.
The moment you break out invoices at risk, recovery rate, and recovered MRR, the problem becomes solvable.

With Revello doing the tracking and the automation, you spend less time chasing spreadsheets and more time improving flows.
You understand exactly how much revenue sits at risk today, how much you saved, and where you still need work.
That level of clarity turns failed payments from an annoying surprise into another growth lever you can actually control.

And if you ever feel depressed looking at those failed invoices, just remember that even the banks occasionally fail at collecting their own fees.