How to Properly Track Your SaaS Churn?

Look, if you're reading this, you've probably already discovered that customer churn is eating into your revenue.

Maybe you're watching your MRR dashboard like it's a horror movie, or perhaps you just realized that "churn rate" means something completely different to your CEO than it does to your product team.

Here's the thing: most companies are tracking churn wrong.

Not because they're bad at math, but because they're measuring the wrong things, at the wrong times, for the wrong reasons.

Let's fix that.

Why Most Churn Metrics Are Lying to You

Before we dive into the "how," we need to talk about why your current churn number is probably misleading. Imagine you run a SaaS company.

In January, you had 100 customers.
By the end of January, 5 customers canceled.
Simple math says that's 5% churn, right?

WRONG. Or at least, incomplete:

• What if 3 of those customers were free trial users who never paid a dime?
• What if one of them was your biggest enterprise client paying $10,000/month, while the other was on a $29/month starter plan?
• What if two customers "churned" but actually consolidated accounts?
  

See the problem? A single percentage doesn't tell you much.

The Churn Metrics That Actually Matter

1. Customer Churn Rate vs. Revenue Churn Rate

Customer churn counts heads; revenue churn counts dollars.

Customer churn rate =

(Customers lost in period / Customers at start of period) × 100

Revenue churn rate =

(MRR lost in period / MRR at start of period) × 100

Let's say you lose 10 customers in a month out of 200 total. That's 5% customer churn. But if those 10 customers represented only $500 in MRR out of your $50,000 total, your revenue churn is just 1%.

Which matters more? Depends on your business model.

For enterprise SaaS: revenue churn is usually more important.
For consumer subscription apps: customer churn tells the real story.

Pro tip: Track both. Always. Services like ChartMogul and Baremetrics make this easy by automatically calculating both metrics from your payment data.

2. Gross Churn vs. Net Churn

Here's where it gets interesting. Gross churn is the raw number of customers or revenue you lost. Net churn factors in expansion revenue from existing customers.

Let's use real numbers:

• You start the month with $100,000 MRR
• You lose $5,000 MRR from churned customers (5% gross revenue churn)
• But your existing customers upgrade, adding $6,000 in expansion MRR
• Your net revenue churn is actually -1% (yes, negative churn!)
  

Companies like Slack and Snowflake have famously achieved negative net revenue churn by expanding within existing accounts faster than they lose customers. It's the holy grail of SaaS metrics.

But don't let negative net churn fool you into ignoring gross churn. If you're losing 20% of customers monthly but growing 25% through expansions, you're on a treadmill that'll eventually wear out.

3. Cohort-Based Churn Analysis

This is where tracking churn goes from basic to powerful.

Instead of looking at overall churn, break it down by when customers signed up. You might discover that customers who joined in Q1 2024 have 3% monthly churn, while Q4 2024 customers have 8% churn.

Why the difference? Maybe:

• Your product quality dropped
• You changed your onboarding flow
• You started attracting the wrong customer profile
• Your pricing shifted

Example structure:

• January 2024 cohort: 100 customers
  → Month 1: 95 remain (5% churn)
  → Month 2: 91 remain (4.2% churn)
  → Month 3: 88 remain (3.3% churn)
  
• February 2024 cohort: 120 customers
  → Month 1: 108 remain (10% churn) → etc.
  

If February's cohort is churning faster, you've got a problem that started in February.

Common Churn Tracking Mistakes (And How to Avoid Them)

Mistake #1: Not Defining "Active" Correctly

When does a customer actually churn? When they cancel? When their subscription ends? When they stop logging in?

For annual contracts, a customer who doesn't renew might have been "churned" in their mind for 6 months before the contract ended. You need leading indicators, not lagging ones.

Solution: Track engagement metrics alongside churn. Set up alerts in tools like Segment or Heap for customers who haven't logged in for 14 days, haven't used a core feature in 30 days, or whose usage has dropped by 50%.

Mistake #2: Ignoring Involuntary Churn

Credit cards expire. Banks flag suspicious transactions. People forget to update their payment info.

Research from ProfitWell suggests that involuntary churn accounts for 20-40% of total churn for many SaaS companies. That's insane when you think about it—up to 40% of your "churn" is customers who didn't even want to leave.

Solution: Implement dunning management. Services like Stripe's Smart Retries or Churn Buster automatically retry failed payments at optimal times and send customer-friendly emails to update payment methods.

Mistake #3: Using the Wrong Time Period

Monthly churn rates are standard, but they can hide problems. A 2% monthly churn rate sounds fine until you realize that compounds to 21.5% annual churn.

For businesses with annual contracts, calculating monthly churn doesn't even make sense. You need to track renewal rates instead.

Solution: Use the time period that matches your billing cycle and understand how churn compounds. The formula for annual churn based on monthly churn is: Annual churn = 1 - (1 - monthly churn rate)^12

Setting Up Your Churn Tracking System

Step 1: Choose Your Core Metrics

At minimum, track:

• Monthly customer churn rate
• Monthly revenue churn rate
• Net revenue retention (includes expansion)
• Cohort retention curves

Step 2: Pick Your Tools

For small teams (< 50 customers): A spreadsheet can work. Seriously. Track customer ID, signup date, plan value, and cancellation date.

For growing teams: Use ChartMogul, Baremetrics, or ProfitWell. They integrate with Stripe, Chargebee, or whatever payment processor you use and calculate everything automatically.

For product-led growth: Add Mixpanel or Amplitude to track behavioral signals that predict churn.

Step 3: Create Your Dashboard

Don't track 47 different churn metrics. You'll drown in data.

Instead, create a simple dashboard with:

• Current month customer & revenue churn
• 3-month rolling average (smooths out volatility)
• Cohort retention grid showing how each monthly cohort performs over time
• Top reasons for cancellation (from exit surveys)

Update it weekly. Review it with your team monthly.

Step 4: Implement Exit Surveys

When someone cancels, ask why. Keep it to 1-2 questions max. The key is categorizing responses consistently—create buckets like "Price too high," "Switched to competitor," "Missing features," "Technical issues," "No longer needed."

A tool like dontchurn.io makes this dead simple—build customizable exit surveys and let it collects and organizes all feedback so you can see exactly which user said what, including their plan level.

If 40% of churn is "missing features," that's a product roadmap issue. If it's "too expensive," you might have a pricing or value communication problem.

Bonus: Predicting Churn Before It Happens

Once you're tracking churn well, the next level is predicting it.

Signs a customer might churn soon:

• Declining login frequency (compared to their baseline)
• Support tickets spike then drop to zero
• They haven't used your core feature in 2+ weeks
• Payment retry attempts
• They're only using basic features, not advanced ones

Companies like Gainsight specialize in customer success platforms that score accounts based on health signals. But you can start simpler:

Create a spreadsheet with customers in rows and health signals in columns. Score each signal (red/yellow/green). Customers with multiple red flags go on a "save this customer" list for your CS team.

The Bottom Line

Tracking churn correctly isn't about finding the perfect formula.

It's about understanding why customers leave and catching problems early enough to fix them.

Start simple: track both customer and revenue churn monthly.

Add cohort analysis when you have 6+ months of data. Implement exit surveys this week. Then layer on predictive signals as you grow.

Remember, every company's acceptable churn rate is different. A B2C app might have 5-7% monthly churn and be healthy. A B2B SaaS company with 5% monthly churn is in serious trouble. What matters is understanding your churn, why it's happening, and whether it's improving or getting worse.

Now go forth and track. Your MRR will thank you.