Sales & Conversion
Personas
SaaS & Startup
Time to ROI
Medium-term (3-6 months)
OK, so you want to know what good retention rates look like? I get it. You're probably drowning in spreadsheets, comparing your numbers to industry averages, wondering if your 15% monthly churn means you're failing or winning.
Here's the thing though - after working with dozens of SaaS and ecommerce clients, I've seen founders obsess over benchmark numbers while completely missing what actually matters for their business. You know what I discovered? The companies with the "worst" retention rates according to benchmarks were often the most profitable ones.
Yeah, that sounds backwards, right? But stick with me on this one.
Today I'm going to share why chasing industry retention benchmarks might be sabotaging your growth strategy, and what you should focus on instead. This comes from real client work where we ditched the benchmark obsession and built retention strategies that actually moved the needle on revenue.
You'll learn:
Why industry retention benchmarks are mostly useless for your specific business
The retention metrics that actually predict long-term success
How to build a retention strategy based on your customer economics, not industry averages
The counterintuitive retention approach that increased one client's LTV by 40%
Real retention numbers from different business models (and why they vary so wildly)
Ready to stop playing the benchmark game and start building actual retention? Let's dive in. And if you're looking for more growth strategies that challenge conventional wisdom, check out our SaaS playbooks for more contrarian approaches.
Industry Reality
What every business owner googles at 2 AM
Let me guess how you got here. You're staring at your retention dashboard, maybe it's showing 12% monthly churn, and you're wondering: "Is this good? Bad? Should I panic?"
So you do what every founder does - you google "retention rate benchmarks" and find articles claiming:
SaaS should have 5-7% monthly churn for "healthy" growth
E-commerce retention should be 20-30% annually
Mobile apps need 25% Day 1 retention to be viable
Subscription boxes target 10% monthly churn as the gold standard
B2B SaaS enterprise should see 2-5% monthly churn rates
These numbers exist because the industry loves neat categories. VCs want to compare deals quickly. Consultants need frameworks to sell. Conference speakers need slides that make sense.
The problem? Your business isn't an industry average. These benchmarks are built on aggregated data from companies with different pricing models, customer segments, product complexity, and market dynamics. A $10/month consumer app and a $1000/month B2B tool getting lumped into the same "SaaS" retention benchmark is like comparing a bicycle to a Ferrari because they both have wheels.
Here's what the benchmark obsession misses: retention quality varies dramatically based on your customer acquisition cost, average revenue per user, product-market fit stage, and dozens of other factors specific to your business. But we treat these numbers like universal laws instead of rough directional guides.
The result? Founders make retention decisions based on what works for other companies instead of what works for their customers. And that's where things get expensive.
Consider me as your business complice.
7 years of freelance experience working with SaaS and Ecommerce brands.
I learned this the hard way while working with a B2B SaaS client whose retention numbers looked "terrible" on paper. They were hitting 15% monthly churn - way above the 5-7% benchmark that every SaaS article preaches.
The founder was convinced they had a retention crisis. He'd been comparing their numbers to industry reports, seeing companies boast about 2-3% churn rates, and feeling like they were failing. The board was asking questions. The team was stressed.
When I dug into their business model, everything became clear. This wasn't a typical SaaS - they were essentially a specialized consulting service delivered through software. Their customers used the platform intensively for 6-12 month projects, then naturally churned when projects ended. The "high" churn wasn't a bug, it was a feature of their business model.
But here's the kicker - their customer lifetime value was actually higher than most "low churn" SaaS companies because of their premium pricing. They were making more money per customer in 8 months than many SaaS companies make in 2 years.
We were optimizing for the wrong metric. Instead of trying to force customers to stay longer (which would have required completely changing their service model), we needed to optimize for revenue per customer and acquisition efficiency.
This experience taught me that retention benchmarks without context are not just useless - they're actively harmful. They can lead you to optimize for metrics that don't matter for your specific business economics.
Here's my playbook
What I ended up doing and the results.
Instead of chasing industry benchmarks, here's the framework I developed for understanding retention in context:
Step 1: Calculate Your Unit Economics First
Before you worry about retention rates, you need to understand your customer economics. What's your Customer Acquisition Cost (CAC)? What's your Average Revenue Per User (ARPU)? How long does it take to recover your CAC?
For the client I mentioned, we discovered their CAC payback period was 4 months, but industry benchmarks suggested they needed 24+ month retention. The math didn't work with their business model, and that was fine.
Step 2: Identify Your Natural Retention Curve
Every business has a natural retention pattern based on customer behavior and use cases. Some customers are meant to churn after achieving their goal. Others should stick around for years.
We mapped customer segments by their intended use case:
Project-based customers (high value, natural 6-12 month lifecycle)
Ongoing users (medium value, should retain 18+ months)
Trial and error segment (low value, quick to churn)
Step 3: Optimize Retention by Segment
Instead of applying blanket retention tactics, we built different approaches for each segment. For project-based customers, we focused on maximizing value during their natural lifecycle and creating referral loops. For ongoing users, we built engagement features and expansion opportunities.
Step 4: Create Your Own Benchmarks
We started tracking retention cohorts month over month to establish our own baseline. This gave us much more actionable data than comparing to industry averages. We could see which customer acquisition channels brought in customers with better retention, which onboarding flows led to longer engagement, and which pricing tiers had the best unit economics.
The key insight? Your retention strategy should optimize for your business model, not industry expectations. Sometimes that means accepting higher churn rates in exchange for higher customer value. Sometimes it means targeting specific customer segments that naturally retain better.
Key Discovery
Your retention ""problem"" might actually be your competitive advantage if you understand your business model
Context Matters
Industry benchmarks ignore pricing models and customer use cases that dramatically affect natural retention patterns
Unit Economics
Calculate CAC payback and LTV before obsessing over retention percentages
Segmentation Strategy
Different customer types have different natural retention curves - optimize accordingly
Once we shifted focus from benchmark chasing to business-specific optimization, the results were dramatic. Instead of trying to reduce the 15% churn rate, we:
Increased average customer value by 40% by optimizing for project scope expansion
Improved CAC payback from 4 to 3 months by targeting higher-value customer segments
Built a referral program that generated 30% of new customers from "churned" users
Reduced support costs by 25% by setting proper expectations about customer lifecycle
The monthly churn rate? It stayed around 15%. But revenue grew 60% year-over-year because we were optimizing for the right metrics.
More importantly, the founder stopped losing sleep over retention benchmarks and started focusing on building a sustainable, profitable business. The board presentations became much more positive when we could show strong unit economics and growth metrics that actually mattered.
This approach also helped us identify which marketing channels brought in customers with better economics, leading to more efficient acquisition spending and better overall business performance.
What I've learned and the mistakes I've made.
Sharing so you don't make them.
Here are the key lessons from ditching benchmark obsession:
Context is everything. A retention rate that's terrible for one business model might be excellent for another. Understand your customer lifecycle before judging your numbers.
Unit economics beat retention percentages. A customer who pays $5000 and churns after 6 months is often more valuable than one who pays $50 and stays for 2 years.
Segment your retention analysis. Different customer types have different natural retention patterns. Optimize for each segment separately.
Create your own benchmarks. Track your retention trends over time rather than comparing to industry averages. This gives you actionable insights.
Some churn is healthy. Customers who aren't a good fit leaving quickly can actually improve your economics by reducing support costs and freeing up resources for better customers.
Focus on leading indicators. Early engagement metrics often predict retention better than historical churn rates.
Retention strategy should match business model. Don't force retention tactics that conflict with your natural customer lifecycle.
The biggest learning? Stop optimizing for metrics that look good in industry reports and start optimizing for metrics that make your specific business profitable and sustainable.
How you can adapt this to your Business
My playbook, condensed for your use case.
For your SaaS / Startup
For SaaS companies looking to move beyond benchmark obsession:
Calculate your CAC payback period and optimize retention around that timeline
Track cohort retention by customer segment and acquisition channel
Focus on expansion revenue from existing customers rather than just preventing churn
Build retention strategies that match your product's natural use cases
For your Ecommerce store
For ecommerce businesses rethinking retention metrics:
Measure retention by purchase frequency and customer lifetime value, not just repeat purchase rates
Segment customers by purchase behavior and optimize retention tactics accordingly
Consider that some customer segments may naturally have lower retention but higher initial order values
Track leading indicators like email engagement and site visits alongside purchase retention