Customer Retention Analytics SaaS: Solving $408 Billion Problem

I remember the exact day I realized I had a customer problem that I couldn’t throw money at. It was a Tuesday morning, and I was looking at my Stripe dashboard having my second coffee. Five customers had churned that week. Just… gone. Unsubscribed. Done with us.

The annoying part? I knew they were leaving before they left. Not with some fancy algorithm. Just from talking to the team. My customer success person would say things like “Yeah, Sarah from that design agency hasn’t logged in all week” or “That marketing company keeps asking questions about billing, I think they’re looking to leave.”

She was right every single time. So I asked her: why don’t we just reach out to them before they cancel? Her answer was simple: “By the time I notice, they’ve already made up their mind. Or I’m juggling ten other things and can’t get to it fast enough.” That stuck with me.

The Money Talk That Changed Everything

A month later, my accountant sat down with me and basically said “you’re bleeding.” He showed me the numbers. We were spending about $3,500 to get a new customer. But every month we were losing customers worth way more than that in terms of what they could’ve paid us over time.

We weren’t adding revenue. We were running on a treadmill. He asked: “What if instead of constantly hunting for new customers, you just… kept the ones you have?” Sounds obvious, right? But I wasn’t obvious about it at the time.

I looked at it from a different angle. If I could catch even half the customers who were thinking about leaving and save them, that was worth way more than going out and finding replacement customers. The math just made sense.

The Spreadsheet Obsession

So I did something kind of nerdy. I built a spreadsheet. I went back through six months of data and looked at every customer who’d churned. Then I tried to find the pattern. What had they done differently in the thirty days before they left?

Here’s what I found:

• They logged in way less
• They stopped using the main feature they were paying for
• Their support messages changed tone. Less excited, more frustrated
• If they talked to us, they were asking about refunds or billing stuff

The crazy part? Every single customer showed like three or four of these signs. So it wasn’t that we couldn’t see it coming. We just had all the clues scattered around in different places. Login data here, support tickets there, billing stuff somewhere else.

If I could somehow put all those puzzle pieces together and just show the team “hey, this customer is about to leave,” they could actually do something about it.

What Everyone Else Was Using (And Why It Sucked)

I started looking at what was out there. Tools that could help with this. Gainsight is the big name. It’s supposed to be the best thing ever. I looked at their pricing and almost fell out of my chair. Five thousand to fifty thousand a month depending on your size.

Totango is similar. ChartMogul too. These are enterprise tools built for companies with fifty-person customer success teams and budgets to match.

I talked to a customer success manager at another startup. She said her company was paying Gainsight eight grand a month but she spent most of her day in Google Sheets anyway because the tool was too complicated for what she actually needed.

So here we are. The big expensive tools exist. But they’re built for companies way bigger than most SaaS companies are. The small and medium-sized companies the ones actually losing sleep over churn have no good options. They either pay way too much, or they do what we were doing. Sit around and hope they notice in time.

I Decided to Just Build Something

This was maybe nine months ago. I told my team I was going to spend some time building something. Just a small thing. Not a whole new product. Just a tool that would look at all our customer data and tell us who was about to leave.

I started simple. Really simple. I grabbed our Stripe data. Who’s been using the product? When was their last login? What features are they actually using? I pulled in our support tickets because the tone of messages matters. Are they frustrated or happy?

Then I just… made a spreadsheet formula basically. If someone’s logging in less than they used to, that’s a point. If they’re not using the main feature, that’s another point. If their support tickets are frustrated, another point. If they haven’t done anything meaningful in two weeks, another point.

Add those up and you get a number. High number means they’re probably leaving soon. I ran it against the last three months of customers and it was scary accurate. It caught like eighty-five percent of people who actually churned.

So I built a real version. Not fancy. Just a simple interface that shows a list of customers with a big red number next to their name if they’re about to leave. Our customer success person tested it. First week, we reached out to twelve customers it flagged as high risk.

Eight of them responded. Most were stuck on something or just busy. We talked to them, helped them out, and they stuck around. That was the moment I was like “oh wait, this actually works.”

I Started Charging People for It

At that point I realized: if this works for us, it probably works for other people too. I reached out to some founders I know and was like “Hey, want to try this weird churn prediction thing I built?” Most people said yes just because they thought it was interesting.

The first real customer was an online course platform. They were losing like twelve percent of students every month. Just accepting it as normal. I set it up for them in like thirty minutes. Stripe integration, email integration, boom.

Within a week the system flagged about two hundred students as high risk out of eight thousand. The owner reached out to a bunch of them. Not with “please don’t leave” messages. Just genuine “hey we noticed you’ve gone quiet, everything good?” messages.

A lot of them responded. Some had questions about the material. Some were just overwhelmed. Some thought the course wasn’t for them. But most of them stuck around once someone actually paid attention.

She told me: “This is the first time I feel like I’m not just watching people leave. I actually caught them in time.” I still remember that because it was the first time a customer made me feel like I’d actually built something useful instead of just something clever.

How I’m Running This Thing Now

So it’s been about a year. I’ve got like sixty-some customers paying between a hundred and four hundred bucks a month. The revenue is real enough that I can pay for servers and keep working on it. Not life-changing money. But actual money that proves people want this.

What’s funny is I barely did any traditional marketing. No ads. No sales team. People mostly found out about it through Twitter or word of mouth. I spent time writing about churn stuff online. About how to spot when customers are about to leave.

About why retention matters more than growth. And people who were dealing with those problems found my stuff and were like “wait, this person gets it, they made a tool for this.” That’s basically my whole customer acquisition strategy.

The customers that do sign up tend to stick around. Not because of fancy contracts. But because the tool pays for itself within like a month. If you save one customer, one, it’s paid for a year.

The Honest Stuff

I should probably tell you the parts that suck too. First, integrations are a nightmare. Every company uses different tools. Some use Stripe, some use Paddle. Some have HubSpot, some have Pipedrive. Some use Intercom, some use Zendesk. I spend way too much time just making the tool connect to different platforms.

Second, data quality is everything. If a company’s data is messy, if they’re not tracking usage properly, if there’s missing information, the predictions get weird. I’ve had to get pretty strict about making sure data is clean before running the model.

Third, I stay up sometimes thinking about what happens if Amplitude or HubSpot just decides to add this as a feature. They have unlimited resources. They already have relationships with customers. They could bury me.

But then I remember: they’re building for big companies. I’m building for small companies. That’s a different market. They might not care about us for a while.

Fourth, pricing is weird. I don’t know if I’m charging too much or too little. Some people tell me I’m underpriced. Others seem to think it’s expensive. I adjust it every few months and try to figure out what’s fair.

Why I Think This Actually Has Legs

Here’s the thing though. There’s a reason I keep going even though it’s not easy. The problem is real. Every SaaS company loses customers. Every subscription business deals with churn. Almost nobody has a good way to see it coming.

The market is massive. There are thousands of small and medium SaaS companies out there. Thousands of course platforms. Membership sites everywhere. All of them are losing money to churn they could probably prevent.

The solution is simple. It’s not complicated. It doesn’t require changing how someone’s whole business works. You connect some data, you get a list of people about to leave, you reach out. Done.

The unit economics work. I can run this for like forty bucks a month per customer. I charge a hundred to four hundred. That’s pure profit basically. At a hundred customers, that’s money. Real money.

And customers stick around. They don’t churn on me very often because they’re saving money every single month by using it. It’s not a software toy. It’s not a status symbol. It solves an actual expensive problem.

What I’m Doing Next

Right now I’m working on making it work for different types of businesses. Online courses need to look for different signals than B2B SaaS companies. Fitness apps have totally different churn patterns. I’m also trying to add integrations so it works with more tools.

Most people use some combination of stuff, and the more things I can connect, the more people I can help. But mostly I’m just talking to customers. Asking them what they need. Watching what actually saves customers. Building more of that.

The Real Takeaway

I didn’t set out to build a software company. I just had a problem at my own company and built something to solve it. Turns out a bunch of other people had the same problem. And turns out when you solve a real problem that costs people real money, they’ll pay you money to solve it. Shocking but true.

The lesson I keep coming back to is this: the best business ideas aren’t fancy or complicated. They’re usually boring problems that affect a lot of people. Everyone’s losing customers. Everyone knows churn is bad. Nobody really has a simple way to see it coming and do something about it.

I built something simple for a boring problem. And it’s working. If you’re dealing with the same thing customers leaving and you don’t see it coming I built this for you. Not because I’m trying to build a billion-dollar company.

But because I got frustrated with the problem and fixed it. Everything else followed from there. If you want to talk about any of this stuff, hit me up. I’m just some person who got annoyed at churn rates and built a thing.