MicroConf Tactics: The Real Reason SaaS Customers Cancel (here's how to fix it)

**Rob Walling** (0:07)
Welcome back to the MicroConf Podcast, I'm Rob Walling. And in this Tactics episode, we pull audio from one of the most popular YouTube videos from my channel, youtube.com/atrobwalling.
This video is titled, The Real Reason SaaS Customers Cancel, and here's how to fix it.
Before we dive in to the meat of the episode, tickets from MicroConf US are now on sale. So the next MicroConf in the US is Austin, Texas, April 18th through the 20th of 2027
Use promo code ROB50, that's ROB50, for $50 off. microconf.com/us to buy your ticket.
And they are as cheap as they will ever be. They're currently priced with early bird pricing. We sell out all of our events. So if you want to come, you might as well buy your ticket now. microconf.com/uspromocoderob50.
And with that, let's dive in to the real reasons SaaS customers cancel, and how to fix it.
Every time a customer cancels, you tell yourself a story about why. They needed a feature you didn't have. They found something cheaper. They just weren't a good fit. And most of the time, that story is wrong. In SaaS, we quantify cancellations with churn rate. It's the percentage of customers or revenue that you lose each month. Even a 5% churn rate can be deadly. It doesn't sound that bad until you do the math and realize that you're replacing half your customer base every single year just to stay flat. Half your marketing isn't growth, it's treading water. And right now, this is playing out at an extreme scale. AI native SaaS companies are churning at 15, 20, even 30% month over month, numbers that make it almost impossible to build a real business. But when I look at why, it's not some new AI specific problem. It's the same handful of mistakes I've been seeing kill SaaS companies for 20 years. AI just turned up the volume. After investing in more than 230 SaaS companies and building several of my own, there are dozens of reasons I've seen customers leave. Every business is a little different, but today I want to walk you through the biggest buckets I see come up over and over and help you figure out which ones you can actually do something about. The first pattern I see is that customers never had their aha moment. Most people who canceled their subscriptions made that decision in the first two weeks. They just didn't tell you for another three months. You can see this when your churn is heaviest in the first 30, 60, maybe 90 days, where your retention grid shows this almost universally. You have high churn and then it frankly levels out. These customers are treating their paid plan as an extended trial. What you have to think about is this concept of onboarding, of getting people onboarded, and the minimum path to awesome. So this is the minimum number of steps, the minimum path within your app for something to click with the person. So as one example, my last SaaS app was called Drip. You can view it at drip.com. We built an internal dashboard tracking users through setup steps as a leading indicator of conversion. And we could track if they'd done one of the steps, two of the steps, three of the steps, and almost predict whether they were gonna churn in the first 30 or 60 days. And there's another version of this missing the aha moment. It's when your marketing promises something that the product doesn't yet deliver. So a customer signs up expecting magic and it really doesn't match. This is rampant, ubiquitous right now with AI products. The demos look incredible, but the day-to-day experience doesn't live up to the pitch. And that gap between expectation and reality is one of the fastest paths to churn. The fix here is onboarding. If you've actually built something that people want once they get onboarded, you need to send emails, you need to have checklists, you can add a customer success manager who is proactively reaching out, in-app chat widgets, tutorials, and for higher price points, you can have a person, a human customer success manager walking them through. But also, honest messaging that sets realistic expectations upfront is a really good start towards cutting this type of churn. Pattern number two, they were never the right customer. If your churn rate is a problem, you need to dig deeper than just looking at the number. You need to actually start looking at who's churning, because I guarantee it's not everyone.
The problem with looking at aggregate churn and expecting that everyone is churning across the board for the same reasons and at the same rate is incorrect. The analogy I like to use is an Amazon review. So if we were to look at an Amazon product that had a 2.5 star average, that could mean everyone voted it 2.5, or it could mean half of the people loved it, half hated it, or were the wrong audience, and it averages out to 2.5 stars. Similarly, if you're looking at aggregate churn, it's muddy, it's cloudy, you can't see through to actually see certain tiers churn a lot higher. So one of the companies in my SaaS accelerator, Tiny Seed, published an example where they had a $30 a month tier that had 11% churn, and then their $100 a month and up tier had negative 4% churn. So this is a 15% swing in churn between these two plans. It's night and day. This is like growing two completely separate businesses. The idea here is once you can see that different tiers are churning at different rates, you can now make an informed decision of whether you want to get rid of your lowest plan, whether you want to pay more attention to that lowest plan, whether you want to raise the price. There's a bunch of things you can do, but if you just looked across the board and said, oh, we have aggregate 7 or 8% churn, that isn't helpful until you segment it out by tier. And I want to make a quick distinction here. Net churn factors into expansion revenue, right? This is when existing customers upgrade and pay you more. And net negative churn, as I said in this example, they had minus 4% churn on their $100 and up plans. That means you can actually grow without adding new customers. So there are different approaches you can take here. You can segment by pricing tier. You can segment by marketing channel. And you can segment by the cohort, right? Which given month, 10 months ago versus 5 months ago, how are the churns different? One example is Agent Methods. And the founder Aaron Cassover told me that he segments by acquisition channel, and it revealed that his pay-per-click ad leads had much lower lifetime value than customers acquired through other channels. In addition, my rule of thumb, almost always correct. In fact, I have, I think I've heard of one counterexample of this rule, lower paying customers always churn faster. Pattern number three is death by a thousand cuts. Very few people cancel your product because of one bad experience. They cancel because of 50 OK experiences that weren't quite good enough. So what often happens is there's this accumulation of small frustrations. So if your user interface is confusing, your user experience isn't great, you have broken integrations, you have bugs, you have billing surprises, these stack up. None of these would be deal breakers alone, but together they erode trust. And these kinds of small issues are what open the door to competitors. The customer isn't actively shopping, but when they hit a small frustration and they notice that another tool they're already using could handle the job, or a competitor's ad or cold email lands at the right moment, the switching cost suddenly feels worth it. These customers rarely tell you the reason they're leaving. They'll say, we switched to X when the truth is, X just happened to be there when they'd had enough. One way to attack this is to watch engagement trends, not just cancellation reasons. So a customer who used to log in daily and now logs in once a week is quite possibly already halfway out the door. The place I most often see this pattern is with software where there's no technical founder. So a SaaS app is started by someone who hires an agency or a freelancer who doesn't give a crap about the code quality. And over time, bugs, confusing UX, broken integrations, they just creep in and nobody really knows how to fix them. So I'm not saying never start a SaaS without a technical co-founder, but there's a reason that 85 to 90% of companies that I'm invested in have at least one technical co-founder. Pattern four are forces outside your control. Some churn you can fight and some churn you just have to absorb. Knowing the difference can save you from spending months trying to fix the wrong problems. There are all kinds of specific reasons that fit under this pattern, but two big ones are the champion leaves the company or the customer outgrows or shrinks out of your product. What I mean by champion departure is where the person who bought your product, who evangelized it internally, and who knew how to use it, leaves the company. Their replacement evaluates the tool with fresh eyes and no loyalty. You can reduce this risk by getting multiple users engaged and making the product imbedded in team workflows, not just one person's workflow. But if a customer outgrows you, so they started as a five person company and now they're at 50, their needs can shift. It isn't really a failure if you're not trying to serve that market. If you're really focused on being amazing for five to 49 person companies, I don't necessarily view this as a failure. It can be the natural life cycle of a customer segment. Businesses shutting down are another reason that folks cancel.