Latest / SaaS Business with Fexingo: Software-as-a-Service Companies, ARR, and Recurring Revenue / How SaaS Companies Track Customer Effort Scores
Transcript
- Lucas: If these conversations are useful for what you're building or running, know that this show is listener funded through buy me a coffee dot com slash fexingo, and that small group keeps it ad-free. Luna: That transparency helps us keep the signal to noise ratio high without chasing clicks. Lucas: Right, so let's get into today's angle. For years, the SaaS playbook was simple: get more seats, expand usage, and watch your net dollar retention climb. But I've been looking at some internal data from a mid-market workflow platform here in early September two thousand twenty six, and they flipped their entire success model around a single metric called customer effort score. Luna: I've seen CES pop up in CX circles, but usually as a survey after a support call. How does it work when it's baked into the product? Lucas: It's less about asking how hard it was to solve a problem, and more about measuring the actual friction in the user journey before they even realize they have a problem. The company tracks micro-interactions—like how many times a user clicks back, or hovers over a help icon without clicking—and correlates that with renewal likelihood. They found that users who hit three specific friction points in their first fourteen days were five times more likely to churn by month nine. Luna: So they're essentially mapping the path of least resistance versus the path of maximum confusion. Lucas: Exactly. And the twist is that they stopped optimizing for feature density. Most SaaS companies add features to justify price hikes, which actually increases cognitive load. This firm removed two major modules that were causing the most hover-back behavior, and surprisingly, their average revenue per user went up because the remaining core features became so much smoother to use. Luna: That feels counterintuitive for sales teams who want to bundle everything. Did the sales team push back on cutting those modules? Lucas: They did, initially. But the leadership team showed them that the cost of supporting those complex modules was eating the margin. It turned out that every dollar spent on training customers to use the clunky features was generating negative return. By simplifying, they reduced their support ticket volume by nearly thirty percent in just one quarter. Luna: Thirty percent is a massive operational shift. How do you measure effort without annoying the user with constant surveys? Lucas: That's the clever part. They don't ask the user anything during the workflow. The measurement is passive, derived from telemetry data like keystroke dynamics, mouse velocity, and error rates. If a user types a password wrong twice and then deletes the whole field, that's a high-effort signal. It's invisible to the customer but highly predictive of frustration. Luna: Invisible telemetry sounds efficient, but isn't there a privacy trade-off we need to acknowledge here? Lucas: Absolutely, and they had to be very careful with their data governance. They aggregate the data at the cohort level, not the individual user level, for their strategic decisions. Only specific triggers—like a user stuck on a screen for more than five minutes—prompt an automated, non-intrusive tooltip offering help. It's subtle enough that most users don't even notice it's happening. Luna: So the goal is to remove the need for intervention by making the default path intuitive. Lucas: Precisely. And this ties back to something we discussed last week about zero-based renewals. When you force customers to justify every line item, you also force them to evaluate their own usage intensity. If the tool is hard to use, that justification fails. Low effort scores make the value proposition self-evident. Luna: I wonder if this approach scales differently for enterprise clients versus small business users. Enterprise buyers often have different tolerance for complexity. Lucas: That's a fair point. In enterprise, complexity can sometimes signal robustness. But even there, the trend is shifting toward 'time to value.' If an enterprise implementation takes three months because the UI is opaque, the champion on the client side gets replaced before the contract renews. Speed of adoption is now a proxy for trust. Luna: So low effort isn't just about convenience; it's about risk mitigation for the buyer's career. Lucas: Spot on. When the software is easy to use, the person who selected it looks smart. When it's hard, they look incompetent. That political dynamic drives renewals more than any feature list ever could. Luna: This makes me think about the role of customer success teams. Does lowering the barrier reduce their headcount needs? Lucas: It changes their role entirely. Instead of being firefighters putting out login issues and basic training calls, they become strategic advisors. They spend less time teaching people how to click buttons and more time helping them interpret data insights. It's a higher-leverage activity that justifies their salaries better. Luna: I can see why executives would prefer paying for strategists rather than trainers. What about the technical debt? Removing those complex modules must have required significant engineering sprints. Lucas: It did. They paused all new feature development for two quarters to refactor the codebase. That was a tough sell to investors who wanted to see innovation. But the narrative they sold was that 'simplicity is the ultimate sophistication,' and the financial results proved it. Their gross margins expanded by four percentage points. Luna: Four percentage points on gross margin is huge for a software company. Did they share that data publicly? Lucas: Not in their earnings calls, but they did publish a case study in a trade journal last month. It's gaining traction among private equity firms looking at portfolio companies. PE owners are increasingly interested in efficiency plays because they plan to hold assets longer than before. Luna: Longer hold periods mean sustainable operations matter more than rapid feature dumping. This aligns perfectly with that shift. Lucas: Yes. And it challenges the old 'growth at all costs' mentality. You can grow faster by retaining existing customers who aren't frustrated. Churn is a leak in the bucket; effort score is the patch. Luna: Is there a threshold where too much simplicity hurts perceived value? Like, if it's too easy, do customers think it's cheap? Lucas: That's the artistry of product design. You want the interface to feel effortless, but the outcomes to feel powerful. Think of Apple products—they are incredibly simple to use, but no one thinks they are low value. The key is visual polish and performance speed. If the app loads instantly and responds fluidly, simplicity reads as premium. Luna: So performance is part of the effort score calculation? Latency matters? Lucas: Huge amounts. Every hundred milliseconds of delay adds to the perceived effort. The company they're tracking has a strict SLA on response times that is tighter than industry standard. They treat latency as a bug, not a constraint. Luna: That discipline must require serious infrastructure investment. Cloud costs alone... Lucas: They optimized their backend architecture to reduce compute costs while improving speed. It was a win-win. Lower cloud bills and happier users. It proves that engineering choices directly impact the bottom line in ways marketing budgets never can. Luna: It's fascinating how deeply technical decisions translate into commercial survival. Do you think smaller startups should try this, or is it only viable for established players with enough data? Lucas: Actually, startups might benefit more because they haven't accumulated the legacy bloat yet. If you build your first version with low effort in mind, you set a culture of clarity. If you start complex, you have to dismantle habits later, which is harder than building right from scratch. Luna: Building for clarity instead of capability seems like a fundamental mindset shift for many founders. Lucas: It is. And it requires saying no to feature requests that add friction. It's easier to say yes than to defend simplicity against the pressure to compete on feature lists. Luna: Defending simplicity is definitely the harder conversation to have in a board meeting. Lucas: But the data speaks for itself. When you can show that removing a feature increased retention by fifteen percent, the argument writes itself. Luna: I'm curious if this metric will eventually replace NPS as the gold standard for satisfaction. NPS feels so outdated now. Lucas: NPS is still useful for broad sentiment, but CES is more actionable. Knowing someone is neutral doesn't tell you what to fix. Knowing they struggled with a specific button tells you exactly where to intervene. Actionable data always wins over abstract sentiment. Luna: Actionability is the difference between a dashboard and a decision. This feels like a solid framework for Q4 planning. Lucas: It is. As we head into the end of the year, companies are reviewing their tech stacks. Those that prioritize ease of use will likely come out ahead in retention metrics next spring. Luna: Simple tools, clear outcomes, and happy champions. It's a formula that works across industries. Lucas: Agreed. The question for leaders today is whether they have the courage to simplify before the market forces them to.