Latest / The Operator's Manual with Fexingo: Daily Decisions, Tactical Wins, and Business Execution / How One Text Message Cut No-Shows 30 Percent
Transcript
- Lucas: So Luna, you know how we're always hunting for those one-change operational wins? The kind where a single tweak saves real money? Luna: Oh, I love these. Give me a good one. Lucas: Well, today it's a dental clinic. They cut no-shows by thirty percent with one text message. And I don't mean a fancy reminder system. Just one text. Luna: Okay, I'm intrigued. Because no-shows are brutal for any clinic. That's lost revenue, wasted staff time, and a hole in the schedule you can't always fill. Lucas: Exactly. And the fix is a lesson in how small changes in wording can change behavior. But before we dive in, I want to say something. If today's episode is useful to you, if you've picked up even one idea that helps you run your operation a little better, that's because these conversations stay ad-free. Listener support is what keeps it that way. So if you're game, you can buy us a coffee at buy me a coffee dot com slash fexingo. Luna: Yeah, it's a small way to keep the lights on, and it really does help. Now, back to that text. What did it say? Lucas: So the clinic was sending the typical reminder: 'You have an appointment on Tuesday at 3 PM. Reply C to confirm.' Standard stuff. And they were getting maybe a sixty percent confirmation rate, but still saw about fifteen percent of confirmed patients not show up. Luna: Right, so even the people who confirm are flaky. Lucas: Exactly. So they tested a new message. Instead of asking for confirmation, it said: 'We're looking forward to seeing you on Tuesday at 3 PM. If you need to cancel or reschedule, please reply here and we'll help you.' Luna: Interesting. So it's not asking for a response, it's just making it easier to cancel. How did that change anything? Lucas: Well, the no-show rate dropped by thirty percent. And the key is that it shifts the default. The old message made you decide to actively confirm. The new one assumes you're coming, and only asks you to act if you need to change. It's a classic default effect. Luna: So by removing the need to confirm, they removed a step where people could drop out. It's like the 'opt-out' versus 'opt-in' thing. Lucas: Exactly. And it also lowers the barrier to cancel. Instead of feeling like you're breaking a commitment, you're just doing a quick favor. People are more likely to cancel properly, so the clinic can fill the slot. Luna: That's smart. So it's not just about reducing no-shows, it's about improving the quality of the communication. You're giving people an out, and they take it. Lucas: Right. And the numbers back it up. They saw no-shows go down thirty percent, and cancellations actually went up a little, but those slots got filled because they had more time to rebook. Net effect: revenue per day went up. Luna: So it's a win-win. Patients feel better, the clinic earns more. What's the operational principle here? Because I feel like this could apply beyond just clinics. Lucas: The principle is to reduce friction for the behavior you want, and increase friction for the behavior you don't. Here, they made it easier to cancel, which seems counterintuitive, but it actually reduces the worst behavior — the no-show. Luna: So it's about designing for the path of least resistance, but in a way that guides people to the outcome you both want. Lucas: Yes. And it's not just about wording. It's about understanding the psychology of commitment. When you confirm, you're making a promise. When you don't cancel, you're just not doing anything. It's a passive state, and people are more likely to stay passive. Luna: I've seen this in my own life. I'm way more likely to show up if I never had to confirm in the first place. Once I confirm, I feel like I've done my part, and then I might forget. Lucas: Exactly. And this clinic is not alone. There are similar experiments in other industries. For example, a car dealership reduced test-drive no-shows by using a similar approach. Instead of asking for a confirmation, they just said, 'Your test drive is confirmed. If you need to reschedule, text us.' Luna: So the lesson is: don't ask for confirmation, assume attendance and make cancellation easy. Lucas: Right. And it's a small change, but it requires thinking about what your customer is going through. Are you adding a step that might cause them to drop out? Are you making it too hard to cancel, so they just don't show up instead? Luna: So what's the implementation cost? I'm guessing it's just changing a template in their system. Lucas: Basically. It took their front desk maybe an hour to update the message and test it. The ROI is enormous. I mean, a no-show costs them maybe eighty to a hundred dollars in lost revenue. So cutting no-shows by thirty percent could be thousands of dollars a month. Luna: That's the kind of win we love. Simple, cheap, and measurable. And it's a good reminder that sometimes the biggest operational gains come from the smallest tweaks. Lucas: And the key is to measure. They ran it for a month, compared to the previous month, and saw the change. If they hadn't measured, they wouldn't have known it worked. Luna: So if you're running any kind of appointment-based business, what's your advice? Should they just copy this text? Lucas: I'd say test it. But don't just copy the wording. Think about your own customers. What's the friction point? What's the behavior you want to encourage? And then design a message that reduces friction for that behavior. Luna: And measure. Always measure. Lucas: Always measure. Because if you don't, you're just guessing. And this is a perfect example of a guess that turned out to be right, but you need the data to confirm it. Luna: So, what's the one takeaway you want listeners to have today? Lucas: I think it's this: before you build a big solution, look for the smallest change that could remove a step or a barrier in your customer's journey. You might find a thirty percent improvement hiding in a one-line text. Luna: I love that. And on that note, we'll see you tomorrow. Lucas, always a pleasure. Lucas: You too, Luna. Until next time.