Latest / Customer Journey with Fexingo: Touchpoints, Mapping, and Multi-Channel Marketing / The Churn Prediction Touchpoint Journey Maps Miss
Transcript
- Lucas: So, Luna, I want to talk about a touchpoint that almost no journey map includes, and I think it's one of the most valuable ones you can add. It's the moment before churn — the quiet window where a customer hasn't left yet, but every signal says they're about to. Luna: You mean, like, the 'going dark' phase? Where they stop opening emails and stop logging in? Lucas: Exactly. And I think the reason it's missed is that journey maps tend to treat loyalty as a flat, happy plateau. You know, customer gets onboarded, they use the product, they renew — done. But the reality is, churn is rarely a sudden decision. It's a slow fade, and that fade is full of micro-touchpoints that a marketer could actually act on. Luna: So you're saying we should map the fade itself. That's a different way to think about it. Lucas: Right. And I've got a specific example. There's a subscription box company — I won't name them, but they're a food-delivery service — and they had a churn problem. About eight percent of their customers were cancelling each month. So they pulled the behavioral data and found that the strongest predictor of cancellation wasn't how long someone had been a customer, or even how much they spent. It was whether they'd skipped a delivery in the last two months. Customers who skipped once were twice as likely to cancel within sixty days. Luna: That's a really specific signal. So skipping a delivery is basically a red flag. Lucas: It is. And once they knew that, they could map a 'pre-churn' touchpoint: when a customer skips a delivery, they now trigger a personalized email that offers to switch the delivery to a different day, or pause the subscription, or even suggest a smaller box. That simple intervention cut their monthly churn by eighteen percent. Luna: Eighteen percent is huge. And it all came from mapping a touchpoint that most companies would never even think of as a journey step. Lucas: Yeah, and that's the thing. The journey map usually ends at 'repeat purchase' or 'renewal'. But the real journey — especially in subscription businesses — loops back. It goes from active to disengaged to churned, and that disengagement phase is where you can intervene. Luna: So how do you actually identify that disengagement in a practical way? I mean, not every customer who skips a delivery is about to leave. Some people just go on vacation. Lucas: Right, and that's why you need a composite signal, not just one behavior. You look at a combination of things: declining login frequency, dropping feature usage, slower response times to your emails, maybe a decrease in support tickets. If a customer used to open your newsletter every week and now they haven't opened in three months, that's a meaningful shift. You can build a churn-risk score that weights these signals. Luna: A churn-risk score. So essentially you're creating a predictive model that tells you who's at risk, and then you can target them with a special touchpoint. Lucas: Exactly. And the touchpoint doesn't have to be a discount or a desperate plea. It can be something genuinely helpful. For that subscription box company, they offered to swap the delivery day. For a SaaS tool, it might be a personalized email showing the user a feature they haven't tried yet, or a quick onboarding refresher. The key is to add value, not just say 'please don't go.' Luna: But here's my question — and I think this is where it gets a little uncomfortable — when you start tracking negative signals like 'hasn't logged in for a while,' are you crossing a line? Is that too stalker-ish? Lucas: It's a fair concern, and it's something companies need to think about carefully. You're not reading their private messages or tracking their location. You're looking at product usage data that you already collect anyway. The ethical question is: how do you use it? If you use it to send a creepy email that says 'we noticed you haven't logged in, which suggests you're about to cancel,' that's bad. But if you use it to reach out with a helpful tip or a check-in, that's actually good service. Luna: So it's about framing. You're not accusing them, you're inviting them back. Lucas: Yes. And this is where I think the journey map really shines. Because a journey map isn't just a list of touchpoints — it's a tool for understanding the customer's mindset at each stage. If you add a pre-churn phase to your map, you're acknowledging that customers go through a period of uncertainty, and you're designing a touchpoint that meets them there with empathy. Luna: I'm thinking about a friend who works at a fitness app, and they noticed that users who stopped logging workouts for two weeks were super likely to churn. They started sending a motivational email with a new workout plan, and it worked. Lucas: That's a perfect example. And it shows that the pre-churn touchpoint doesn't need to be complicated. It just needs to be timely and relevant. The hard part is knowing when to trigger it. Luna: And that's where the data comes in. You need to actually analyze your historical churn data to figure out what the leading indicators are. Lucas: Right. And I want to be clear: this isn't about adding another email to your automated sequence. It's about creating a new phase in your journey map, with its own goals, its own touchpoints, and its own success metrics. You're not just reacting to churn — you're anticipating it. Luna: So let's say I'm a marketer and I want to implement this. Where do I start? Do I need a fancy AI model? Lucas: Not necessarily. You can start simple. Look at your churned customers from the last six months, and compare their behavior in the thirty days before they churned to the behavior of your active customers in the same period. Look at things like login frequency, feature adoption, support interactions, even email engagement. You'll likely find a few patterns that stand out. Then you can create a simple rule-based trigger — like 'if a customer hasn't logged in for fourteen days and hasn't opened any of the last five emails, send them a re-engagement email.' You don't need machine learning for that. Luna: That's really practical. And I bet a lot of companies already have this data in their analytics tools, but they're just not using it for this purpose. Lucas: Exactly. And that's the missed opportunity. The data is sitting there, but because the journey map doesn't include a pre-churn phase, nobody thinks to look at it. Once you add that phase, it becomes a natural part of your marketing strategy. Luna: I wonder if this approach works for all types of businesses, or if it's mostly for subscription models. Lucas: It works best for any business with recurring engagement — so subscriptions, SaaS, membership programs, even retail with a loyalty app. But you can adapt it to one-time purchases too. For example, a car dealership might track when a customer's warranty is expiring or when they're due for a service, and that's a pre-churn touchpoint for a different kind of churn — the move to a competitor. Luna: That makes sense. So it's really about identifying the key moments when a customer is at risk of leaving, regardless of the business model. Lucas: Exactly. And I think the most important thing is to be proactive instead of reactive. Most companies wait until the customer calls to cancel, and then they offer a discount to keep them. But by then, the customer has already made up their mind. If you catch them earlier, you have a much better chance of changing the outcome. Luna: So mapping the pre-churn phase is like having a early warning system for your customer relationships. Lucas: That's a great way to put it. And I think it's something that separates great marketers from average ones. Average marketers look at the happy path and assume it will continue. Great marketers know that every customer is on a journey, and that journey sometimes leads away from you. The question is: are you going to be there to guide them back? Luna: Absolutely. And I have to say, this episode has been really useful. I feel like I could actually go and apply this tomorrow. Lucas: That's the goal. And you know, if you found this genuinely useful, the way we keep these conversations ad-free is through listener support. If you've ever gotten something out of our shows, you can help by buying us a virtual coffee at buy me a coffee dot com slash fexingo. It's a small gesture, but it goes a long way. Luna: Yeah, and honestly, we appreciate every single one of you who's ever contributed. It helps us keep doing what we love, and it keeps the podcast free for everyone. Lucas: So, back to the journey map. Another thing that's often overlooked is the 'silent churn' — customers who don't cancel, but just stop using the product. They're not even in your churn data because they never formally leave. Luna: Oh, that's a whole other layer. So you have to map the 'dormant' phase too, not just the pre-cancellation phase. Lucas: Exactly. For a subscription business, a customer who stops using the product but keeps paying is actually a liability. They're not getting value, so they're likely to churn at some point, but in the meantime, they're not engaging with your brand. That's a missed opportunity for upsells, for referrals, for anything. Mapping that dormant phase helps you re-engage them before they even think about cancelling. Luna: And I imagine that's even harder to detect, because they're not making any noise. They're just silent. Lucas: Right. But the data is still there. You can track login frequency, feature usage, even how often they interact with your customer support. If those numbers drop off a cliff, you know something's wrong. The key is to define what 'inactive' means for your product and set up a trigger for that. Luna: So what would a touchpoint for a dormant customer look like? Maybe a different kind of email than the pre-cancellation one. Lucas: Yeah, I think so. For a dormant customer, you might want to offer an incentive to come back, like a free month or a credit. Or you might just ask for feedback — 'we haven't seen you in a while, is there anything we can do?' That can often uncover an issue that's easy to fix. Luna: That's a smart way to look at it. It's not about guilt-tripping them into coming back; it's about understanding why they left and showing you care. Lucas: Exactly. And that's what makes the journey map such a powerful tool. When you map the negative space — the moments of inactivity, the signals of disengagement — you turn those from blind spots into opportunities. Luna: I think we've given our listeners a lot to think about today. I know I'm going to revisit my own journey maps and see where I could add a pre-churn phase. Lucas: And that's the best takeaway we can hope for. Thanks for being here, and remember to keep an eye on those silent signals.