Latest / Marketing Automation with Fexingo: HubSpot, Marketo, and Automated Customer Journeys / Why Marketing Automation Ignores Customer Hobby Changes
Transcript
- Lucas: Alright, let's talk about something that hits close to home for anyone who's ever changed hobbies. You sign up for a brand's emails because you're into marathon running, you buy a pair of high-end Asics, and then — life happens. A knee injury, a new interest in weightlifting. Suddenly those 'Your next race is coming up!' emails feel like a weird guilt trip. Luna: Oh, I've been on the receiving end of that. It's almost comical how long they keep sending the same messages. Lucas: Right. And the problem is almost never malice — it's that the marketing automation is built on a static persona. You set a customer's 'hobby' or 'interest' field once, usually at signup, and then the workflows treat that as gospel forever. Luna: So the system doesn't know that I went from running to deadlifts. What's the actual scale of this? Do marketers track hobby changes at all? Lucas: A 2025 survey from MarTech — I think it was Ascend2 — found that only about 12 percent of marketers actively update customer hobbies or interest tags based on behavioral shifts. Most rely on the initial profile. That means 88 percent are effectively blind to one of the most natural human patterns: evolving what we care about. Luna: And it's not just running. Could be someone who bought a DSLR and a year later is only buying phone camera accessories. Or a home brewer who switched to kombucha. Lucas: Exactly. I want to focus on a concrete case: a mid-size running shoe retailer, roughly 200 stores across the US. They had a classic automation — ten-touch nurture sequence for anyone tagged 'marathon runner'. Every email was about race prep, hydration belts, foam rolling. Luna: I can picture it. And the problem customer? Lucas: A guy named Mark. He bought a pair of Gel-Nimbus in March 2024. Got tagged 'marathon runner'. Then he tore his meniscus in June, switched to weightlifting. Started buying lifting shoes from the same retailer — they sell a small line. In the next twelve months he bought three pairs of lifting shoes, zero running shoes. But the automation kept treating him as a marathoner. Luna: So what happened? Did he unsubscribe? Lucas: He actually called customer service to complain. Said the emails made him feel like the brand didn't see him anymore. He still liked the retailer, but the irrelevant content was pushing him away. That's the core issue: the automation wasn't listening to his purchase data. Luna: And that data was right there in the CRM. Three lifting shoe purchases should have triggered a reassessment. Lucas: That's the fix. Instead of a static tag, you build a recency-weighted model. If a customer's most recent purchase in the last 90 days is from a different category than their original interest, the system should flag them for a persona update. In Mark's case, the algorithm sees his last three purchases are 'weightlifting' — that's a strong signal. Luna: Could also use content clicks. If someone stops opening race-prep emails but clicks on every strength-training blog post, that's a data point too. Lucas: Absolutely. And some brands are starting to pull in external signals — like connecting to workout apps via API. If you authorize a connection to Strava or Apple Health, a change in activity type could trigger a workflow automatically. Luna: But that's a big ask privacy-wise. Most customers won't connect their health data. Lucas: True, but you don't need it. Purchase history is enough for most cases. You just need a simple rule: if a customer buys from a new category that's not their primary, and that category accounts for more than 50 percent of their transactions in the last six months, reclassify them. Luna: That's clean. And it respects their agency — they're telling you with their wallet what they care about now. Lucas: Exactly. The retailer in our example actually implemented this. They built a 'hobby drift' flag into their CRM. Any customer who showed a category shift got moved to a new segment and received a re-engagement email: 'We noticed your interests may have changed — update your preferences to get content you'll love.' Luna: Did it work? Did they win Mark back? Lucas: Mark didn't come back — but that's because he'd already soured on the brand. However, for other customers, the open rate on that re-engagement email was 41 percent, compared to their usual 18 percent for standard prompts. And 23 percent of those who clicked actually updated their preferences. Luna: That's a solid lift. And it's not just about retention — it's about relevance. You're not spamming someone with content they've outgrown. Lucas: Right. And the cost of implementing this is low. A decent CRM like HubSpot or Salesforce can handle recency-weighted segments natively. You don't need a data science team. You just need to admit that your personas aren't permanent. Luna: There's a bigger principle here too. Marketing automation often treats customers as static profiles, but people are dynamic. If your system doesn't account for that, you're basically ignoring the customer's present self. Lucas: That's a great way to put it. And speaking of things that keep the show going — if these kinds of marketing conversations have sparked something you've actually used at work, or even just made you think differently about your own inbox, it genuinely helps when listeners support the show. Luna: Yeah, a couple of dollars a month is all it takes. It's what keeps these episodes ad-free and focused on real examples. Lucas: Exactly. So if you're able and you've gotten something out of these episodes, you can find us at buy me a coffee dot com slash fexingo. No pressure, but it does make a difference. Luna: Alright, back to hobby drift. One thing I want to dig into — how do you handle the timing? If someone buys one pair of lifting shoes, is that enough to trigger a change? Lucas: Great question. One purchase could be a gift. A one-off. So you need a threshold. Most best practices suggest a minimum of two purchases in a new category within 90 days, or three within 180 days. That gives you confidence it's a real shift. Luna: And what about customers who have multiple hobbies simultaneously? Like someone who runs and lifts and also does yoga? Lucas: That's the multi-interest customer. The solution there is to use a weighted tag system, not a single tag. You can have primary, secondary, tertiary. And then send emails that mix content — maybe 60 percent primary, 30 percent secondary, 10 percent tertiary. Dynamic content blocks make that pretty easy. Luna: So you're not erasing their past, you're just updating the mix. Lucas: Exactly. The running shoe retailer actually did that too. For customers who showed multiple categories, they created a 'hybrid athlete' segment and served blended content. Open rates on those emails were 34 percent — higher than the single-hobby segments. Luna: That makes sense. People like feeling seen as whole humans, not just a single dimension. Lucas: And that's the real takeaway from this episode. Marketing automation is incredibly powerful, but it's only as smart as the data you feed it — and the assumptions you're willing to revisit. Hobby changes are just one example. Think about life stage, job changes, location moves. The same logic applies. Luna: So the question every marketer should ask is: when was the last time you let your customers tell you they've changed? And did your automation listen? Lucas: That's the one to sit with. I'm Lucas. Luna: And I'm Luna. See you next time.