Latest / Marketing Automation with Fexingo: HubSpot, Marketo, and Automated Customer Journeys / How Marketing Automation Misses Customer Hobby Changes
Transcript
- Lucas: Let me tell you about a friend of mine named Dan. Dan is a serious cyclist — has been for about eight years. He used to ride mountain bikes almost exclusively, and for years he got great emails from a brand called Specialized, tailored to trail riding and suspension setup. Luna: So the automation was working. They knew his segment. Lucas: Exactly. But about eighteen months ago, Dan switched to gravel riding. He sold his mountain bike, bought a gravel bike, started following gravel influencers on Instagram, joined a gravel forum, and started watching GCN Gravel videos on YouTube. His entire digital footprint changed. Luna: And Specialized kept sending him mountain bike content. Lucas: Every single email. New trail bike. Suspension maintenance tips. Enduro race coverage. Nothing about gravel. Dan stopped opening them. Eventually he unsubscribed. And then he bought a gravel bike from Canyon, a direct to consumer brand that had no idea he existed six months ago. Luna: So the automation actually drove him away. That's a retention failure disguised as a targeting success. Lucas: Right. And the problem is structural. Most marketing automation platforms — HubSpot, Marketo, Salesforce Marketing Cloud — they're built on explicit signals. Purchase history, email clicks, page visits, form fills. Those are great for capturing intentional behavior. But hobby changes are almost never explicit. Luna: People don't fill out a form saying 'hey, I started gravel riding.' They just change what they consume. Lucas: And the platforms have no way to ingest that shift. Dan's new YouTube subscriptions, his new Strava clubs, his Pinterest boards — none of that feeds into the CRM. So the automation treats him as a static person. And that static profile becomes more wrong every day. Luna: Is this a data problem or a workflow problem? Could a brand build a hobby-change trigger if they had the right data? Lucas: Both. Let's start with data. There are third-party sources that could signal a hobby shift. Strava API data, for instance — if a cyclist suddenly logs more road miles than trail miles, that's a signal. Pinterest interest tags. Reddit subreddit memberships. Even something like change in credit card spending at different retailer categories. Luna: That's a lot of data. And a lot of privacy questions. Lucas: Absolutely. And that's the second part — workflow. Even if you had permission to access that data, most marketing automation tools don't have native integrations for these signals. You'd need a custom data pipeline, maybe using a customer data platform like Segment or mParticle, to stitch together that behavioral data and feed it into your automation tool as a custom event. Luna: So the barrier isn't just willingness — it's technical infrastructure. Lucas: And organizational silos. The social media team might see the change in follows. The customer support team might hear the customer mention a new interest. But none of that gets into the marketing automation system. I talked to a marketing ops lead at a large outdoor retailer last week, and she told me they recently did a data audit and found that less than three percent of their customer profiles had any hobby-related attribute. Luna: Three percent. That's almost zero signal for something that drives so much purchasing behavior. Lucas: Exactly. And the cost is real. Dan's story is one customer, but multiply that across your base. People change hobbies all the time. They start running, they switch from skiing to snowboarding, they get into photography, they quit playing golf. Each shift is a moment where your automation either adapts or alienates. Luna: What would a good hobby-change workflow look like? Give me a concrete example. Lucas: Let's say you're a brand like REI. You sell gear across dozens of activities. A customer has historically bought hiking boots, camping gear, maybe a tent. Then for six months, they buy nothing. But their Strava data shows they've been logging runs every week. The ideal workflow: a custom event triggers when the ratio of running activities crosses a threshold. That event moves the customer into a 'running enthusiast' nurture track — maybe sending content about trail running shoes, hydration vests, injury prevention. And crucially, it pauses the hiking content that's now less relevant. Luna: So you're not just adding a new track — you're also suppressing the old one. That's the part most automation fails at. Lucas: Yes. Most platforms are additive. They keep sending everything. The key is to treat hobby change as a lifecycle event, similar to a move or a job change. It should trigger both an inclusion and an exclusion. Luna: But there's a risk of over-personalization, right? What if I just tried running for a week and then quit? Now you've pigeonholed me. Lucas: That's a real concern. You need a confidence threshold. Maybe you wait until the behavior is sustained for a certain period — say, four weeks of consistent activity — before you change the profile. And you should always allow the customer to correct it. A simple 'are you still interested in hiking?' prompt can prevent false positives. Luna: That feels more respectful. And it gives the customer agency. Lucas: Right. And here's the thing — the brands that get this right will have a significant advantage. Because right now, everyone is competing on the same signals. Purchase history, email opens, site visits. Hobby change is an overlooked signal that can differentiate your relevance. Luna: And relevance drives retention. And retention drives lifetime value. Lucas: Exactly. I think the next frontier in marketing automation isn't better algorithms for predicting what someone will buy next. It's better listening for who someone is becoming. Luna: That's a great line. And it reminds me — if these conversations have sparked something you've actually used in your own marketing, or given you a fresh way to think about your customer data, that's exactly why we do these shows. A couple of dollars a month at buy me a coffee dot com slash fexingo genuinely helps keep them ad-free and focused on the ideas. Lucas: Yeah, it's a small thing that makes a real difference. And it lets us keep digging into these blind spots without worrying about sponsorships. Luna: So back to the hobby question — are there any brands you've seen doing this well already? Lucas: A few. I've heard that some fitness apparel brands are experimenting with Strava API integrations. And there's a fishing gear company that actually built a custom field in their CRM for 'primary fishing type' — freshwater, saltwater, fly — and they have workflows that detect when a customer starts buying gear in a different category. That's a simple version of the same idea. Luna: So it's not impossible. It just requires intention. Lucas: And a willingness to look beyond the data you already have. The most valuable signal might be the one you're not collecting yet.