Latest / Marketing Automation with Fexingo: HubSpot, Marketo, and Automated Customer Journeys / Why Marketing Automation Ignores Customer Vacation Homes
Transcript
- Lucas: So there's this segment of customers that marketing automation almost never acknowledges, and it's surprisingly large: people who own a second home. Luna: Like a vacation house? I've been getting emails for a lawn service company that I signed up for when I was renting a place in Vermont for a month. They still think I live there. Lucas: That's exactly the problem. According to the Census Bureau's 2024 American Housing Survey, about 5.6 percent of US households own a second home. That's roughly 7 million households. But if you look at the typical marketing automation setup — HubSpot, Marketo, Salesforce Marketing Cloud — they all treat a customer's primary address as the only address. Luna: Right, and the data is practically screaming at us. If someone's ZIP code changes every few months, or if they have a property tax record in another county, that's a signal. Lucas: But most marketers aren't even looking. They'll run a campaign for 'homeowners' and blast the same message about snow removal or pool cleaning to everyone. That works fine if you live in one place year-round. But if you're a second-home owner, you might get an offer for a snowblower in July because the automation still thinks you're at the ski house. Luna: I've definitely been that person. The Vermont rental I mentioned — it was a ski cabin. I got leaf blower ads in February, which is ridiculous because there's no leaves in February up there. So what's the fix? Lucas: The fix starts with data enrichment. You can buy property tax records from companies like CoreLogic or ATTOM Data Solutions for a few cents per record. They'll tell you whether a property is owner-occupied or a second home. Then you overlay that with your CRM data. If a customer matches a second-home record in a different county, you know you've got a vacation homeowner. Luna: That's clever. But doesn't that get expensive at scale? Especially if you have millions of customers. Lucas: It depends on your margin. For a home-services company or a luxury brand, the incremental revenue from targeting someone at the right property at the right time can easily justify the cost. And you don't have to do it for everyone. Start with your top decile of customers by lifetime value. Chances are, a disproportionate number of them own second homes. Luna: I wonder if there's a simpler signal. Like, if someone's credit card shows recurring transactions at two different home-improvement stores in different states. Lucas: That's a great point. Transaction data is another layer. But the tricky part is that marketing automation platforms don't natively handle multi-address customers. HubSpot lets you store multiple addresses on a contact record, but the default behavior is to use the primary address for everything. So you have to build custom logic: if secondary address is present and matches a seasonal ZIP, use that for certain campaigns. Luna: And that's where most teams give up. They just don't have the bandwidth to build that logic. But the opportunity is real. I read a case study about a pool maintenance company that used property tax data to identify second-home owners. They sent off-season maintenance reminders to the primary address and got a 40 percent response rate. Because the owner wasn't being bombarded during the months they weren't there. Lucas: Forty percent is huge. The average email open rate for home services is something like 20 percent. So this isn't just a nicety — it's a real performance lever. And it applies beyond home services. Think about insurance, utilities, even grocery delivery. If someone splits their time between two cities, they might want grocery delivery at both addresses, but only when they're there. Luna: But here's the thing: most marketing automation treats a 'customer' as a single entity with one location. That's a legacy of the direct-mail era. And now we're all stuck in that mindset. Lucas: Exactly. And the platforms haven't evolved because they're designed for the median use case. The median customer has one home. So why build features for the minority? But that minority is often the most valuable segment — they have more disposable income, they spend more per transaction. Ignoring them is leaving money on the table. Luna: I want to throw in a listener story. A woman named Sarah emailed us last week. She owns a condo in Florida that she uses for three weeks every winter. She got a year's worth of pest control ads because she signed up for a local service once. The automation saw her address and didn't check seasonality. She said she felt like the company didn't understand her at all. Lucas: That's a perfect example of the problem. And it's not just about nuisance — it's about wasted ad spend. That pest control company spent money showing ads to someone who was never going to use their service in July. If they had a seasonal flag, they could have paused those ads and saved the budget for when she was actually in Florida. Luna: And speaking of saving budget, if these marketing conversations have sparked something you've actually used — maybe a strategy we talked about that helped you clean up your audience segmentation — we'd love if you considered supporting the show. It's listener-supported and ad-free, and a small contribution at buy me a coffee dot com slash fexingo goes a long way. Just a thought. Lucas: Yeah, seconded. It helps us keep digging into corners like this. So back to the vacation home problem — there's also a privacy angle. If you're going to use property tax data, you need to be transparent about it. Some customers might not want you to know they own a second home. Luna: Right. You'd have to give them an opt-out. But if you frame it as 'we want to send you the right offers at the right time,' most people will appreciate it. Lucas: And the compliance piece matters too. Property tax records are public, but using them for marketing might fall under certain state privacy laws. California's CCPA, for instance, gives consumers the right to know what data you're collecting about them. So you'd want to have that disclosure ready. Luna: So what's the first step for a marketer who wants to try this? Say they're using HubSpot. Lucas: First, identify your second-home owners. You can do a rough cut by looking at customers who have two addresses in your CRM and where the addresses are in different climate zones or far apart geographically. Then export those and match them against property tax records. For a pilot, you could just survey a segment: 'Do you own a second home?' People are often willing to answer if you explain why you're asking. Luna: And then create separate lists or campaigns for that segment. Maybe a 'snowbird' campaign for people who migrate south in winter, or a 'lake house' campaign for summer residents. Lucas: Exactly. And set up triggers based on seasonality. If someone's second home is in a Northern ski area, you might ramp up email frequency in November and scale back in April. Marketers already do seasonal campaigns, but they usually treat the whole list the same. This is about micro-segmentation based on actual residence patterns. Luna: It seems like such an obvious blind spot once you think about it. I'm surprised more people don't talk about it. Lucas: Well, the data has only become easily accessible in the last few years. And marketing automation platforms are still catching up. But I think within the next two to three years, we'll see features that natively handle multiple residences. Until then, the teams that build this logic themselves will have a big advantage. Luna: Any other creative applications? Besides home services, I mean. Lucas: Sure. Car dealerships: if someone has a second home in a state with different weather, they might want a different vehicle there. Or subscription boxes: if someone splits time, they might want their box delivered to the second address during certain months. Even media companies: someone might want local news alerts for both their hometown and their vacation town. Luna: The more we talk, the more I realize how many industries this touches. And how many customers are probably annoyed right now. Lucas: Exactly. And the fix isn't rocket science. It's just a matter of recognizing that the single-address model is a relic. We have the data, we have the tools — we just need to connect them. Luna: Alright, something to think about. Thanks, Lucas. Lucas: Thanks, Luna. See you next time.