Latest / Marketing Automation with Fexingo: HubSpot, Marketo, and Automated Customer Journeys / Why Marketing Automation Ignores Customer Home Renovation Projects
Transcript
- Lucas: So it’s July 22, 2026, and I’ve been thinking about a blind spot that keeps popping up in marketing automation conversations — the kind that seems obvious once you say it out loud but almost nobody builds for. Luna: I’m ready. What are we missing this time? Lucas: Home renovation projects. Not just the contractor or the materials — the entire multi-year cycle that starts when a homeowner decides to remodel a kitchen or finish a basement. Luna: Interesting. So the trigger isn't a single event — it's a phase of life that can last six to twelve months or more. Lucas: Exactly. And during that window, spending patterns change dramatically. The average major renovation costs around twenty-two thousand dollars, according to the Joint Center for Housing Studies at Harvard. But that’s not the whole story. People buy new appliances, new flooring, new paint, new furniture, new lighting — the list goes on. Luna: And most marketing automation platforms are completely blind to it. They'll track an email open, a website visit, a cart abandonment. But they don't know that someone just pulled a permit for a new bathroom. Lucas: Right. And the data exists. County permit offices are public records. Some home services platforms like Angi or Thumbtack have signals. Even credit card data could show a spike at Home Depot or Lowe's. But the systems aren't wired to ingest that and trigger a campaign. Luna: Why not? Technically, it's feasible. You could scrape permit data, or partner with a home improvement platform. Lucas: Part of it is privacy. Pulling public permit data and matching it to individual customer profiles is legally gray in a lot of states. And credit card data aggregators like Plaid have strict use policies. But there's also a mindset issue. Most marketing automation is built around explicit actions — clicks, opens, purchases. It's not designed to infer life stages from indirect signals. Luna: So what's the missed opportunity? Give me a concrete example. Lucas: Let's say you're a window treatment company. You know the average homeowner replaces windows every fifteen to twenty years, but the real trigger is a renovation. If someone starts a kitchen remodel, they're likely to replace windows in that room within two to three months. A simple trigger — if we detect a permit for kitchen remodeling in a zip code, or a spike in lumber purchases — could send a targeted offer for custom blinds or shades. Luna: But you'd need to know who that specific person is. If you're just targeting a zip code, it's not exactly personalized. Lucas: True. But even zip level targeting based on permit volume can be more effective than broad demographic targeting. And if you have a loyalty program or a customer database, you can layer data. Someone who bought paint six months ago and lives in a permit-heavy area is a strong candidate. Luna: Okay, but what about the timing? Renovations have different phases. Early on, people are demo-ing, framing, roughing in electrical. They're not thinking about decor. Lucas: That's the real art. If you hit them too early, it's noise. Too late, and they've already made decisions. The sweet spot is usually three to five months into a major renovation — when the drywall is up, the cabinets are ordered, and they're starting to think about finishes. That's when flooring, lighting, and appliance brands should be showing up. Luna: Do any companies actually do this well? I know Wayfair has some dynamic segments based on recent searches, but I'm not sure they're keying off renovation signals. Lucas: A few are trying. IKEA, for example, launched a kitchen planning tool that captures intent. If you save a layout, you're clearly in the market. But they don't cross-reference with permit data or contractor referrals. The most advanced I've seen is a startup called Haven — they partner with home services platforms to identify homeowners in pre-renovation planning and then send curated product bundles. They claim a thirty percent higher conversion rate on those leads. Luna: That's a meaningful lift. But it's still niche. What would it take for a mainstream marketing automation platform like HubSpot or Marketo to build this in? Lucas: It would require a data partnership and a new class of triggers. HubSpot currently has something called 'custom behavioral events' where you can send any event from your own system. So theoretically, if you can get permit data into your CRM as a custom event, you can trigger workflows. But the default library doesn't include 'customer filed a building permit.' Luna: So the burden falls on the marketer to source and integrate that data. And most teams don't have the resources. Lucas: Exactly. And that's where the opportunity is. If a platform offered a pre-built integration with county permit databases or home services APIs, they'd unlock a whole new category of lifecycle marketing. Think about it: the home renovation market in the US alone is over four hundred and fifty billion dollars a year. A huge chunk of that spending is concentrated in the twelve to eighteen months of a renovation project. Luna: And yet most people in the middle of a remodel get generic home improvement emails that don't account for where they are in the process. I know when I redid my kitchen last year, I was drowning in offers for things I'd already bought or wasn't ready for. Lucas: That's the failure mode. You get a carpet ad two weeks after you installed hardwood. Or a backsplash tile offer when your cabinets aren't even in yet. It erodes trust. But if someone sends you a timely recommendation for under-cabinet lighting right when your countertops are being templated, that feels serendipitous. Luna: It also feels like they know you — which is the whole goal of marketing automation. So what's the privacy workaround? Lucas: Opt-in is the cleanest path. If you're a home improvement retailer, you could ask customers during checkout: 'Are you planning a renovation? Tell us which room and when.' That's explicit permission. Some people will opt in. And you can use that to trigger a timed nurture sequence. It's not as rich as public permit data, but it's compliant and still powerful. Luna: But that relies on self-reporting, which is notoriously unreliable. People might say 'next month' and then wait a year. Lucas: True. That's why a hybrid approach works best. Self-reported intent for the initial trigger, then behavioral signals — like shopping for tile or searching for contractors — to validate and refine timing. The key is to build a model that combines explicit and implicit data. Most marketing automation platforms can handle that if you set up the right scoring rules. Luna: So the technology isn't the barrier. It's the imagination to see renovation as a lifecycle event worth tracking. Lucas: And the willingness to invest in the data plumbing. But for a brand like Lowe's or Home Depot, the ROI is enormous. They already have the customer relationship. If they could tag every customer who's in a renovation phase and serve them the right product at the right time, they'd capture share from Amazon and specialty retailers. Luna: And for smaller brands — say a local lighting showroom — they can't build proprietary data integrations. They need the platform to do it for them. Lucas: That's where I think the next evolution of marketing automation is headed. Platforms will start offering industry-specific trigger libraries. A real estate vertical might have triggers for listing a home, getting a mortgage pre-approval, closing. A home improvement vertical would have triggers for permit filing, contractor hire, material delivery. The building blocks are there — they just need to be packaged. Luna: It's funny, because we've talked about a lot of blind spots on this show — social media unfollows, credit score changes, pet adoption — but this one feels bigger in scale. Renovations affect almost every household at some point, and the spending is massive. Lucas: Yeah, and it's also more predictable than some of those other events. You can see it coming if you're paying attention. A customer starts buying paint, then drop cloths, then a new faucet — it's a classic signal chain. The platforms just aren't wired to sequence those signals into a unified view yet. Luna: Alright, so let's say I'm a marketer at a home improvement brand listening to this. What's one thing I can do next week? Lucas: Start with your existing customer data. Pull a list of everyone who bought a renovation-adjacent product in the last six months — paint, flooring, tools, fixtures. Then segment them by purchase recency and category. Send a short survey: 'We see you've been working on your home. Which room are you focusing on?' You'll get a decent response rate because it's relevant. Then build a simple automation that adjusts content based on their answer. Luna: That's low-hanging fruit. No data partnership needed. Lucas: Right. And from there, you can start layering more sophisticated signals. The point is, the renovation moment is already happening in your data — you just have to look for it. Luna: It's a good reminder that sometimes the best triggers aren't new data sources, but smarter use of the data you already own. Lucas: Exactly. And if these kinds of marketing conversations have sparked something you've actually used in your own work, that's exactly why we keep doing this show ad-free. It's a choice we made early on — no sponsors, no interruptions, just the thinking. If that model matters to you, you can support it at buy me a coffee dot com slash fexingo. Luna: Yeah, it's a small way to keep the conversation going without selling your attention. Appreciate everyone who does. Lucas: So back to renovation triggers — I think the next frontier is actually predictive. If you can identify customers who are likely to start a renovation within the next three months, you can pre-position your brand before they even begin shopping. Luna: How would you predict that? Home age? Mortgage data? Lucas: Home age is a big one. Houses built in the early 2000s are now twenty-plus years old — prime for kitchen and bath remodels. Also, changes in property tax assessments can signal recent improvements. And if you have access to home equity line of credit data, that's a strong indicator. Someone who just opened a HELOC is likely to spend it on renovations within six months. Luna: That's getting into sensitive data. HELOC information isn't exactly public. Lucas: No, it's not. But a bank that offers both mortgages and home improvement products could use that internally. That's where the real competitive advantage lies — companies that already sit on the data but haven't connected the dots. Luna: So the message for marketing teams is: look at your data assets differently. Don't just think about what customers bought — think about what they're about to do. Lucas: Exactly. And if you can identify the renovation moment, you can own that customer for the next decade. Because after the kitchen comes the bathroom, then the basement, then the landscaping. It's a recurring cycle. Luna: Alright, I'm convinced. Next time I see a permit truck in my neighborhood, I'm going to think about marketing automation. Lucas: That's the spirit. And maybe we'll see a platform that actually lets you trigger on it one day.