Latest / Marketing Automation with Fexingo: HubSpot, Marketo, and Automated Customer Journeys / Why Marketing Automation Ignores Your Dietary Shift
Transcript
- Lucas: Let me read you an email I got from a listener named Sarah. She said she switched to a plant-based diet three months ago, and yet she keeps getting bombarded with emails from a meal kit service promoting their steak and salmon recipes. She's tried to update her preferences, but the marketing automation still treats her like a carnivore. Luna: Ouch. That's a classic data silo problem. Her dietary change is a first-party signal — she likely updated her profile — but the automation rules are hardcoded to look at purchase history or past engagement, not self-reported preferences. Lucas: Exactly. And it's not just meal kits. Think about grocery loyalty programs, supplement subscriptions, even clothing stores that push leather belts. Once you change your diet, you effectively become a new customer to many brands, but they haven't built the triggers to recognize that transition. Luna: So the gap is that marketing automation typically treats diet as a static attribute, not a dynamic life event. Lucas: Right. And the interesting thing is that dietary shifts are becoming more common — not just veganism, but keto, gluten-free, low fodmap, intermittent fasting. Each of these opens up a whole new product ecosystem, but the data model hasn't caught up. Luna: I saw a stat from an Accenture survey last year that said 68 percent of consumers who changed their diet in the prior year received irrelevant marketing from their previous food brands. That's a huge churn risk. Lucas: And that churn is preventable. But the fix requires marketers to rethink how they handle first-party data. Most platforms like HubSpot or Marketo let you create a custom property for 'dietary preference', but that property is usually buried under 'demographics' and rarely triggers a sequence reset. Luna: Right, because the rule engine typically says: if a customer has bought steak recipes in the past, keep sending steak recipes until they opt out or unsubscribe. It's a logic of recency and frequency. Lucas: And that's the problem. The automation is optimized for what customers have done, not who they are becoming. A diet change is a signal that their needs have fundamentally shifted — but the system sees it as a minor profile update at best. Luna: So what would a 'diet shift trigger' look like in practice? Lucas: First, you need a way to capture the change at the point of intent. When Sarah updated her profile to 'vegan', that should have immediately paused any sequences related to animal products and enrolled her in a welcome series for plant-based alternatives. That's basic event-driven automation. Luna: But many brands don't even ask for dietary preferences during signup. They collect birthday, gender, maybe location — food preferences are an afterthought. Lucas: Right, and even when they collect it, the field is often free-form text, which is a nightmare for segmentation. 'Vegan', 'plant-based', 'whole food plant-based' all mean something similar but the system treats them as different categories. Luna: So you also need a taxonomy. Map common variants to a standard attribute. Then the trigger can be 'dietary preference changed from any non-vegan value to vegan' — that's a concrete condition. Lucas: Exactly. And once triggered, the system should not just change the email content. It should also adjust product recommendations, coupon types, even shipping preferences. If you're suddenly buying almond milk instead of dairy, you might want a different subscription cadence. Luna: I wonder about the reverse. What if someone goes from keto to a balanced diet? Or from vegan back to omnivore? The system needs to handle both directions. Lucas: Yeah, and that's where a lot of automation falls short. They program for the 'new year resolution' diet change but forget that diets are iterative. A customer might try paleo for three months, then switch to Mediterranean. Each iteration is a micro life event. Luna: So the solution isn't just one trigger, it's a continuous listening strategy. You need to monitor not just profile changes but also purchase behavior shifts. If someone stops buying coffee creamer and starts buying oat milk, that's a leading indicator. Lucas: Right. And the best brands are starting to use machine learning to detect these pattern shifts without requiring the customer to explicitly update their profile. But that's still rare. Most are still in the rules-based world. Luna: Which brings us back to the listener's frustration. She did the right thing — she updated her profile. And the system ignored her. Lucas: And that's why this is such a missed opportunity. The brands that catch a diet change early can build incredible loyalty. You're showing the customer you see them as a whole person, not just a transaction history. Luna: I've got a personal example. After I went gluten-free a few years ago, one specialty grocer sent me a coupon for their new gluten-free pasta within a week. I've been shopping there ever since. That's the power of a timely trigger. Lucas: That's exactly what automation should do. And it's also why we dig into these gaps every day on this show. We deliberately keep the conversations ad-free so we can call out specific failures and solutions without any sponsor constraints. Luna: And it's listener support that makes that possible. If you've gotten value from episodes like this one, and you want to support that independence, you can find us at buy me a coffee dot com slash fexingo. No pressure, just a note that every bit helps keep these topics deep and unfiltered. Lucas: Yeah. So, back to the data model. How do you design a system that not only catches a diet change, but also primes the customer for what comes next? Luna: I think you need to think about the customer journey not as a linear funnel, but as a set of concentric circles. The diet change moves them into a new inner circle of needs. Lucas: Right. And you need to sequence that transition. For Sarah, the first contact after her profile update should have been: 'Welcome! Here are our top vegan recipes.' Then a week later: 'Our vegan meal prep guide.' Then a personalized offer based on her first purchase in the new category. Luna: That sounds like a basic welcome series, but tailored to a change instead of a new acquisition. It's surprisingly rare. Lucas: It is. And I think part of the reason is that marketing teams are organized around acquisition and retention, not around life events. Dietary shifts fall through the cracks because they don't neatly fit into either bucket. Luna: Yeah, and that organizational silo maps directly to the technology silo. The campaign manager for dairy products doesn't talk to the one for plant-based alternatives. Lucas: Which means a customer changing diets is essentially handed off from one team to another — but the handoff is never automated. It's a manual, error-prone process. Luna: So to fix it, you need both a technical trigger and an organizational process. The trigger pauses old campaigns and enrolls the new. The process ensures someone reviews the transition for edge cases. Lucas: Right. For example, what if Sarah's profile said she had a child who eats meat? The system shouldn't just assume the whole household is vegan. That's another layer of complexity. Luna: That's a great point. A dietary shift is often personal, not household-wide. So the automation needs to respect individual preferences within a shared account. Lucas: And that's a whole other episode — we actually did one on shared account changes recently. But for today, the takeaway is this: if you're a marketer, ask yourself whether your automation treats diet as a static field or a dynamic event. Luna: And if you're a consumer like Sarah, vote with your inbox. Unsubscribe from the brands that don't see you, and reward the ones that do. Lucas: Well said. That's it for this episode of Marketing Automation with Fexingo.