Latest / Marketing Automation with Fexingo: HubSpot, Marketo, and Automated Customer Journeys / The Death of the Linear Funnel in Marketing Automation
Transcript
- Lucas: We spend so much time talking about getting people into the top of the funnel, but I think we have a massive blind spot when it comes to what happens once they’re already inside the system. Most marketing automation platforms are still built around this idea of a linear path, like a slide where you start at one end and inevitably land at the bottom. But if you look at actual buyer behavior today, especially in complex b2b environments, nobody moves in a straight line. Luna: Right, because even in consumer goods, people bounce between categories all the time before they commit. It feels like our software assumes customers are robots following a script rather than humans with changing priorities. Lucas: Exactly. And the damage isn't just theoretical. When a platform forces a rigid sequence, it penalizes lateral movement. If someone drops off a pricing page, goes back to read a blog post three weeks later, and then checks out a competitor site, the automation often sees that as disengagement or loss. So it stops sending relevant content, effectively freezing the account in a dead zone while the rep thinks the lead is cold. Luna: That sounds like the classic case where a tool optimizes for activity metrics instead of actual intent signals. Are we seeing specific numbers on how much revenue gets stuck in these linear bottlenecks? Lucas: There was a recent study by an independent MarTech analytics firm that tracked over five thousand mid-market deals. They found that approximately thirty percent of closed-won opportunities involved at least two distinct lateral movements away from the primary product category during the evaluation phase. The teams using node-based journey maps recovered nearly forty percent more of those stalled deals compared to teams relying on strict stage-gate workflows. Luna: Thirty percent is huge. That means almost a third of your pipeline is being misclassified as dead simply because the workflow wasn't flexible enough to handle curiosity. Lucas: It’s not just curiosity though; it’s risk mitigation. Buyers are more cautious than ever. They want to see if there’s a better option before they lock in. The problem is that most crm setups treat any deviation from the expected timeline as a failure state. So the system automatically pauses outreach. It’s basically putting the deal in a digital freezer. Luna: So how do you build a node-based map? Is it just about adding more branches to the existing logic trees, or does it require a fundamental shift in how we define success metrics? Lucas: It requires shifting from stage-based metrics to signal-based metrics. Instead of asking, did the prospect move from consideration to decision, you ask, what did they interact with last? Did they download a technical white paper? Did they visit the partner directory? Those are positive signals even if they aren't direct buying actions. You need to trigger nurture paths based on those lateral interests, not just silence. Luna: That makes sense. If someone reads about integrations, send them integration case studies, not a generic product demo reminder. It keeps the context alive even if they aren't ready to buy yet. Lucas: Precisely. And this is where the technology gap shows up. A lot of legacy platforms were designed when email was the primary driver. They assumed that if you didn’t open the email, you weren’t interested. But now, engagement is fragmented across webinars, community forums, social proof pages, and private demo requests. If your automation only listens to email opens, you’re deaf to half the conversation. Luna: I’ve seen this happen with software subscriptions too. People cancel, then come back six months later because they realized they needed the feature again. Does the current standard handle that reactivation loop well? Lucas: Generally, no. Reactivation is treated as a separate campaign, often led by a discount offer. But that misses the psychological nuance. The person who left because they couldn’t find a specific feature doesn’t want a discount; they want confirmation that the feature now exists. Sending a fifty percent off coupon to someone who left due to a product gap is actually insulting. It suggests you think money solves a usability problem. Luna: That’s a sharp distinction. So the automation needs to be smart enough to segment by reason for exit, not just the fact of exit. That requires data hygiene that most companies struggle with. Lucas: It does. And that’s the hard part. You need clean exit survey data or clear support ticket tags linked directly to the user profile in your marketing platform. If that link doesn’t exist, you’re guessing. And guessing in automation is dangerous because you might spam someone who explicitly asked to be ignored, or worse, ignore someone who was just waiting for the right nudge. Luna: Speaking of nudge timing, how do you balance frequency when you’re dealing with these lateral movements? You don’t want to overwhelm someone who is actively comparing options. Lucas: Frequency caps are essential, but they need to be dynamic. If a user engages heavily with comparison content, you might increase the cadence of related resources. If they go silent, you drop to a low-frequency check-in. Static weekly blasts are the enemy of modern journeys. They assume every prospect has the same attention span and urgency level, which is never true. Luna: It feels like we’re moving from broadcasting to contextual listening. The tool becomes less of a megaphone and more of a concierge service. Lucas: That’s the best way to put it. A concierge watches what you look at and suggests the next logical step. A megaphone just yells the same message until you cover your ears. The platforms that win will be the ones that act like intelligent guides rather than automated broadcasters. Luna: Do you think this shift is happening faster in enterprise or in smaller startups? Startups usually have less legacy baggage to deal with. Lucas: Startups definitely adapt faster, but they often lack the volume to justify complex automation. Enterprises have the data but are hamstrung by compliance and rigid approval processes. There’s a middle ground emerging where martech stacks are becoming composable. You can swap out the engagement engine without rebuilding the entire crm foundation. Luna: Composable stacks sound like the future. It allows you to plug in specialized tools for specific journey nodes rather than forcing everything through one monolithic vendor. Lucas: Exactly. You might use one tool for predictive scoring, another for personalized website experiences, and a third for email orchestration. As long as the data flows seamlessly between them, the user experience remains consistent regardless of which backend systems are pulling the strings. Luna: How do you measure the roi of this kind of flexibility? Traditional attribution models credit the last click or the first touch. Neither really captures the value of a lateral move. Lucas: You have to look at assisted conversions. How many times did a lateral content piece appear in the path to purchase? If you remove the webinar attendance from the history, does the conversion probability drop significantly? If yes, that asset has high assisted value. You need multi-touch attribution that weights intermediate steps, not just the endpoints. Luna: That’s a lot of data to process. Are there any pitfalls leaders should watch out for when implementing these node-based systems? Lucas: The biggest pitfall is complexity creep. You start adding so many branches and conditions that the workflow becomes unmaintainable. Eventually, no one understands what the bot is supposed to do, so they turn it off or leave it running blindly. You need governance. Clear rules on when to add a branch and when to kill one. Luna: Governance is key. Otherwise, you end up with a spiderweb of emails that confuse the customer and exhaust the marketing team trying to manage them. Lucas: Absolutely. And remember, the goal is clarity for the buyer, not cleverness for the marketer. If the customer can’t intuitively understand why they’re receiving a certain message, you’ve failed the journey map. Luna: I’m curious, what role does ai play in this? Can algorithms predict the lateral moves before they happen? Lucas: Ai is getting very good at pattern recognition. It can identify early signs of lateral interest based on subtle changes in browsing behavior or content consumption. It can pre-emptively route users to the right node before they even realize they’re looking for alternatives. But it’s not magic. It needs clean training data and constant human oversight to avoid bias. Luna: So it’s a partnership between algorithmic prediction and human strategic direction. Not a replacement. Lucas: Correct. The algorithm handles the volume and speed; the human handles the nuance and ethics. Together, they create a journey that feels personal and responsive rather than calculated and cold. Luna: This feels like a major evolution from where we started ten years ago. It’s less about capturing leads and more about sustaining relationships through uncertainty. Lucas: That’s the core shift. We used to think of marketing as a capture mechanism. Now it’s a retention engine. The money is in keeping the relationship alive during the quiet periods, not just shouting during the sale. Luna: If you haven’t already, take a quick look at your current workflows. Are they linear slides or flexible networks? It might be worth the audit. Lucas: Definitely. And if these conversations have helped you rethink your own approach, consider supporting the show. Buy me a coffee dot com slash fexingo helps keep the research deep and the insights free for everyone. Luna: Thanks for the support, listeners. It really keeps the lights on and the ideas flowing. Lucas: Back to the data. One final thought: as we move into late twenty twenty six, the expectation for seamless, non-linear service is becoming the baseline. Companies that cling to linear funnels won’t just lose market share; they’ll lose relevance entirely. Luna: So the question isn’t whether you can afford to update your automation, but whether you can afford to stay static while your buyers evolve. Lucas: Exactly. The journey is messy, so your tools should be messy too, just in a controlled, intelligent way. Thanks for tuning in.