- Tension: Marketers expect automation to solve outreach inefficiencies, but the reality often demands more human input—not less.
- Noise: Conventional wisdom claims automation simplifies marketing, yet this oversimplification blinds teams to the complexities of buyer psychology and organizational alignment.
- Direct Message: Automation doesn’t replace strategy—it reveals the gaps in it, and succeeding with it requires deeper behavioral insight and cross-functional collaboration.
To learn more about our editorial approach, explore The Direct Message methodology.
This article was originally published in early 2022 and was last updated on June 12, 2025.
The illusion of effortless automation
When LEGO Education turned to marketing automation, the goal was clear: reach more teachers, more meaningfully, with fewer bottlenecks. The challenge was familiar—growth outpacing infrastructure—and the solution seemed straightforward: automate. Streamline. Scale. If only it were that simple.
In my experience working with growth-stage tech companies, this is a recurring theme. Marketing automation is sold—and often bought—as a turnkey engine for performance. But like many performance tools, the benefit isn’t in the tool itself; it’s in how the organization reshapes itself to use it effectively.
LEGO Education’s story offers a valuable case study. On the surface, it’s about switching platforms and segmenting better. Underneath, it reveals a deeper truth about expectations, complexity, and what automation actually demands from a marketing organization—and what it teaches us about our assumptions.
The gap between what we expect and what actually works
For many teams, the promise of automation brings a specific expectation: that technology will make things easier. Less manual work. More output. Shorter feedback loops. In short—more scale, less stress.
But for LEGO Education, adopting a marketing automation platform didn’t deliver effortless success. It revealed gaps in the customer journey that hadn’t been visible before. Suddenly, the team saw the disconnects between content and context, touchpoint and timing, interest and intent. Automation magnified what was missing.
Brandee Johnson, senior marketing manager at LEGO Education, described their old platform as a limiting factor—it lacked lead scoring and automation capabilities. But once they upgraded, the real challenge emerged: turning granular customer data into meaningful behavioral signals. As Johnson put it, “Just like with any other tool, you can get out of it what you put into it.”
This is where the expectation-reality gap becomes clear. Automation doesn’t reduce complexity—it reorients it. Instead of solving for volume, teams must solve for relevance, sequencing, and cross-functional agility. That’s a higher bar, not a lower one.
And in the education market, where purchasing decisions follow long cycles, involve multiple stakeholders, and are often dictated by institutional budgeting rather than personal preference, the challenge compounds. Behavioral clarity becomes essential.
Why the standard playbook doesn’t apply
Conventional wisdom paints automation as a silver bullet—set it up, and watch the leads roll in. But much of this thinking comes from consumer-oriented models where purchase decisions are faster, signals are clearer, and emotional triggers are more predictable.
In B2B environments like LEGO Education’s, that playbook breaks down. The path from awareness to action isn’t linear—it’s looping, political, and often invisible. Teachers aren’t the final decision-makers. Budgets are locked into academic calendars. And engagement metrics—like email opens or video views—don’t always correlate with real intent.
What I’ve found analyzing consumer behavior data across verticals is that automation works best when the organization already has a sophisticated understanding of its buyer’s psychology. That means knowing not just what people click, but why—and how to respond to that why in the flow of communication.
Many companies miss this. They focus on system capabilities—lead scoring, trigger campaigns, segmentation logic—without doing the deeper work of journey mapping, message calibration, and interdepartmental feedback loops. Without that behavioral scaffolding, automation doesn’t clarify—it confuses.
This is where LEGO Education made a pivotal move. Instead of treating automation as a marketing shortcut, they treated it as a behavioral insight engine. That shift made all the difference.
The essential truth we often miss
Automation doesn’t simplify marketing—it exposes its complexity. To succeed, teams must align around strategy, psychology, and sustained experimentation.
What it really takes to build smarter campaigns
The real takeaway from LEGO Education’s transformation isn’t that they automated more—it’s that they learned more. Their success hinged on several key moves:
1. Behavioral intelligence over raw data
Act-On gave LEGO Education access to richer engagement data, but they had to translate that into behavioral narratives. Who clicked wasn’t as important as why they clicked—and what that action suggested about their place in the decision journey. That shift—from static profiling to dynamic understanding—is where the power of automation truly lies.
2. Investing in talent, not just tech
Johnson noted that simply installing the platform wasn’t enough. The team needed more marketing capacity and expertise to realize the system’s full potential. This echoes a behavioral economics principle I often reference: people over-index on tools and under-invest in capability. The tool doesn’t make the strategy; the team does.
3. Building a feedback loop between marketing and sales
Too many organizations treat marketing automation as a one-way outbound engine. But LEGO Education built a loop. When a lead watched a webinar or attended an event, that signal wasn’t just logged—it was acted on. Sales followed up with context. This required tight alignment and shared definitions of lead quality—something most companies think they have, but few operationalize.
4. Recognizing the emotional layer in B2B decisions
While it’s tempting to see education purchases as purely rational, there’s a strong emotional current beneath them: the desire to empower students, the pressure of performance metrics, the fear of wasting limited budgets. LEGO Education leaned into this by crafting content that resonated with the teacher’s mission—not just their metrics. In behavioral terms, they acknowledged the dual-system decision-making at play: emotional intuition alongside rational evaluation.
Rethinking automation as a learning system
We need to stop treating automation as a marketing fix and start treating it as a learning framework. It’s not just about sending the right email—it’s about understanding the context that makes the email right in the first place.
During my time consulting for SaaS platforms in the edtech space, the highest-performing teams weren’t the ones with the flashiest campaigns or deepest data stacks. They were the ones willing to revisit assumptions, iterate quickly, and learn continuously. Automation didn’t make them smarter; it amplified their curiosity and discipline.
That’s the lesson in LEGO Education’s story. Not that automation solved their challenges, but that it revealed the real work to be done—and gave them the tools to pursue it.
Marketing automation isn’t about pressing buttons. It’s about building better questions.
And that, just like a good LEGO set, starts with understanding how each piece fits together.
