This is Part 2 of my series on universal marketing patterns that work across industries. In Part 1, I shared five core patterns—lead generation, customer journeys, next best action, conversion, and attribution—and why they matter no matter what space you’re in.
Lessons Travel Well
Some of the best marketing strategies don’t start in a boardroom—they start in the field, solving real problems. What works in one industry often works in another, once you strip away the jargon and see the pattern underneath.
After working across various industries, I’ve seen the same decision-making patterns emerge again and again. Behind every successful campaign is the same foundation: understanding user behavior, responding with relevance, and using data to drive timing, content, and next steps.
Marketing is less about mastering tools, and more about recognizing patterns and applying them wisely esp. as a data leader. In this post, I’ll try to share real stories that show how marketing lessons transfer across industries. For each, I’ve included key takeaways for data and marketing leaders—so you can guide your teams with more clarity, speed, and impact.
1. Field Prospecting: From Landscaping to Education
Pattern: Find the right people at the right moment
I once watched a landscaper drive through a neighborhood, looking for signs that a home was being renovated—new windows, dumpsters, scaffolding. Why? Because that’s the perfect time to offer lawn and hardscape services. The customer’s already in “fix-up” mode.
That same concept applies to higher ed, car shopping or any similar industry. Prospective students show signs when they’re exploring options: searching for majors, comparing schools, attending virtual tours, etc. Those signals show up as data: site visits, engagement patterns, inquiries, when captured can help colleges time their outreach. It’s not about blasting messages—it’s about contacting at the right moment.
Don’t overengineer your lead models. Focus on identifying actionable signals that show someone is in a moment of need. Operationalize those signals so your teams can act on them without friction. A scrappy behavioral model can outperform a polished but static score.
2. Personalization: From E-Commerce to College Matching
Pattern: Reduce friction through guided discovery
E-commerce thrives on “you might also like…” It’s a simple but powerful way to move people forward without overwhelming them. Why not borrow that logic, to build college recommendation engines—based on student preferences, geography, and interests. Rather than make students start fresh on every search, help them continue the journey.
Personalization isn’t about creepiness—it’s about relevance. Think in terms of “next best options,” not full automation. What’s the next logical step someone like this would want to take? If your data stack can support that one question, you’re already ahead.
3. Funnel Design: From Automotive Sales to Complex Buyer Journeys
Pattern: Simplify decision-making without oversimplifying the options
When we launched an automotive marketplace, we learned how easy it was to overwhelm users. Too many filters, too much choice, not enough guidance. People dropped off. Car buying is high-stakes—just like choosing a school, vendor, or long-term solution.
So streamline the funnel: fewer choices up front, clearer steps, more visual guidance. Apply the same approach cross-industry in higher ed and enterprise tools: design the journey with confidence-building in mind, not just speed.
Don’t confuse “more features” with “more value.” Use funnel data to identify where users lose confidence—and address it through better UX, clearer messaging, or improved onboarding. You don’t need more leads. You need more people finishing what they started.
4. Form Optimization: From SaaS to B2B Lead Capture
Pattern: Make taking action feel easy
In SaaS, short sign-up flows are key—only ask for what you need, make it clear what happens next, and remove friction. Bring that same mindset into B2B lead capture optimizing overly complex contact forms that otherwise scare off qualified prospects. By simplifying the forms, removing jargon, and adding clearer expectations (“we’ll respond within 1 business day”), companies can increase conversions without changing the offer or audience.
Form optimization is often the highest-ROI fix sitting in plain sight. Don’t overlook it just because it seems “basic.” Partner with marketing to shorten paths to value, reduce hesitation, and A/B test language. The data will tell you quickly what’s working (Data Leaders — listen carefully!).
Conclusion: Lead Through Pattern Recognition
If you lead data teams, your job isn’t to master every tool—it’s to help your organization see clearly and act with leverage. That means recognizing which patterns are playing out, which playbooks can be reused, and which data points actually matter in the decision journey.
When you think cross-industry:
- You prioritize signal over surface
- You design journeys with intent, not inertia
- You focus your stack on what enables action, not just tracking
Marketing is about understanding people, and people follow patterns. The more confidently you recognize those patterns, the faster you can build systems that serve them.