How to Build Better Prototypes: Borrow Brilliance from Across Industries (Part 3)

June 10, 2026|Karl Dionne

5 min read

In this four-part series on rapid prototyping, we’re exploring how teams can move quickly without guessing, using expert insight, real-world data, structured research, and disciplined testing to turn early ideas into smarter, more validated products.

In Part 1, we explored how expert insight can reduce uncertainty and improve decision-making early in the prototyping process. In Part 2, we examined how research and data help validate prototypes before significant investment is made. 

In Part 3, we shift our focus outward, exploring how the world’s best digital experiences can inspire better prototypes by revealing proven solutions to common human behaviours and usability challenges.

The Problem With Looking Only at Competitors

Many organizations limit their research to direct competitors. The result?: Everyone ends up copying the same patterns, the same workflows, and the same assumptions, often reproducing the same frustrations users already dislike.

But people don’t compare your product only to competitors in your category anymore. They compare your experience to every exceptional digital experience they use every day.

The same person who:

• • Books travel through Airbnb
• • Orders dinner on Uber Eats
• • Shops on Amazon
• • Tracks rewards in Starbucks
• • Communicates in Slack
• • Streams content through Netflix

…will bring those expectations into your platform too.

Users now expect:

• • Frictionless onboarding
• • Intuitive navigation
• • Intelligent recommendations
• • Real-time feedback
• • Personalization
• • Seamless mobile experiences
• • Low cognitive effort

Not because your competitors trained them, but because the market trained them.

Best-in-Class Analysis Changes the Conversation

This is where Best-in-Class Analysis becomes one of the most valuable tools in rapid prototyping. Instead of studying only industry peers, teams analyze organizations that have mastered specific behaviors exceptionally well.

For example:

• • If you’re building scheduling functionality, studying Airbnb’s booking flow may be more valuable than studying competitors with clunky calendar systems.
• • If you’re designing family communication tools, Slack’s notification hierarchy or WhatsApp’s simplicity may offer stronger behavioral lessons.
• • If you’re building loyalty mechanics, Starbucks and Nike provide powerful examples of habit loops, gamification, and emotional engagement.
• • If you’re improving reordering experiences, Amazon and Shop offer proven friction-reduction strategies.

We touched on this in our post about the Power of Familiar UI Models. The goal isn’t copying visual design. It’s understanding the psychology behind why certain experiences feel effortless.

Great Prototypes Reduce Cognitive Load

One of the biggest drivers of product adoption is familiarity. Humans naturally gravitate toward experiences that feel intuitive because they align with mental models they already understand.

That’s why the strongest prototypes often feel:

• • Easy to navigate
• • Predictable in the right ways
• • Emotionally comfortable
• • Immediately usable

The mistake many teams make is confusing innovation with complexity. However, the best innovation often feels obvious in hindsight. Why? Because it mirrors behaviors users already trust elsewhere. Borrowing brilliance helps teams avoid reinventing interaction patterns users have already learned across other platforms. This dramatically reduces friction during onboarding and adoption.

The Fastest Builders Learn From Existing Human Behavior

Organizations can spend months, even years, trying to validate interaction patterns that leading companies have already tested at scale.

The reality is that many of the world’s largest platforms have invested millions into understanding:

• • Attention
• • Habit formation
• • Navigation behavior
• • Trust signals
• • Conversion psychology
• • Reward systems
• • Notification timing
• • Retention loops

Smart product teams study those patterns before reinventing them. Not to imitate, but to accelerate learning. That’s what makes rapid prototyping more strategic:

• • Fewer avoidable mistakes
• • Faster validation
• • Stronger usability
• • More intuitive workflows
• • Higher stakeholder confidence

Innovation Happens Between Industries

Some of the best digital experiences emerge when organizations apply proven behaviors from one industry into another:

• • Healthcare platforms borrowing hospitality-style booking experiences.
• • Financial apps using ecommerce-style onboarding simplicity.
• • Enterprise software adopting consumer-grade UX expectations.
• • Retail loyalty systems borrowing gaming mechanics.

This cross-industry thinking often creates the perfect balance:

• • Differentiated enough to feel innovative
• • Familiar enough to feel intuitive

Because users rarely want to “learn” entirely new behaviors. They want products that work the way modern digital experiences already taught them to expect.

A Simple Best-in-Class Exercise

One of the easiest ways to apply this approach is to start by identifying the three most important experiences within your product, service, or process. For example, you might choose:

• • Onboarding and first-time user experience
• • Search and discovery
• • Personalization and recommendations

Ask your team to identify the three applications, websites, or digital products that execute each of those experiences exceptionally well, regardless of industry. 

As we discussed in Part 1 of this series, involving experts with cross-industry experience can make this exercise even more valuable. People who have worked across multiple sectors often recognize successful patterns that industry insiders overlook. They can quickly identify proven approaches, explain why they work, and help teams avoid costly experimentation.

This simple benchmarking exercise frequently uncovers ideas that would otherwise take months of trial and error to discover. More importantly, it helps prototype teams build on proven human behaviours rather than assumptions, resulting in faster validation, stronger usability, and greater confidence in the final solution.

Why This Matters More in the AI Era

As we noted in earlier posts in this series on prototyping,  AI has made idea generation incredibly fast. New app concepts, interfaces, workflows, and automation systems can now appear almost instantly. But speed creates a new risk: organizations can now build unfamiliar, overly complex experiences faster than ever before.

That’s why behavioral intelligence matters more than ever. The companies that win in the AI era won’t simply be the ones generating the most ideas, they’ll be the ones designing experiences people instinctively understand and trust. And that comes from studying proven human behavior patterns across the market.

Build Smarter by Learning From the Best

Rapid prototyping is about learning from the best experiences people already trust,  wherever they exist.

At KPDI Digital, Best-in-Class Analysis helps teams move beyond assumptions and build products rooted in proven human behavior, usability patterns, and real-world engagement psychology.

Because the fastest path to innovation often starts with understanding what people already know how to use.