Check understanding

Purchase decisions are based on perceived understanding. Customers believe they know how a product works, what it does, and why it is valuable. But how deep is this understanding really? The key question is: Do people systematically overestimate their own understanding, and what happens when they're required to explain it—and what does the evidence tell us?

Studies

The Explanation Experiment

In 2002, Yale University researchers Leonid Rozenblit and Frank Keil conducted a groundbreaking experiment on overconfidence. They asked 85 students to rate their understanding of everyday objects—such as zippers, toilet flushes, and bicycle gears—on a 7-point scale. Initially, participants rated themselves at an average of 4.5 points, indicating considerable confidence. Then came the crucial moment: they were asked to explain step-by-step how these objects actually worked. Suddenly, most faltered. Keep in mind, these were items they used daily. The result was sobering: after their failed explanation attempts, self-assessments plummeted to just 2.8 points. The illusion of understanding burst like a soap bubble the moment they had to articulate their supposed knowledge.

Mechanic exposes ignorance

In a follow-up study, Rozenblit and Keil investigated which objects produce particularly strong knowledge illusions. They tested 112 participants across different categories: mechanical devices, natural phenomena, and psychological concepts. The surprising result: self-overestimation was strongest with everyday mechanical objects like sewing machines or helicopters, where self-confidence dropped by an average of 1.7 points after explanation attempts. In contrast, participants remained relatively confident with more abstract topics like "Why do we dream?" Apparently, familiar mechanics suggest a depth of understanding that doesn't actually exist. The researchers called this the "illusion of explanatory depth"—we confuse familiarity with understanding.

Principle

Which principle for Customer Experience Design can be derived from this? People systematically overestimate their understanding of products and how they work, leading to unrealistic expectations and costly purchasing mistakes. This cognitive bias is particularly problematic with complex or configurable products, where customers believe they have thoroughly considered all aspects, even though their knowledge remains superficial. Companies can correct this overconfidence through interactive experiences that prompt customers to reflect on their actual level of understanding and make more realistic purchase decisions. This principle works particularly well for products that require explanation, but loses effectiveness with very simple products or emotional impulse purchases. The following guidelines demonstrate how to implement this principle in practice.

Guidelines

Virtual Product Testing

Provide interactive simulations that allow customers to virtually 'experience' their configured product—not merely view static images. People tend to overestimate how well they understand products. Interactive demonstrations reveal how selected options actually perform, correcting misconceptions before purchase. The following examples illustrate this guideline:

• IKEA Place: AR app displays furniture in your own home - virtual trial placement instead of imagination.
• Auto-Konfigurator: 360° interior view of the configured vehicle - not just exterior view, but 'What does it look like when I'm sitting inside?'

Offer try-before-you-buy

Enable genuine try-before-you-buy options—free trial periods, test usage, and samples. While virtual simulations are valuable, real experience is superior. For complex or expensive products, try-before-you-buy maximally reduces uncertainty. The following examples illustrate this guideline:

• SaaS-Trials: 14-day free trial - all features, no credit card required. Real product experience.
• Matratzen-Test: '100 nights trial sleep' - real long-term experience instead of showroom impression.

Show realistic preview

Display products realistically rather than in idealized settings—use authentic photos in real environments and genuine usage scenarios. Idealized representations create unrealistic expectations that lead to disappointment. Realistic previews, even those showing minor imperfections, set accurate expectations and reduce product returns. The following examples illustrate this guideline:

• User-Generated-Content: Customer photos alongside studio photos - real application instead of perfect staging.
• Farbtreue-Hinweis: 'Colors may vary depending on screen. Request samples when selecting colors.' - realistic expectations.