Respect what exists

# Improved Text Purchase decisions rely on information. However, people already hold opinions about brands, products, and quality. New information can either change or reinforce these existing views. The question is: Do people search for and interpret information objectively, or do they favor information that confirms their pre-existing beliefs—and what does the evidence tell us? --- **Key improvements:** - "are based on" → "rely on" (more concise) - "could change or confirm" → "can either change or reinforce" (stronger, clearer) - "neutrally" → "objectively" (more precise term) - "prefer information that confirms their existing opinion" → "favor information that confirms their pre-existing beliefs" (eliminates repetition of "opinion," more professional) - "what evidence is known about this" → "what does the evidence tell us" (more direct and engaging)

Studies

Death Penalty Study

Lord, Ross, and Lepper conducted a groundbreaking experiment at Stanford University in 1979. They presented 48 students—half supporters and half opponents of the death penalty—with two fictitious research reports: one showing that the death penalty deters murder, the other demonstrating the opposite. Notably, both studies were methodologically identical. Nevertheless, supporters rated the pro-death penalty study as convincing while finding weaknesses in the opposing study—opponents did exactly the reverse. The striking result: both groups became even more convinced of their original positions. The same objective data had reinforced opposing opinions.

The 2-4-6 Task

In 1960, Peter Wason developed one of the most famous experiments in cognitive psychology. He presented 29 Cambridge students with the number sequence "2-4-6" and instructed them: "Discover my rule by testing your own sequences of three numbers—I'll tell you whether they fit the rule." Most students systematically tested only confirming examples such as "8-10-12" or "20-22-24." The actual rule was simple: "three ascending numbers." However, only 6 of the 29 participants discovered it on their first attempt because they never tested disconfirming examples like "1-2-3" or "5-20-100." They sought only confirmation of their more complex hypotheses.

Selective information search

Fischer and colleagues investigated how people select information in a 2005 study at the University of Munich. They presented 145 German students with 16 carefully selected articles on controversial topics such as nuclear power—8 presenting pro arguments and 8 presenting contra arguments. The results were clear: participants chose articles that supported their pre-existing opinions twice as often. Even more striking, they spent 40% longer reading opinion-congruent texts and rated them as "more scientific," despite all articles being identically written. The effect was particularly pronounced when participants had publicly stated their opinion beforehand.

The Sandwich Board Experiment

In 1977, Lee Ross conducted an elegant experiment at Stanford University. He asked 80 students whether they would be willing to walk around campus for 30 minutes wearing a large sign around their neck that read "Joe's Restaurant." Some said yes, some said no. Then everyone had to estimate how many other students would agree. The astonishing result: Those who had agreed themselves estimated 62% agreement among others. Those who had declined estimated only 33% agreement. Their own decision altered their perception of social reality by nearly twofold—even though everyone had been asked the identical question.

The Alcohol Consumption Study

In 1985, Brian Mullen and his colleagues at Syracuse University investigated how people estimate others' alcohol consumption. They asked 358 students to first report their own drinking habits, then estimate the average consumption of their peers. The correlation was striking: r=0.52 between personal behavior and estimates of others' behavior. Heavy drinkers significantly overestimated how much others drink, while abstainers underestimated it. Both groups projected their own sense of normality onto the social world. As a control, the researchers also asked about objectively measurable facts, such as average height—in those cases, the bias nearly disappeared.

Principle

Which principle for Customer Experience Design can be derived from this? Confirmation bias reveals that successful customer experience depends on respecting and reinforcing customers' existing beliefs and expectations rather than challenging them. Companies should design their communication and product presentation to align with and validate customers' already-positive attitudes. This approach proves particularly effective when introducing new features or services that can be positioned as natural extensions of existing offerings. However, this strategy works optimally only when the target audience holds a neutral-to-positive view of the brand—customers with strongly negative prior experiences may reject even confirming information. The following guidelines demonstrate how to implement this principle in practice.

Guidelines

Align positioning with existing beliefs

First, understand what your target audience already believes—about the problem, potential solutions, and themselves. Then frame your offer as confirmation: "You were right all along. This is what you've been looking for." The following examples illustrate this guideline:

• Oatly: Instead of attempting to convert milk drinkers by claiming "milk is bad," Oatly targets people already receptive to alternatives with messaging like "It's like milk, but made for humans." This approach reinforces their existing belief that plant-based options are the sensible choice.
• Patagonia: The 'Don't Buy This Jacket' campaign succeeded because it validated the target audience's pre-existing beliefs: 'Consumption is problematic, and you're someone who recognizes this.' The paradox: those who already hold this worldview are more likely to make the purchase—precisely because buying the product reinforces their identity.

Gradually shifting beliefs

When you need to change beliefs, proceed incrementally. Begin with what your audience already accepts as true, then build from that foundation. Each step should feel like a natural progression, not a challenge to their existing views. The following examples illustrate this guideline:

• B2B-Software: Instead of saying "Your current system is outdated" (which attacks their past decision), try: "Your system has served you well. The requirements have changed. Here's the logical next evolution." This approach avoids cognitive dissonance.
• Finanzberatung: Instead of 'You invested incorrectly': 'Your strategy was right for the situation at that time. The markets have evolved. Here is the adjustment that continues your original logic.'

Optimize post-purchase communication

Use the critical window immediately after purchase for proactive confirmation messaging: send welcome emails that reinforce the smart decision and share success stories from other customers. Avoid cross-selling during this phase—validate the purchase decision rather than introducing new uncertainty. The following examples illustrate this guideline:

• Apple: After the iPhone purchase: 'Welcome to iPhone. Here's what your new iPhone can do.' The communication emphasizes what the customer has gained – not what they could have purchased.
• Peloton: After purchasing the expensive bike: Onboarding emails that show how other users have achieved their fitness goals. The message: You made the right decision.

Show real usage data instead of assumptions

Don't rely on what customers believe "most people" want. Present concrete data: "X% of our customers use feature Y" rather than "Many customers use..." This is especially critical for product decisions: what the loudest customer describes as "obviously necessary" may represent a niche opinion.

Consciously showcase diverse customer testimonials

People project their own motivations onto others. A tech-savvy customer assumes everyone buys based on features. A price-sensitive customer assumes everyone prioritizes cost. To counter this, deliberately showcase different customer types with distinct motivations: 'Maria bought because of X, Thomas because of Y.' This breaks through the projection bias and makes the actual diversity of customer motivations visible.

Create feedback loops about real preferences

Build in mechanisms that expose customers to the actual distribution of choices. For example, after product configuration, display "X% of customers chose this option." This corrects false consensus assumptions and helps customers validate or reconsider their selections. This approach is particularly effective for decisions where customers feel uncertain.

Validate user research with quantitative data

In interviews and focus groups, participants tend to project their views onto others ('Most people would see it that way'). Treat such statements as hypotheses, not facts. Always validate qualitative insights quantitatively with larger samples. What appears to be consensus in five interviews may simply be a shared niche opinion.