What people claim they will do in surveys often differs dramatically from their actual purchasing behavior. This phenomenon, 'consumer dissonance,' makes survey data on price sensitivity and buying intent highly unreliable. Real-world A/B testing or sales data provides a far more accurate predictor of consumer action.
Related Insights
The common advice to conduct unbiased discovery interviews sounds logical but often fails. The truest way to validate an idea and understand customer needs is through the act of selling. This forces a concrete value exchange and reveals genuine demand in a way that hypothetical conversations cannot.
The most valuable consumer insights are not in analytics dashboards, but in the raw, qualitative feedback within social media comments. Winning brands invest in teams whose sole job is to read and interpret this chatter, providing a competitive advantage that quantitative data alone cannot deliver.
The most significant marketing mistake is using data to push consumers down a brand-desired path they aren't interested in. It is far more effective to identify and build upon existing consumer behaviors. Forcing a misaligned journey is a waste of resources and alienates the customer base.
Most problems customers describe are "pain points" they won't act on. You can't distinguish these from real, actionable demand ("pull") through interviews alone. The only true test is presenting a viable solution and attempting to sell it. Their reaction—whether they try to pull it from you—is the only reliable signal.
When Nespresso priced a feature-rich coffee machine the same as its basic model, customers grew suspicious. Assuming a hidden flaw in the advanced version, they overwhelmingly purchased the simpler one, showing how price equality can paradoxically devalue a superior product.
While transparent, all-in pricing feels better to consumers, high-performing online stores consistently use 'drip pricing'—adding taxes and shipping fees late in the checkout process. This psychological hack works by getting users invested in the purchase before revealing the full cost, making them less likely to abandon their cart. This suggests that in competitive markets, psychological optimization often outperforms straightforward pricing.
Perfection is often perceived as 'too good to be true', leading consumers to suspect that negative reviews have been removed. A Northwestern University study of 100,000 reviews found a tipping point, typically between 4.2 and 4.8 stars for FMCG products, after which purchase likelihood begins to decline. An imperfect score is more believable.
The way a price is presented alters a consumer's emotional response, even if the total cost is identical. Breaking a large sum into smaller installments, like Klarna does, makes it feel more manageable and less intimidating, thus boosting sales.
The perceived value of a discount changes based on its presentation. Test framing it as a percentage off, an absolute amount off, a relative equivalent (e.g., "save a steak dinner"), or simply the final discounted price to see which one drives the most action from your target audience.
Traditional ad testing relies on surveys, which are unreliable as respondents may not be truthful or self-aware. A more predictive method is to measure actual consumer behaviors like attention and emotional response using neuroscience and AI. These are more direct indicators of an ad's potential sales impact.
