Product reviews have become one of the most powerful signals in modern commerce. From booking a hotel to choosing enterprise software, consumers increasingly rely on aggregated results as an indicator of quality. However, new research suggests that something as simple as how those ratings are displayed – stars versus numbers – can systematically skew perception, with important implications for businesses.
A study published in Journal of Marketing Research has found that consumers interpret fractional ratings in different ways depending on whether they are presented visually, as stars, or numerically. The difference is subtle but important: a score of 3.5 appears materially higher when shown as a star than when shown as a number.
The research, led by Deepak Sirwani of the University of British Columbia and Manoj Thomas of Cornell University, sheds light on how cognitive processing affects decision-making. It also raises a broader question for companies: are they accurately communicating value or are they inadvertently misleading their customers?
The psychology behind stars and numbers
At the heart of the findings is a divergence in the way the brain processes images versus numbers. When consumers see a typical five-star rating with a half star included, they instinctively “finish” the picture, turning the partial star into something closer to a full star.
This visual bias has a measurable effect. In six controlled experiments, researchers consistently found that participants overestimated partial star ratings, perceiving them as closer to the other whole number. In contrast, when the same ratings were expressed numerically, consumers tended to anchor on the leftmost digit. A rating of 3.5, then, felt more like a 3 than a 4.
Essentially, the same underlying result produces two different perceptions depending on the format. The result is a systematic distortion: the stars swell, the numbers fade. For marketers and product teams, this is not an academic curiosity. Ratings affect conversion rates, pricing power and brand perception. In digital markets, small differences in perceived quality can translate into disproportionately large differences in sales.
The significance of these findings becomes clearer when set against the growing importance of ratings in consumer decision making. Online reviews now work alongside price and brand as key factors shaping shopping behavior.
Previous studies have shown that even marginal changes in ratings, sometimes as little as 0.2 points, can affect sales results. Cornell-led research implies that such differences may not always reflect real product differences, but rather the effects of presentation.
This introduces a new layer of strategic complexity. A company that displays ratings numerically may inadvertently sell its product against a competitor that uses stars. In contrast, star-based systems can create high expectations that are difficult to meet, increasing the risk of customer dissatisfaction.
Whether intentional or not, format becomes a competitive variable.
Canadian businesses navigating the valuation economy
These dynamics are particularly important in Canada’s rapidly evolving digital economy, where platform-based business models and AI-driven recommendations are becoming more prevalent.
- Ecommerce (eg, Shopify-powered stores): Star icons are the main rating signal.
- Travel and booking (eg Hopper): Star style or visual scores dominate.
- App Markets and SaaS Tools: star ratings are standard.
Shopifywhich powers a large ecosystem of online merchants globally. Within the app market and merchant storefronts, ratings play a central role in shaping adoption decisions. A subtle format bias, stars vs. numbers, can influence how marketers choose tools, ultimately influencing which services scale.
Similarly, the Canadian travel platform Hopperwhich uses predictive analytics to predict prices, relies heavily on customer trust and perceived reliability. In a sector where users compare dozens of options, rating presentation can influence booking decisions, especially when the differences between competing services are marginal.
The venture artificial intelligence firm time offers another angle. While its customers are businesses rather than consumers, evaluation metrics and comparison results perform a similar function to ratings. How performance is visualized as graphs, scores, or quality indicators can shape customer perception in analogous ways.
Even in healthcare and life sciences, where firms like it Deep genomics operation, communication of model performance, and predictive accuracy must balance clarity with interpretability. Numerical accuracy is essential, but human interpretation remains central.
In all these sectors, learning is consistent: presentation affects perception, even when the underlying data remains unchanged.
Implications for trust and transparency
Cornell’s findings raise a wider issue all around transparency in digital markets. If common evaluation formats are systematically misinterpreted, then much of consumer decision-making is based on cognitive shortcuts rather than objective evaluation.
For regulators and platform operators, this presents a challenge. Standardizing rating systems can reduce variability, but it can also limit flexibility for businesses. Alternatively, hybrid formats, such as combining stars with clear numerical values, may provide a more balanced signal or, alternatively, further confuse consumers.
There is also a role for design. Platforms could experiment with clearer visual cues, such as scaling indicators or contextual benchmarks, to reduce misinterpretation. Small tweaks to user interfaces can bring big improvements in decision quality.
From a compliance perspective, companies should consider whether their valuation submissions comply with the principles of fair representation. In sectors where consumer protection is critical, misleading impressions – even if unintentional – can attract scrutiny.
Given that visual cues and numerical data seem to trigger different cognitive pathways, then in a market increasingly mediated by algorithms, reviews and charts, these differences matter. Businesses that understand the behavioral dimension of data presentation are better positioned to communicate value accurately.
