TAMPA – It’s a conundrum online consumers face most of the time: A product’s “top” online reviews show a slew of conflicting star ratings. Some reviewers give it four or five stars. Other reviewers blast it with one star.
How does that clash influence when consumers buy?
A new study from researchers at the University of South Florida examines how consumers react when faced with a collection of top reviews that conflict with each other — when a product’s top reviews contain both positive and negative opinions from different reviewers, sometimes even directly contradicting each other on certain product attributes.
The study, authored by four USF Muma College of Business researchers and published this month in Information Systems Research, found:
- Inconsistency among top online reviews causes consumers to defer purchases so they can obtain more information about the product, such as additional reviews.
- The likelihood of buyers reading more reviews increased by 20% when they were faced with conflicting reviews that lacked contextual details behind reviewers’ opinions.
“Consumers read online reviews to decide whether to buy a product. There is extensive research on what makes a single review useful or credible, but there is very limited understanding of how a set of conflicting reviews influence purchase decisions,” said Dezhi (Denny) Yin, an associate professor in the School of Information Systems and Management at the USF Muma College of Business.
The article “Decide Now or Later: Making Sense of Incoherence Across Online Reviews,” was published in July in Information Systems Research, a premier journal included among the top 24 leading business journals by the University of Texas at Dallas.
The findings are based on data collected at USF between 2019 and 2021. Researchers conducted two laboratory experiments where they asked more than 1,000 individuals to read a few top reviews of a digital camera being sold on Amazon.com. Afterward, participants were asked to decide if they were ready to make the buy-or-not-buy decision or if they wanted to wait and seek more information.
Yin said online review platforms could use the study’s conclusions as a guide on how to select which top reviews to display and the number of reviews to highlight. Furthermore, review platforms should analyze the interrelationships among top reviews and their context using text mining techniques to predict the likelihood and the extent consumers will seek and read more reviews.
For example, websites such as Amazon.com typically highlight the top three to six most helpful online product reviews. But if the top three reviews are contradictory and do not offer detailed contextual information, it might be useful to show more reviews because consumers are 20% more likely to defer buying decisions until they seek and read additional reviews.
Such design considerations are critical because existing research shows that the set of reviews consumers are exposed to and end up reading can easily sway consumers’ ultimate decisions. As a result, companies should not limit their attention to only those top reviews, but expand their focus to more reviews, such as the most recent reviews consumers may consult next, Yin said.
In addition, the study shows the value of adding contextual information to reviews and could help reviewers write more helpful reviews, he said.