Have you ever read an online review before purchasing a product? If you did, you are not alone! In fact, a vast majority of consumers read online reviews before making a purchase. According to a survey conducted by BrightLocal in 2023, 98% of consumers read online reviews for local businesses, and 91% of consumers read online reviews for non-local businesses (BrightLocal, 2023).

The strong effect of consumer reviews on purchasing behavior raises the question why consumers read online reviews and what they are specifically looking for. In order to answer this question, one has to first consider the purchasing process of a consumer. In a physical store, the consumer is able to pick up the product and thereby to evaluate its quality and performance. For example, a consumer wanting to buy a piece of clothing, e.g. a jacket, in a physical store could easily try it on and check if it fits properly (performance) and if the material feels premium (quality). Such an evaluation is impossible in an online shop.

To compensate for the missing possibilities to evaluate a product’s quality and performance in an online shop, consumers look for additional information on the internet. One source of additional product information are online consumer reviews. They are intended to provide additional information that is based on the experience of another consumer that already has bought the product. Therefore, consumer reviews are intended to reduce uncertainty before buying a product.

Studies have proven that there is a significant correlation between the star rating and the sales of a product. For example, a study conducted in 2016 analyzed the impact of the volume of consumer reviews on the conversion rate of users browsing a product page. The results show that having reviews can increase the conversion rate of a product by up to 270%, with the first five reviews having the most significant impact, and high-priced items benefiting more from reviews than low-priced items (Askalidis & Malthouse, 2016). However, it appears that a negative 1-star rating has a greater influence on the purchasing behavior than a positive 5-star rating (Chevalier & Mayzlin, 2006). This emphasizes the importance of online reviews and the need for businesses to monitor and respond to negative reviews.

Consumer reviews can be classified as a form of crowd evaluations and therefore also as a form of crowdsourcing. An (usually) anonymous group of consumers review products they have bought so that other people can benefit from their experiences. The motivation to write a review can be very diverse, ranging from the desire to share a positive experience to the intention to help others make informed purchasing decisions.

However, not all online reviews are reliable and objective. Over the past years, the phenomenon of fake reviews has significantly increased. Studies estimate that a staggering 16-33% of reviews are fake (Wu et al., 2020). In my next blog post, I will elaborate on why people write fake reviews and describe consumers’ awareness of fake reviews.

In conclusion, online consumer reviews are an important source of information for consumers and can have a significant impact on purchasing behavior. They provide additional product information that cannot be evaluated in an online shop and reduce uncertainty before buying a product. Therefore, businesses should encourage and monitor online reviews to improve customer satisfaction and increase sales.

References:

Askalidis, G., & Malthouse, E. C. (2016). The Value of Online Customer Reviews. Proceedings of the 10th ACM Conference on Recommender Systems, 155–158. https://doi.org/10.1145/2959100.2959181

BrightLocal. (2020). Local Consumer Review Survey 2020. Retrieved from https://www.brightlocal.com/research/local-consumer-review-survey/

Chevalier, J. A., & Mayzlin, D. (2006). The Effect of Word of Mouth on Sales: Online Book Reviews. Journal of Marketing Research, 43(3), 345–354. https://doi.org/10.1509/jmkr.43.3.345

Wu, Y., Ngai, E. W. T., Wu, P., & Wu, C. (2020). Fake online reviews: Literature review, synthesis, and directions for future research. Decision Support Systems, 132, 113280. https://doi.org/10.1016/j.dss.2020.113280