We have all been there; browsing for too long on Tripadvisor.com or Amazon.com trying to find that one review that could be the decisive factor in buying (or not buying) that specific product. But what exactly is it that we are looking for? What makes one review more helpful than another? The article of Mudambi and Schuff (2010) tries to find the answers to these questions by reviewing almost 1600 reviews on Amazon.com throughout several products and product categories.
When browsing online, individuals are presented an increasing amount of customer reviews; these reviews have proven to increase buyers’ trust, aid customer decision making and increase product sales (Mudambi, Schuff & Zhang, 2014). In addition, customer reviews can attract potential visitors and can increase the amount spent on the website. Hence, retail sites with more helpful reviews hold greater potential to offer value to consumers, sellers as well as the platform hosting the customer reviews.
In order to increase the helpfulness of customer reviews, several websites such as Amazon.com and Yelp.nl ask the question “was this review helpful to you?” and list more helpful reviews more prominently on the product information page. Mudambi and Schuff (2010: 186) define a helpful review as a “peer-generated product evaluation that facilitates the consumer’s purchase decision process”.
The article distinguishes between two types of goods when looking for products online: search goods and experience goods. Search goods possess attributes that can be measured objectively, whereas the attributes of experience goods are not as easily objectively evaluated, but are rather dependent on taste. Examples of search goods are printers and cameras; examples of experience goods are CD’s and food products.
Past research showed conflicting findings as to whether extreme ratings (rating very negatively or very positively) are more helpful that moderate reviews; some argue that extreme ratings are more influential, whereas others argue that moderate reviews are more credible. Mudambi and Schuff (2010) argue that taste often plays a large role with experience goods as consumers are quite subjective when rating; hence, consumers would value moderate ratings of experience goods more, as they could represent a more objective assessment (H1).
Next, Mudambi and Schuff (2010 scrutinize the review depth of customer reviews. Since longer reviews often include more product details, and more details about the context it was used in, the authors hypothesize that review depth has a positive impact on the helpfulness of the review (H2). Nevertheless, the review-depth of a review might not be equally important for all products. Reviews for experience goods often include unrelated comments or comments so subjective that they are not interesting to the reader. For example, movie reviews often entail elaborate opinions on actors/actresses that are not important for the reader. On the other hand, reviews of search goods are often presented in a fact-based manner as attributes can be objectively measured. As a result, it is argued that review depth has a greater positive effect on the helpfulness of the review for search goods than for experience goods (H3).
By evaluating almost 1600 reviews (distributed over 6 products; 3 experience goods and 3 search goods) and excluding the ones that did not get any vote whether it was helpful or not, the researchers were able to confirm all three hypotheses. The article teaches us that there is no one-size-fits-all method as to what makes a reviewhelpful. Experience goods prove to be less helpful with extreme ratings, whereas search goods benefit from in-depth reviews.
Mudambi, S. & Schuff, D. (2010). What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com. MIS Quarterly, Vol 34 (1), pp 185-200.
Mudambi, S., Schuff, D. & Zhang, Z. (2014). Why Aren’t the Stars Aligned? An Analysis of Online Review Content and Star Ratings. IEEE Computer Science, 3139 -3147.