Knozen is an app that started as rating and review system for colleagues. Now you can rate everyone you know anonymously. Knozen asks you funny questions about someone’s personality but also about your own personality such as: “Denise is more likely to leave work early for a date – true or false”. On each profile 12 characteristics are shown with a rating scale from 1 to 10. The answers on the questions in the quiz influence the score on each characteristic. As a result, a personality chart will give you an idea of someone’s personality.
Tag Archives: Rating system
Electronic Word of Mouth and Amazon.com
Figure 1: ‘Understanding’ online star ratings
Amblee and Bui (2011) have researched the effect of electronic word of mouth (eWOM) on the sales of digital microproducts. They studied amazon.com ‘shorts’: short stories (e-books) that are made available for a set price of 49 cents. They classify these shorts as digital microproducts.
This article focusses on their study on de effect of social commerce on product reputation and sales (hypothesis 1). Amblee and Bui (2011) studied this effect from three different perspectives: Valence (how positive or negative a rating is), the presence of a rating versus no rating and volume (thus the amount of ratings). Interestingly, they do not find a significant correlation between valence of the rating and sales. Amblee and Bui (2011) suggest that this might be due to the generally positive ratings, and thus a low variance between positive and negative ratings. Second, they also find that the presence of a rating is a good predictor of higher sales, as compared to no ratings. Furthermore, they also find a significant correlation between the volume of ratings and the volume of sales.
In their discussion, Amblee and Bui (2011) propose a better scoring system which allows users to score the e-book on different dimensions such as content, writing style and so on. While this suggestion might lead to a bigger variance between ratings, I wonder if it would have a positive effect on sales in the end. Amblee and Bui (2011) point out that the majority of past research on valence suggests that valence is not a reliable predictor of sales. However, by including more ratings to fill in like Amblee and Bui (2011) suggest, you might achieve a negative effect: that customers are no longer willing to fill in the rating. And the importance of the presence of the rating, and moreover the volume is exactly what is found to be so important to spark sales by Amblee and Bui (2011).
Fast forward to 2015. Did Amazon.com change the rating system? I went to Amazon.com and I filtered on short stories and on kindle editions. This is what I found:
Figure 2: Average customer review of shorts on Amazon.com, 2015
Figure 3: Layout of customer reviews of shorts on Amazon.com, 2015.
This shows that the great majority of the ratings is still very high (roughly 84% of the ratings are 4 stars or more). However, it seems like Amazon has added some space for customers to motivate their rating. Furthermore customers can also identify reviews as helpful, and Amazon shows me the most helpful reviews first. By using this system, Amazon.com leaves it up to its customers if they want to motivate their rating (and spend more time rating a book) or not. What do you think, has the system improved? Do you think it will lead to more sales? Please comment below!
- Amblee, N. and Bui, T. (2011) ‘Harnessing the influence of social proof in online shopping: The effect of electronic word of mouth on sales of digital microproducts’, International Journal of Electronic Commerce, Vol. 16, No. 2, pages 91-113, DOI 10.2753
- Featured image: GTP Headlines, accessed 31-03-2015, http://news.gtp.gr/2014/11/25/amazon-com-launch-travel-service-enter-the-world-online-booking/
- Figure 1: quora.com, accessed 01-04-2015 http://qph.is.quoracdn.net/main-qimg-80cd8d435bc1eed5a48d8732857f5aa7?convert_to_webp=true
- Figure 2: Amazon.com, accessed 31-03-2015, http://www.amazon.com/s/ref=sr_nr_p_n_feature_browse-b_2?fst=as%3Aoff&rh=n%3A283155%2Cn%3A%211000%2Cn%3A17%2Cn%3A10300%2Cn%3A10307%2Cp_n_feature_browse-bin%3A618073011&bbn=10307&ie=UTF8&qid=1427828706&rnid=618072011
- Figure 3: Amazon.com, accessed 31-03-2015,http://www.amazon.com/When-Fall-Love-Blue-Series-ebook/product-reviews/B00HE1PEZO/ref=cm_cr_dp_see_all_summary?ie=UTF8&showViewpoints=1&sortBy=byRankDescending