Longer online reviews are not necessarily better
By Lior Fink, Liron Rosenfeld, Gilad Ravid
- Longer reviews are less likely to be overlooked because they are “visually more salient” 
- Longer reviews contain more information, which leads to less product-related uncertainty which leads to more consumer confidence  
The time of the data collection was December 2013 and the apps selected from Google Play were listed in 26 different categories and the ones from Amazon Appstore in 28, yielding a total of 33,119 and 95,683 apps respectively. To be consistent with previous research, the authors also removed the apps that did not have reviews at all, yielding a total of 7864 Google Play free apps, 6,206 Google Play paid apps, 6,158 Amazon Appstore free apps, and 2,734 Amazon Appstore paid apps.
These apps were then divided into intervals according to the amount of downloads, which then it’d later stand for “demand”.
Besides demand (which would be the dependent variable), the other variables observed in the different types of apps where:
- Days since last update
- App size
- Star Rating
- Number of reviews
- Average review length (in words)
But the only relationship we care about here is between review length and “demand”. And this is what we’ve got.
As we can observe from the figure above, professor Fink and his colleagues identified a sweet spot for most categories of 100 to 150 words when it comes to the optimal average of words in a review.
This fitted curves of predicted demand as a function of review length shows means as ‘tics’ and ‘quartile ranges as dots.
The authors believe that maximum demand correspond to the optimum cognitive load, however “optimum” load shall only apply from the companies point of view [see 4th weakness below].
The authors came up to the previous fitted curve by equating quadratic formulas to 0 in the following way:
Let’s now wrap up the paper with its weaknesses, strengths, and implications for managers and researchers, let’d do a TL;DR:
Strengths of the paper
- Explores a different setting with very high managerial implications
- Kudos for challenging dogmas
- More relevant scenario than previous research as smartphones overtake computers in e-commerce source of traffic
Weakness of the paper
- Longer reviews might be rants
- Popular apps do not necessarily require the users to know more about the app by reading reviews.
For instance may instagram users decide to download the app rather than because of app reviews but because of peer pressure/social acceptance.
- It won’t have a large impact on research done in computer settings
- The variables tested are review length and downloads “demand”, not exactly “review usefulness”.
Usefulness in terms of explicitly stated by a review reader when it comes to helping him/her make a sound decision.
- Since good reviews may also advise you to not buy a bad product, in this case clearing up product uncertainty does not logically seem to lead to necessarily more sales, something most authors do not take into account, including these.
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