To Learn from Your Own or Others’ Experiences?
To Learn from Your Own or Others’ Experiences?
The influence of online ratings and free samples on users’ purchase decision of experience goods.
Have you ever felt overwhelmed by too many choices when shopping online? In such situations, you may need help to give you clues about which choice is the best fit for you. It might be even more severe for experience goods, products whose information is difficult to obtain before usage. For example, information goods, including software, movies, and music, are typical experience goods. Consumers find it even harder to make purchase decisions about experience goods. Various market tools might act as information channels to reveal product information to potential shoppers before purchasing, among which online ratings and free samples are the two most popular ones.
—Have you ever felt overwhelmed by too many choices when shopping online?—
Interestingly, we observe that online ratings and free samples are often provided to shoppers simultaneously. An intriguing question arises: When shoppers have access to both online ratings and free samples, which one would be their first choice? In other words, does the effect of one information channel dominate the other? Further, do the two information channels have different effects across various product categories?
The essential difference between the two information channels involves how they reveal information to users. By reading online ratings, consumers obtain product information from other users’ usage experiences, and therefore it is a social learning process. In contrast, consumers learn product information based on their own usage experiences when using free samples, and so this is an individual learning process. Based on a dataset drawn from CNET.com, a leading software rating and downloading website, we conducted a series of research to investigate the above issue. Our research leads to several interesting findings.
As for the individual learning channel, we find that user ratings, but not expert ratings, significantly influence consumers’ adoption behavior. This finding confirms that social learning is an effective information channel. However, the rating source also plays an important role. Besides the online ratings posed by previous users, some review websites might recruit experts to experience products and publish their ratings. Although experts may be more knowledgeable, they are also perceived as less trustworthy (as sellers might intentionally control expert reviewers). As a result, when both user and expert ratings are available, only the former can effectively enhance consumers’ willingness to purchase the software. This result is in our recently published JIS paper, entitled “Do online reviews have different effects on consumers’ sampling behaviour across product types? Evidence from the software industry.”
More importantly, our findings provide insight into how customers process information before purchasing. When both individual learning and social learning information channels exist, they process information as follows. Since online ratings can be directly accessed from review websites, they can quickly capture consumers’ attention. Therefore, consumers first narrow down their choices by reading online ratings. Then, for software with high user ratings, consumer willingness to purchase is enhanced, and customers then have an incentive to further learn product information before purchasing. As a result, they will turn to free samples to further learn product information. This result can be found in our IP&M paper, entitled “The interaction effects of online reviews and free samples on consumers’ downloads: An empirical analysis.”
As for the individual learning channel, we can observe three different designs of software free samples which come with different restrictions: namely, function-limited, time-limited, and unfriendly obstacles. Intuitively, these three types of samples may lead to varying levels of incentives for consumers to try the software. However, we find that various sample restrictions lead to the same level of willingness to adopt these samples when we consider all categories of software as a whole.
However, the effects of social learning and individual learning information channels might be different for various software categories. Software can be categorized as utilitarian or hedonic according to consumers’ usage purpose. Typical utilitarian software includes developer tools, security software, and browsers, while games, music players, and wallpaper software are deemed hedonic software. Utilitarian goods are usually considered as necessary, functional, practical, and instrumental, while hedonic items are related to thrilling, delightful, spontaneous, and sensorial consumption experiences. Thus, consumers’ intention to purchase the two types of software might be driven by different incentives. It is, therefore, reasonable to conjecture that the individual and social learning information channels may have different influences on consumers’ adoption of utilitarian and hedonic software. If this is true, software firms will need to design different information channels for different software categories. The results confirm our conjecture. More specifically, we find that the influence of user ratings is significant for utilitarian software but not for hedonic software. Further, when using utilitarian software, consumers prefer time-limited free samples, while users of hedonic software are indifferent to different types of restrictions. A comprehensive result is in our I&M paper “What results in more sample downloads? The role of social learning and individual learning with software category.”
Our research provides several practical implications. First, software consumers rely more on user ratings than expert attitudes. Therefore, we suggest software firms avoid posting online expert reviews only. Instead, it is crucial to provide consumers with online user reviews to facilitate consumers’ learning from previous users. In addition, their effects might depend on the categories of the software. As a result, utilitarian software firms should put more effort into improving user ratings. For example, firms may use gamification or reward mechanisms to encourage satisfied users to rate. However, this strategy is not effective for hedonic software firms. Further, according to our findings, utilitarian software firms should consider time-limited free samples as their primary strategy. In contrast, for hedonic software firms, each type of free sample makes no difference.
Cite this article in APA as: Li, S. (2022, February 2). To learn from your own or others’ experiences? Information Matters, Vol. 2, Issue 2. https://informationmatters.org/2022/02/to-learn-from-your-own-or-others-experiences/