Have you ever wondered if your considerations during online shopping were really selected by yourself? Prior to my recent studies I was certain that I only bought what I needed. Now I reckon that decisions during online shopping are more or less influenced by recommender systems (RSs). In this blog, I will present my findings on how RSs influences our decision making.
At this point, some of you may ask what RSs are. Recommender systems are software tools and techniques that suggest you what to buy based on your and other people’s data. More simply, RSs are just like your friends, with a great understanding of you, who are eager to inform you of any products or services that might interest you.
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Recommender Systems make us discover more options
As one informant in my study said, even if I have something specific in mind, I will still spend more time searching on things because more options are presented [on e-commerce websites]. More interestingly, options offered by RSs can be of better value compared to your initial consideration, as one of the informants explained:
RSs help me to have taste of new brands or new products that are on the market but haven’t gotten to me.
Indeed, many informants reported that using RSs changes their perception about price, in the sense that cheap products do not always have inferior quality.
Moreover, RSs also helps in discovering complementary goods, especially when shopping for clothing online. As one female respondent said:
If I buy a bag, they will recommend the products that usually goes with it, e.g., shoes, trousers or a dress.
This ability of RSs is especially useful for those with limited product knowledge.
Recommender Systems make us consider more options…, don’t they?
Although it seems logical that RSs will make us consider more options, RSs could actually shorten our consideration process because they give you all necessary information and enable you to filter information quickly. This was explained clearly by one informant:
Before, in case I want to buy something, I have to search for products on Google, search for similar things to it, compare the price and, read reviews here and there. But with RSs, I don’t have to do the part of searching it. So, they just recommend me right away. I just need to go to the review pages saying, e.g. “This product is better than that product”. So, it helps me save a lot of time in researching.
However, if you don’t trust the systems, RSs will lengthen your consideration process because you need to double-check information provided by the system.
When is the use of Recommender Systems most useful?
In the end, the effects RSs have on our decision making are relative. This became evident when I analysed the usefulness of RS systems, as the responses I received showed great variation. The most frequently cited reason for using the RS system is a lack of knowledge and experience with the product of interest. For example, one person with little knowledge of electronics, considered recommendations for electronics very useful when shopping online.
Secondly, it is mentioned that the use of RSs is helpful when shopping for special events, such as Valentine’s Day. In my cases, I usually type “Valentine’s Day presents for family” in the search bar and go with the recommendations. Additionally, some participants in my study stated that they find the use of RSs most helpful when they can’t recall product names. What an insightful response, don’t you think? Last but not least, RSs could become useful when you don’t know what to buy. Even though this may sound ridiculous, next time when you have free time, try to check out random recommendations on your favourite e-commerce website. You never know what you might discover.
Read more about the study here.
Phuong Nguyen
Phuong is a first year PhD Student with her area of expertise in recommender systems as service technology and consumer behaviours. She is intrigued by research topics such as service innovation, consumer behaviours, strategic marketing and Artificial Intelligence. At the moment, she’s conducting research on AI-human collaborations.