The Impact of Timing and Product Portfolio of Recommendation Systems on Customer Satisfaction


It’s safe to say we have all bought something online. The web has become an important platform over the years for people to obtain information and shop. Why? It’s easy, you can shop whenever, wherever you want and all the information you need is in the product description. Because of rise of e-commerce, personalised recommendation was created to recommend products that meet consumers’ preferences, reduce cognitive efforts, improve user experience, and help purchasing decisions while prompting sales. We’ve all seen companies such as Amazon.com, Bol.com, and Alibaba.com, and even online supermarkets use these recommendation tools. By looking at their consumers browsing history, purchase history and comment history these companies can determine consumer behavioural preferences and recommend consumers the products that they may interest.

The paper written by Yan, Q. et al., looks at the decision-making process of consumers and analyses the mechanisms involved in consumers’ acceptance of these recommendations.  What makes the paper unique is its distinctive assessment of the personalised recommendation system by analysing it from two angles; the recommendation timing and product portfolio. Past papers looked at accuracy and efficiency of recommendation algorithms and their ways to reduce perceived risks, however according to Yan Q.et al, a good recommendation system does not only focus on accuracy but also on customer satisfaction which isn’t determined by accuracy. What does determine customer satisfaction is time.

How can time increase customer satisfaction? By recommending products at the right time with the right diversity. According to the preference inconsistency theory, there is a discrepancy of consideration sets in the first and second stage of the decision-making process. In the first stage, when users are browsing, for example for a new pair of jeans, consumers want a lot of choices while in the second stage, before users click submit for purchase, the focus is to minimise the difficulty in decision making and making the right decisions. Too much product choices will cause users cognitive overload, and lower consumer satisfaction. Hence, consumer preferences for recommended products vary in time and the recommended product portfolio and recommendation timing should be consistent with the consumers’ preferences, or it can cause a burden on consumers and decrease consumers’ satisfaction of the system!

What also affects consumer satisfaction is the difference in the type of products recommended in each stage. When consumers browse e-commerce sites, they tend to focus on their own needs and objectives and conduct search on the initial target product and products in the same category. Because consumers tend to focus more on similar products, similar products recommended by the system will be recommended. However, in the second stage, consumers have developed certain awareness and made choices regarding their target product, hence their focus easily moves to products complementary to the target product and consider purchasing other products that are not the target product!

Also, there is a difference in the acceptance of personalised recommendation between practical and hedonic products. Think about the difference of buying dental floss or buying a new television.  The motives for practical products include meeting basic needs and convenience while the motives for hedonic products is based by perceived fun and entertainment. Hence, consumers are likely to have different cognitive and emotional reactions when purchasing these different products. The research shows that consumers who have hedonic products in their consideration set are more susceptible to the systems product recommendations, compared to practical products!

The strength of the research is its further in-depth analysis of the various factors influencing recommendations on consumers. The study takes a different approach compared to past research papers and can be a theoretical basis for e-commerce companies in understanding consumers focus and behaviours at the different stages of the shopping journey. The meticulous understanding can be used to improve customer satisfaction by reducing the cognitive journey and ultimately increase sales! Recommendation systems based on accurate timing and product portfolio are a win-win situation for both the consumer and the retailer!

References:

Tsekouras, D. (2017). Session 2: Personalization & Product Recommendations.

What every marketer should know about hedonic shoppers. (2017). [online] The Rooster Blog. Available at: http://blog.getrooster.com/every-marketer-know-hedonic-shoppers/ [Accessed 10 Feb. 2017].

Yan, Q., Zhang, L., Li, Y., Wu, S., Sun, T., Wang, L. and Chen, H. (2016). Effects of product portfolios and recommendation timing in the efficiency of personalized recommendation. Journal of Consumer Behaviour, 15(6), pp.516-526.

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