Just in time for Cyber Monday. Online retailers have long wondered if trumpeting consumer-behavior statistics on their websites could hurt business. New findings from Qi Wang, an associate professor of marketing at Binghamton University, should ease their fears.
Wang studied the effects of user comments and sales statistics that accompany products offered on e-commerce sites. While the impact of positive and negative feedback has been well understood, much less was known about so-called “observational behavior” – aka a person’s tendency to adopt the same habits as his or her peers. Wang’s findings were published in the Journal of Marketing Research.
According to Wang, households make decisions by following what they see their neighbors doing. People learn from their peers what to buy. For online marketers, word-of-mouth recommendations are displayed in the form of customer reviews. If the site also reveals statistics on how many users purchased the product, the shopper also can be influenced by observational behavior.
Wang analyzed data on 90 brands of digital cameras from Amazon.com, which includes a section disclosing the percentage of people who bought the product after viewing it. She and her colleagues found that positive observational behavior data boosted sales, while negative observations had little influence.
The results dispel a myth in e-commerce that consumers are likely to be discouraged if they see a low percentage of peers following through with the purchase. Wang sees it as good news for manufacturers who haven’t had a lot of people buy their product. If it’s a niche market just targeting a small group of consumers, they don’t have to worry because there is no harm in releasing this type of information.
Wang also identified a synergy between word-of-mouth and observational learning and found, much to her surprise, that the interactions strengthen each other. Previous market research indicated that consumers often dismiss highly positive product feedback, realizing that a person writing favorable comments may be biased. Highly critical product feedback is viewed as more reliable. For observational learning, the opposite is true.