Marketing expert tracks online shoppers

November 28, 2011 By Dom Yanchunas

Online retailers have long wondered if trumpeting consumer-behavior statistics on their websites could hurt business. Qi Wang’s new findings should ease their fears, just in time for Cyber Monday.

Wang, an associate professor of marketing at Binghamton University, studied the effects of user comments and sales 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” data.

Observational behavior refers to a person’s tendency to adopt the same habits as his or her peers. “Households make decisions by following what they see their neighbors doing,” Wang says. “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.

“It’s good news for manufacturers who haven’t had a lot of people buy their product,” Wang says. “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.”

The findings were published in the Journal of Marketing Research.

Juanjuan Zhang, assistant professor of marketing at Massachusetts Institute of Technology, has cited Wang’s findings in her own research exploring the observational learning phenomenon. “This is a new, interesting and important result, which could be highly valuable to companies that want to manage the market consequences of word-of-mouth and observational learning,” Zhang says.

The research, Zhang says, “disentangles the effect of word-of-mouth and observational learning using a very clever natural experiment.”

Wang also identified a synergy between the two concepts. “What’s most surprising is the interactions of word-of-mouth and observational learning,” Wang says. “They 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.

“Negative word-of-mouth affects people more than positive word-of-mouth. This is not new,” Wang says. “With our study, we are the first to show the influences of observational learning. This is very important to companies thinking about what types of information can be posted on their websites. Our study gives them the evidence.”

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