The Effect of Need for Uniqueness on Word of Mouth

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Cheema, Amar and Kaikati, Andrew M., (April 24, 2009). The Effect of Need for Uniqueness on Word of Mouth. Journal of Marketing Research 47 (3). 553-563.

Reviewed by Jason Dong, August 2010

Executive Summary

The authors set out to test a set of hypotheses on what impact the need for customers to be unique has on their likelihood to provide Word Of Mouth (WOM) recommendations for products. They list the various benefits of WOM on purchase decisions and why customers engage in WOM (e.g. customers use WOM to justify purchase decisions, psychological & social benefits). They also note the costs of WOM which include the risk of communicating inappropriate advice and opportunity cost (e.g. the likelihood of WOM is lower when the supply for the product in question is limited). The article then segues into consumers’ need for uniqueness on varying levels, the factors that affect uniqueness like individual characteristics & traits, and intended & unintended consequences of the actions of "high uniqueness” customers. This flows nicely into the introduction of the hypotheses the authors set out to test and assumptions they have on what results they expect to see. The hypotheses are as follows:

  1. Higher need for uniqueness decreases willingness to provide positive WOM to a greater extent for public versus privately consumed discretionary products owned by consumers
  2. Within the domain of public products, the high need for uniqueness decreases a consumer’s willingness to provide positive WOM for owned products but not products that he/she does not plan to buy
  3. Within the domain of public products, the high need for uniqueness decreases a consumer’s willingness to provide positive WOM but does not decrease willingness to provide WOM that only contains product details

The authors then conducted 4 studies and examined the process in two other ones to test these hypotheses including analysis of a study involving WOM agencies. The majority of the studies were 2x2 factorial design experiments designed to test and observe interactions between variables such as public vs. privately consumed products and high vs. low uniqueness need.

Findings coming out of the studies include high-uniqueness customers being less willing to provide positive WOM for publically consumed products and high-uniqueness customers less willing to provide positive recommendations for products to others but willing to share product details.

Why you should care

The most immediate application this particular research has on the digital space is its applicability to websites that facilitate public and private feedback such as the writing of product reviews, providing product ratings, and forums. This dovetails into the trend lately where brands are attempting to increase engagement and conversation with its customers.

From an analytics and optimization perspective, this research presents interesting web and sales analysis opportunities. Brands with websites that currently have integrated user feedback channels can carry out deep dive analyses on product or category performance. One such example may be fallout and conversion analyses on various products based on volume of positive reviews or ratings a product has received and who left them. Bear in mind, the focus of this research was on the willingness of customers to provide WOM rather than the effectiveness of WOM; correlating this data with categorized publically vs. privately consumable products within a category or product line; and even categorization of a company’s products based on whether they are considered highly-unique vs. low-uniqueness. The research that was conducted can provide at least a reference for what kind of result one could expect for each product or category.

Based on the findings of this exercise, companies can then carry out simple tests like offering an incentive in exchange for feedback to encourage high-uniqueness customers to leave positive WOM for specific products. The success rate is higher if it is classified as a privately consumable product according to the research. Then, monitor whether the volume of reviews or ratings for a given product goes up versus a control. The overall goal is to incrementally increase the participation rate of customers by enticing them to leave very valuable customer feedback on a company’s products. Especially those who characteristically are less inclined to do so out of fear that others will buy the product and decrease its exclusivity.

This article is relevant to analysts who as part of their overall measurement responsibilities include user-generated content or voice of customer as part of their scope. The research presented in this article may provide some insight into the type of personas who leave feedback on certain products versus those that don’t and why.

A single copy of the full journal reviewed above is available to members of the Web Analytics Association. To request a copy, email Shannon Taylor.