Can online product reviews be more helpful? Examining characteristics of information content by product type

Many online retailers and other product-oriented websites allow people to post product reviews for use by shoppers. While research indicates that these reviews influence consumers' shopping attitudes and behaviors, questions remain about how consumers evaluate the product reviews themselves. With the current research, we introduce a new methodology for identifying the review factors that shoppers use to evaluate review helpfulness, and we integrate prior literature to provide a framework that explains how these factors reflect readers' general concerns about the diagnosticity (uncertainty and equivocality) and credibility (trust and expertise) of electronic word-of-mouth. Based on this framework, we offer predictions about how the relative importance of diagnosticity and credibility should vary systematically across search and experience product types. By analyzing secondary data consisting of over 8000 helpfulness ratings from product reviews posted by shoppers on Amazon.com, we find that, while review content affects helpfulness in complex ways, these effects are well explained by the proposed framework. Interestingly, the data suggest that review writers who explicitly attempt to enhance review diagnosticity or credibility are often ineffective or systematically unhelpful. Our findings have implications for both IS developers and retailers for designing online decision support systems to optimize communication practices and better manage consumer-generated content and interactions among consumers.