The Effect of Word of Mouth on Sales: Online Book Reviews

We examine the effect of consumer reviews on relative sales of books on Amazon.com and BarnesandNoble.com. We find that 1) reviews are overwhelmingly positive at both sites, but there are more reviews and longer reviews at Amazon.com, 2) an improvement in a book's reviews leads to an increase in relative sales at that site, and 3) the impact of 1-star reviews is greater than the impact of 5-star reviews. The results suggest that new forms of customer communication on the Internet have an important impact on customer behavior.

Promotional Reviews: An Empirical Investigation of Online Review Manipulation

Firms\u27 incentives to manufacture biased user reviews impede review usefulness. We examine the differences in reviews for a given hotel between two sites: Expedia.com (only a customer can post a review) and TripAdvisor.com (anyone can post). We argue that the net gains from promotional reviewing are highest for independent hotels with single-unit owners and lowest for branded chain hotels with multi-unit owners. We demonstrate that the hotel neighbors of hotels with a high incentive to fake have more negative reviews on TripAdvisor relative to Expedia; hotels with a high incentive to fake have more positive reviews on TripAdvisor relative to Expedia

Word of mouth and marketing : influencing and learning from consumer conversations

Thesis (Ph.D.)--Massachusetts Institute of Technology, Sloan School of Management, 2002.Includes bibliographical references.This thesis contains three separate essays that deal with word of mouth. In the first essay, "Promotional Chat on the Internet," we analyze the firms' incentives to anonymously supply positive reviews of products in chat rooms and other recommendation sites. This, in turn, lowers the credibility of word of mouth transmitted online. We develop a game theoretic model where an incumbent and an entrant that are differentiated in quality compete for the same online market segment. The consumers are uncertain about the entrant's quality, whereas the firms know the value of their products. The consumers hear messages online that make them aware of the existence of the entrant as well as help them decide which product is superior. We find a unique equilibrium where online word of mouth is informative despite the promotional chat activity by competing firms. In this equilibrium, we find that firms spend more resources chatting up inferior products. We also find that promotional chat may be actually more beneficial to consumers than a system with no promotional chat. In the second essay, "Using Online Conversations to Measure Word of Mouth Communication," we test a long-held belief that word of mouth recommendations have a tremendous influence on the sales of new products. So far, there has been little empirical evidence to support this belief since, before the advent of the Internet, word of mouth recommendations were exchanged in private conversations that left no documentary evidence. The Internet provides a window into some of these private conversations and thus a means of measuring word of mouth activity.(cont.) We pose the following pragmatic question: can we use these data to measure word-of-mouth and predict future product sales? We develop and test a model that predicts which metrics of online discussion activity should be correlated with long-run performance. Our empirical findings demonstrate that certain measures of online word-of-mouth are predictive of sales though their predictive power varies significantly over the show's lifetime. Finally, in the third essay, "The Influence of Social Networks on the Effectiveness of Promotional Strategies," we examine the role of social network in word of mouth. The defining characteristic of "buzz" strategies is that the sellers approach the consumers directly, either in online chat rooms or in physical locations such as cafes or nightclubs. The goals of such strategies are twofold: to turn the approached consumer into a buyer and a missionary. The basic characteristic of buzz is that its diffusion is dependent on one's neighbors in the network in contrast to advertising, which allows the firm to communicate with consumers independently of their neighbors. We examine the network's moderating effect on the payoff from firm's investment to promote buzz. In addition, we compare the effectiveness of buzz promotion versus mass advertising as stand-alone marketing instruments and also analyze an advertising campaign that consists of both instruments.by Dina Mayzlin.Ph.D

Promotional chat on the Internet

C hat rooms, recommendation sites, and customer review sections allow consumers to overcome geographic boundaries and to communicate based on mutual interests. However, marketers also have incentives to supply promotional chat or reviews in order to influence the consumers' evaluation of their products. Moreover, firms can disguise their promotion as consumer recommendations due to the anonymity afforded by online communities. We explore this new setting where advertising and word of mouth become perfect substitutes because they appear indistinguishable to the consumer. Specifically, we investigate here whether word of mouth remains credible and whether firms choose to devote more resources promoting their inferior or superior products. We develop a game theoretic model in which two products are differentiated in their value to the consumer. Unlike the firms, the consumers are uncertain about the products' quality. The consumers read messages online that help them decide on the identity of the superior product. We find a unique equilibrium where online word of mouth is persuasive despite the promotional chat activity by competing firms. In this equilibrium, firms spend more resources promoting inferior products, in striking contrast to existing advertising literature. In addition, we discuss consumer welfare implications and how other marketing strategies might interact with promotional chat

Se servir des conversations en ligne pour étudier le bouche-à-oreille

International audienceLes managers s'intéressent beaucoup au phénomène du bouche-à-oreille car ils pensent que le succès d'un produit est lié au bouche-à-oreille qu'il génère. Cependant, l'étude de ce phénomène se heurte à au moins trois obstacles. Tout d'abord, comment recueillir les données ? Les informations étant échangées dans un cadre privé, l'observation directe est habituellement difficile à réaliser. Deuxièmement, quel aspect de ces conversations faut-il mesurer ? Le troisième obstacle est lié au caractère non exogène du bouche-à-oreille. La prévision des ventes futures à partir du bouche-à-oreille est un procédé très utile à l'entreprise. Cela dit, il faut également prendre en compte le fait que le bouche-à-oreille est un effet des ventes passées. Notre premier objectif est de lever ces obstacles. Notre contexte d'étude concerne de nouvelles séries télévisées diffusées entre 1999 et 2000. La source des conversations interpersonnelles est le site Usenet, regroupant des milliers de forums de discussion à propos de sujets divers. Nous estimons que les conversations en ligne représentent un moyen facile et peu coûteux pour mesurer le phénomène de bouche-à-oreille. Nous montrons qu'une mesure de dispersion des conversations au sein des communautés virtuelles est un bon facteur explicatif dans le cadre d'une modélisation dynamique des audiences télévisées

The effect of word of mouth on sales: Online book reviews

* This is a preliminary draft. Please do not quote without the authors ’ permission. W

Using Online Conversations to Study Word of Mouth Communication

Managers are very interested in word-of-mouth communication because it can have a tremendous impact on a product's sales. However, there are at least three significant challenges associated with measuring word of mouth. It is our primary objective in this paper to address these challenges. First and foremost, how does one even gather the data? Since the information is exchanged in private conversations, direct observation is (or at least has traditionally been) quite difficult. Second, even if one could observe the conversations, what aspect of them should one measure? The third challenge comes from the fact that word of mouth is not exogenous. While the mapping from word of mouth to future sales is of great interest to the firm, we must also recognize that word of mouth is at the same time an outcome of past sales. Our core result is that on-line conversations may offer an easy and cost-effective opportunity to measure word-of-mouth. However, simply counting on-line conversations may not be informative. On the other hand, measuring the "dispersion" of these conversations across communities is. Specifically, we show that a measure of dispersion has explanatory power in a dynamic model of sales, while pure counts do not. As a context for our study, we have chosen new TV shows during the 1999/2000 seasons. Our source of word-of-mouth conversations is Usenet, a collection of thousands of newsgroups with very diverse topics.