Journal of Interactive Marketing

With the availability of online creative tools, consumers create ad-like communications on their own or in response to company contests. These consumer-generated ads (CGA) are like word-of-mouth (WOM) in that they are consumer-to-consumer communications, yet they have the look and feel of traditional advertising. We examine consumer responses to both contest and unsolicited CGA and company ads using data gathered from consumers via netnography and depth interviews. Content analysis is used to compare the three ad types and reveals that the contest rules frame CGA so that they resemble company ads while unsolicited CGA differ from both ad types. Findings show that consumers respond to both types of CGA by engaging with the ad rather than the brand, much like an ad critic, while company ads elicit brand associations. Unsolicited CGA are seen as authentic, but not credible, while contest ads are seen as credible, but not authentic, revealing a boundary condition to the conventional view that authenticity leads to credibility.

Web 2.0 has empowered consumers to voice complaints with reduced costs (physical and psychological), and to share these with a multitude of other consumers on the Internet. As a public phenomenon, online complaints have a negative impact on consumers’ evaluations of brands that are under attack in online complaints. By means of an experiment, we study the most effective means for companies to counter complaints as expressed in negative electronic word of mouth (NWOM). The results show that negative brand evaluations engendered by NWOM can be attenuated by webcare interventions dependent on type of strategy (proactive vs. reactive) and platform used (consumer-generated vs. brand-generated blog). This effect appeared to be mediated by conversational human voice. The findings are discussed in the light of practical implications for online complaint management.

In search engine marketing, such as on Google, advertisements’ ranking and prices paid per click result from generalized, second-price, sealed bid auctions that weight the submitted bids for each keyword by the quality of an advertisement. Conventional wisdom suggests that advertisers can only benefit from improving their advertisement's quality. With an empirical study, this article shows that quality improvements have complex effects whose returns are actually unclear: 5% of all quality improvements to an advertisement lead to higher prices (measured by price per click) per keyword, 100% to a higher number of clicks, 53% to higher costs for search engine marketing, and 37% to lower profits. Quality improvements lead to higher weighted bids, which only lower prices if they do not improve the ranking of the advertisement. Otherwise, better ranks likely lead to higher prices. A decomposition method can disentangle these effects and explain their effects on search engine marketing costs and profits. Finally, the results indicate that advertisers benefit if they lower their bids after improvements to advertising quality.

Online advertising has short- and long-term effects. Little is known, however, about which online advertising channel works best to address particular customer groups when short- and long-term effects, are taken into account. We look at the sales effect of search engine marketing (SEM), banner advertising, price comparison advertising (PCA) and coupon/loyalty advertising (CLA) on new and existing customers. Our analysis, which uses a sample of 2.8 million purchases, shows that SEM has the longest effect, followed by banners, CLA, and PCA. We find that CLA works better for existing customers than for new customers, whereas PCA works better to attract new customers.

The Internet has significantly impacted the information search behavior of consumers. Many consumers regularly consult Internet sources for information on product categories, brands, manufacturers, and retailers, particularly when making a purchase decision about major durable goods. Automobiles are one example of such goods. The Internet has become a major source for information on automobile brands, attributes, and dealers. While much research has been done on the impact of the Internet on automobile information search behavior and search costs, there is limited work on the relationship between Internet use and the ultimate automobile choice. This type of relationship may have interesting managerial implications for both manufacturers of automobiles and firms that provide information on automobiles. This paper attempts to address this gap. It examines whether Internet use is associated with different choice patterns for automobiles. Using discrete choice analysis on automobile choice data, we explore whether there will be differences in the salience of specific information types for online versus offline consumers. We find that Internet users rely more on ratings while non-Internet users rely more on recommendations when making automobile choices. Our findings have several useful managerial implications for information provision, both online and offline.

Average effects of influence strategies on consumers’ attitudes and behaviors have been studied extensively. Less is known about the relative size of individual differences in these effects, despite recognition of their importance in social psychology. Two experiments use repeated exposures to influence strategies to identify the effects of each social influence strategy for individual participants. Study 1 provides evidence of large variation in the effects of influence strategies, such that for many participants the estimated effect of using an influence strategy is negative, even though the effect of that strategy is significantly positive on average. Study 2 replicates these findings over three sessions, each a week apart. The observed variation in responses to influence strategies cannot be attributed to transient intra-individual variation (e.g., strategy × mood interactions). Meta-judgmental measures of personality constructs (e.g., need for cognition) explain only a small portion of the observed variance, suggesting the importance of directly modeling heterogeneity in responses to influence attempts. These results are important for interactive marketeers since they indicate that different influence strategies substantially differ in their effects on individual consumers and should thus be adapted to individuals.