Seeded marketing campaigns (SMCs) involve firms sending product samples to selected customers and encouraging them to spread word of mouth (WOM). Prior research has examined certain aspects of this increasingly popular form of marketing communication, such as seeding strategies and their immediate efficacy. Building on prior research, this study investigates the effects of SMCs that extend beyond the generation of WOM for a campaign's focal product by considering how seeding can affect WOM spillover effects at the brand and category levels. The authors introduce a framework of SMC-related spillover effects, and then empirically estimate these with a unique dataset covering 390 SMCs for products from 192 different cosmetics brands.Multiple spillover effects are found, suggesting that while SMCs can indeed be used primarily to stimulate WOM for a focal product, marketers must also account for brand-and category-level WOM spillover effects. Specifically, product seeding increases conversations about that product among non-seed consumers, and, interestingly, decreases WOM about other products from the same brand and about competitors' products in the same category as the focal product. These findings indicate that marketers can use SMCs to focus online WOM on a particular product by drawing consumers away from talking about other related, but off-topic, products.
The global importance of online advertising calls for a detailed understanding of consumer-specific responses to online ad repetitions. A key concern for advertisers is not only whether some consumers display degrees of “wearout” but also whether they can surpass a point at which additional exposures have a negative marginal effect: “weariness.” The authors examine a large-scale advertising campaign aimed at driving viewers to a target website, which comprises more than 12,000 users across over 400 websites. These data are analyzed using a flexible discrete mixture specification that accommodates different response shapes over ad stock and timing and parcels ad viewers into response classes based on their internet usage metrics. The resulting classes display varying degrees of wearout, with one subgroup, accounting for about 24% of the sample, evincing weariness. The model also estimates differential publisher effectiveness, with the most effective publisher being nine times more effective than the one 26 places down. The authors demonstrate that the finding of weariness is robust to all the model’s main components, with one key exception: heterogeneity in users’ ad response. Analysis further suggests that an appropriate “profiling and capping” strategy can improve ad deployment by as much as 15% overall for these data.
Marketers are adopting increasingly sophisticated ways to engage with customers throughout their journeys. We extend prior perspectives on the customer journey by introducing the role of digital signals that consumers emit throughout their activities. We argue that the ability to detect and act on consumer digital signals is a source of competitive advantage for firms. Technology enables firms to collect, interpret, and act on these signals to better manage the customer journey. While some consumers’ desire for privacy can restrict the opportunities technology provides marketers, other consumers’ desire for personalization can encourage the use of technology to inform marketing efforts. We posit that this difference in consumers’ willingness to emit observable signals may hinge on the strength of their relationship with the firm. We next discuss factors that may shift consumer preferences and consequently affect the technology-enabled opportunities available to firms. We conclude with a research agenda that focuses on consumers, firms, and regulators.
Seeded marketing campaigns (SMCs) involve firms sending product samples to selected customers and encouraging them to spread word of mouth (WOM). Prior research has examined certain aspects of this increasingly popular form of marketing communication, such as seeding strategies and their immediate efficacy. Building on prior research, this study investigates the effects of SMCs that extend beyond the generation of WOM for a campaign's focal product by considering how seeding can affect WOM spillover effects at the brand and category levels. The authors introduce a framework of SMC-related spillover effects, and then empirically estimate these with a unique dataset covering 390 SMCs for products from 192 different cosmetics brands. Multiple spillover effects are found, suggesting that while SMCs can indeed be used primarily to stimulate WOM for a focal product, marketers must also account for brand-and category-level WOM spillover effects. Specifically, product seeding increases conversations about that product among non-seed consumers, and, interestingly, decreases WOM about other products from the same brand and about competitors' products in the same category as the focal product. These findings indicate that marketers can use SMCs to focus online WOM on a particular product by drawing consumers away from talking about other related, but off-topic, products.
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