Digital transformation and resultant business model innovation have fundamentally altered consumers’ expectations and behaviors, putting immense pressure on traditional firms, and disrupting numerous ...markets. Drawing on extant literature, we identify three stages of digital transformation: digitization, digitalization, and digital transformation. We identify and delineate growth strategies for digital firms as well as the assets and capabilities required in order to successfully transform digitally. We posit that digital transformation requires specific organizational structures and bears consequences for the metrics used to calibrate performance. Finally, we provide a research agenda to stimulate and guide future research on digital transformation.
Break the Wall: Why and How to Democratize Digital in your Businessexamines problems facing business units and top management adapting to digital transformation and offers solutions.
In light of the emerging discourse on AI systems' effect on society, whose perception swings widely between utopian and dystopian, we conduct herein a critical analysis of how artificial intelligence ...(AI) affects the essential nature of customer relationship management (CRM). To do so, we survey the AI capabilities that will transform CRM into AI-CRM and examine how the transformation will influence customer acquisition, development, and retention. We highlight in particular how AI-CRM's improving ability to predict customer lifetime value will generate an inexorable rise in implementing adapted treatment of customers, leading to greater customer prioritization and service discrimination in markets. We further consider the consequences for firms and the challenges to regulators.
•Artificial Intelligence will have noticeable impact on how firms manage customer relationships.•We present a critical view of expected implications of AI-CRM emergence.•AI-CRM much improve the ability to predict customer lifetime value and to adapt treatment of customers.•This will lead to greater customer prioritization and increase in service discrimination.
Seeded marketing campaigns (SMCs) involve firms sending products 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 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 empirically estimate these with a unique data set covering 390 SMCs for products from 192 different cosmetics brands. Multiple spillover effects are found, suggesting that while SMCs can be used primarily to stimulate WOM for a focal product, marketers must also account for brand- and category-level WOM spillover effects. Specifically, seeding increases conversations about that product among nonseed 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.
Data, as supplemental material, are available at
http://dx.doi.org/10.1287/mksc.2016.1001
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In a classic seeded WOM marketing campaign, a company sends product samples to a selected group of influencers, and encourages them share the product information and their own opinions with other ...consumers. Positive effects include more WOM for the focal product in the target segment, but also in additional segments. But there are additional spillover effects on the brand and the product category level and they are negative. More conversations about the focal product reduced the “off-topic” conversations about other brands in the same category as well as other products of the same brand. These negative brand and category spillover effects are stronger when the focal product is of a more functional nature. Marketers tend to consider only positive spillovers to be beneficial for a company, but negative spillovers should not be immediately classified as “bad news.” There are upsides to this effect that managers can use in their favor.
The authors develop a conceptual model that links Web site and consumer characteristics, online trust, and behavioral intent. They estimate this model on data from 6831 consumers across 25 sites from ...eight Web site categories, using structural equation analysis with a priori and post hoc segmentation. The results show that the influences of the determinants of online trust are different across site categories and consumers. Privacy and order fulfillment are the most influential determinants of trust for sites in which both information risk and involvement are high, such as travel sites. Navigation is strongest for information-intensive sites, such as sports, portal, and community sites. Brand strength is critical for high-involvement categories, such as automobile and financial services sites. Online trust partially mediates the relationships between Web site and consumer characteristics and behavioral intent, and this mediation is strongest (weakest) for sites oriented toward infrequently (frequently) purchased, high-involvement items, such as computers (financial services).
We investigate the factors that affect the growth of Groupon, the leading online daily deals platform. We concentrate on the online-to-offline (O2O) aspect of the business that differentiates it from ...other e-commerce platforms—its strong connection to local markets. We focus on travel cost and store density, the key local characteristics that affect consumer deal demand and merchant deal offering. Using a comprehensive longitudinal data set on deal offerings and sales across local markets, and combining it with local market characteristics, we estimate a simultaneous equation model of the weekly number of deal offerings and deal sales characterizing the two-sided nature of the platform. We find that the word-of-mouth effect on the consumer side and the observational learning effect on the merchant side contribute to and reinforce the expansion of a two-sided platform. However, a larger number of deals intensifies the competition, which then lowers per deal sales and limits the number of deal offerings. We find that local characteristics have significant impact on both the deal demand and the supply side. We further use model simulation to show how differences in growth patterns across markets may be driven by local characteristics, and we decompose their relative impact on the demand and supply sides. The paper provides managerial implications for firms specializing in O2O commerce.
This paper was accepted by Matthew Shum, marketing.
Platform businesses are typically resource-intensive and must scale up their business quickly in the early stage to compete successfully against fast-emerging rivals. We study a critical question ...faced by such firms in the novel context of multicategory two-sided platforms: how to optimally make investment decisions across two sides, multiple categories, and different time periods to achieve fast and sustainable growth. We first develop a two-category two-period theoretical model and propose optimal resource allocation strategies that account for heterogeneous within-category direct and indirect network effects and cross-category interdependence. We find that the proposed strategy shares the spirit of the allocation rules for multiproduct nonplatform firms and single-product platform firms, yet it does not amount to a simple combination of the existing rules. Interestingly, the business model that platforms adopt crucially determines the optimal strategy. Platforms that charge by user should adopt a “reinforcing” rule for both within- and cross-category allocations by allocating more resources toward the stronger growth driver. Platforms that charge by transaction should also adopt the reinforcing rule for within-category allocation, but follow a “compensatory” rule for cross-category and intertemporal allocations by allocating more resources toward the weaker growth driver. We use data from the daily deals industry to empirically identify the network effects, propose alternative allocation strategies stemming from our theoretical findings, and use simulations to show the benefits of these strategies. For instance, we show that reallocating 10% of the average observed investment from Fitness to Beauty can increase profits by up to 15.5% for some cities.
This paper was accepted by Matthew Shum, marketing.
Mobile advertising allows retailers, service providers, and manufacturers to provide consumers with increasingly relevant offers. The success of such campaigns depends on an ever better understanding ...of environmental, consumer, and technological context variables; a strong focus on advertising goals; accounting for market factors related to the nature of stakeholders and market environment; and the use of appropriate mobile ad elements to improve relevant outcome metrics. This article provides an overarching framework to synthesize current findings in mobile advertising, as well as a research agenda to stimulate additional work in this nascent field.
Companies increasingly use personalization to offer a better experience to their customers. Online personalization enables them to learn from customers’ data and adapt their website content ...accordingly. Although customers may value personalization, it may also trigger privacy concerns. In this context, both regulators and firms need a better understanding of the process underlying the effect of personalization on privacy concerns, as well as the role of information transparency in this process. Drawing on signaling theory, the authors propose how perceived control may mediate the negative impact of personalization on privacy concerns and hypothesize that the interaction effect of personalization and information transparency depends on customer need for cognition. Findings from two experimental studies show that perceived control is lower on personalized websites than on nonpersonalized websites, which leads to privacy concerns. However, the presence of a transparency message can mitigate the negative effect of website personalization for customers who are in low need for cognition.
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