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[Display omitted] •Omnichannel deal prone segments use different channels to procure and use promotions.•Motivation, opportunity, and ability factors predict segment membership.•Omnichannel deal prone segments focus either on offline or online, but not on both.•Online and On-and-offline segments respond more to promotions than offline segments.•Managers can use results to target deals to the right segments in the right channels. Today's retail promotional environment is driven by channel proliferation, customer channel preferences, and managers’ efforts to create a unified “omnichannel” customer experience. This paper identifies the omnichannel deal prone segments that emerge in this environment, that is, segments that employ multiple channels to procure and use promotions. We describe these segments, measure the motivations, opportunities, and abilities (MOA) associated with segment membership, and quantify how these segments respond differently to promotions. We apply latent class cluster analysis to a database of over 1,000 respondents in three product categories. We find a rich array of omnichannel deal prone segments. Interestingly, 82% of consumers have bifurcated into online- or offline-focused deal prone segments. That is, most consumers use multiple channels to procure and use promotions, but they focus on either online or offline channels. Only seventeen percent of consumers strongly utilize both online and offline channels. We find that opportunity factors such as access to physical stores, and ability factors such as online shopping experience, explain this finding. We discuss how our results enable managers to target the right promotion designs to the right customers through the appropriate channels.

This study evaluates the differential effect of price promotions on brand choice across the offline and online channels of a grocery retailer. We use scanner data to analyze the purchasing behavior of orange juice of a sample of multichannel customers of a large European grocery chain selling across offline and online stores. We find that promotions have a higher impact on offline than in online purchases. In fact we don’t find a significant effect of promotions in the online channel. We also find a moderating effect of purchase frequency in the category, in the sense that frequent customers are more influenced by promotions than infrequent customers. While this effect is clear in the offline channel, it is not found in the online channel. There is also a high degree of heterogeneity in the effect of promotions among consumers, specially in the offline channel. It is important to remark that these differential effects across channels have been found for the same sample of multichannel customers, meaning that the same consumers are more affected by promotions offline than online. Potential causes and consequences of these results, as well as implications for management, are also discussed.

Purpose – The purpose of this paper is to present a buying process for the multichannel consumer (MCC) that starts at online information search and ends at the offline retail channel and then seeks to determine the universality of such behavior across countries. Design/methodology/approach – A structured questionnaire was administered to MCCs from Russia, Singapore and the USA. The model was estimated using partial least square and country comparisons were conducted with a multi-group analysis. Findings – The empirical results validated the conceptual model. In country comparisons, there is both converging (online information search) and diverging (retail store) MCCs’ behavior exhibiting nuanced differences. Research limitations/implications – Future research should examine values of MCCs at the individual level so as to increase the generalizability of the findings. Practical implications – The convergence of MCCs information search behavior suggests that there is an opportunity for companies to standardize their online information strategy to educate global MCCs prior to their visiting brick and mortar stores. In-store salesperson remains important and effective for MCCs in the USA and Singapore, but not Russia. Originality/value – A new conceptual framework that integrates economic and psychology theories is presented to depict the shift of control tilting in favor of MCCs in the buying process and introduces the concept of “reversal” information asymmetry in which consumers perceive to have more knowledge than the vendors.

Purpose The purpose of this paper is to investigate the impact of adaptive selling (AS) when “click and brick” in control multichannel consumers (MCCs) encounter in-store salespeople. Design/methodology/approach An online survey was administered to 387 college students from several southeastern colleges in the USA. The study consisted of a single manipulated factor (AS: high vs low) and a second measured factor (degree of MCC search: high vs low). Covariance-based structural equation modeling was selected and analysis was conducted using IBM SPSS AMOS 22.0.0.0. Findings The findings indicate that while perceptions of control in the retail store increase as customers engage in more multichannel search behavior, the path from perceived control (PC) to purchase intention (PI) is also positively affected by AS as multichannel search increases. Practical implications To increase in-store purchases by consumers using the physical location as an information channel, professional sales training, specifically AS skills, should be considered by retail managers for in-store sales personnel. Our findings suggest that salespeople can use AS skills to increase the likelihood of the MCCs’ in-store PI while not reducing their feelings of PC. Originality/value In a time where many marketers struggle with how to combine multichannel retailing efforts effectively, this research confirms that new channels create MCCs who desire control. AS shows promise as a technique for retailers to use when selling to a consumer who values control.

•Omnichannel marketing is a continuum of strategies.•The continuum unifies the customer journey and channel choice.•Omnichannel strategy is vertical (integrate journey) and horizontal (integrate channels).•Consumer behavior and marketing determine where a firm should position along the continuum.•Ten consumer and marketing determinants of omnichannel strategy have strong empirical support. This paper provides a framework for conceptualizing omnichannel integration as a continuum, identifies phenomena that determine how firms should position along that continuum, and summarizes empirical research regarding these phenomena. The framework combines the customer journey (search to purchase to aftersales) and channel choice (online vs. offline). This generates a range of omnichannel strategies, anchored by “Unconnected” on one extreme and “Complete” on the other. In between, “Vertical” strategies integrate channels over the customer journey, while “Horizontal” strategies integrate across channels at a given stage in the customer journey. We draw on more than 200 articles to identify 10 consumer and marketing phenomena (“determinants”) that influence where a firm should position along the continuum. This however raises challenges. For example, empirical research surprisingly finds many customers belong to an offline-focused segment. This suggests a Vertical strategy linking offline channels. However, today's turbulent retail environment questions whether the offline-focused segment will endure. Should the retailer cater to offline-focused customers or facilitate their progression to “multichannelism”? Another finding is that consumers strongly prefer consistency across channels. This suggests a Horizontal strategy. However, consistency might create channel cannibalization. How can the retailer avoid this? We discuss these and several other findings regarding the impact of the 10 determinants on omnichannel continuum strategy. We identify issues researchers need to research and managers need to consider when developing omnichannel continuum strategy. [Display omitted]

In recent years, online retailers (also called e-tailers) have started allowing manufacturers direct access to their customers while charging a fee for providing this access, a format commonly referred to as agency selling. In this paper, we use a stylized theoretical model to answer a key question that e-tailers are facing: When should they use an agency selling format instead of using the more conventional reselling format? We find that agency selling is more efficient than reselling and leads to lower retail prices; however, the e-tailers end up giving control over retail prices to the manufacturer. Therefore, the reaction by the manufacturer, who makes electronic channel pricing decisions based on their impact on demand in the traditional channel (brick-and-mortar retailing), is an important factor for e-tailers to consider. We find that when sales in the electronic channel lead to a negative effect on demand in the traditional channel, e-tailers prefer agency selling, whereas when sales in the electronic channel lead to substantial stimulation of demand in the traditional channel, e-tailers prefer reselling. This preference is mediated by competition between e-tailers—as competition between them increases, e-tailers prefer to use agency selling. We also find that when e-tailers benefit from positive externalities from the sales of the focal product (such as additional profits from sales of associated products), retail prices may be lower under reselling than under agency selling, and the e-tailers prefer reselling under some conditions for which they would prefer agency selling without the positive externalities. This paper was accepted by Chris Forman, information systems.

[Display omitted] •Online sales for hybrid retailers exceed those of pure, online retailers.•Distrust of pure etailers is a key reason behind the hybrid retailer advantage.•Etailers can manage psychological distance in ways that increase trust perceptions.•Tangibility and social proximity can be used to reduce psychological distance.•Simple and readily available website images offset the hybrid retailer advantage. E-commerce offers retailers the opportunity to attract new customers online; however, consumer distrust toward unfamiliar retailers can seriously impede these efforts. Construal Level Theory suggests that such distrust can be partially understood in terms of psychological distance, and that reducing psychological distance using simple website tactics should overcome distrust and encourage first-time purchases. Studies 1 and 2 show a physically distant retail store, or lack of a physical store altogether, contribute to psychological distance, distrust, and reluctance to purchase online. Studies 2 and 3 further show that website images of an office building (increased tangibility), or the owner's name and appearance (social proximity), can improve trust and purchase intentions by specifically reducing the psychological distance otherwise associated with purely virtual or physically distant retailers.

How does the monetary value of customer purchases vary by customer preference for purchase channels (e.g., traditional, electronic, multichannel) and product category? The authors develop a conceptual model and hypotheses on the moderating effects of two key product category characteristics—the utilitarian versus hedonic nature of the product category and perceived risk—on the channel preference—monetary value relationship. They test the hypotheses on a unique large-scale, empirically generalizable data set in the retailing context. Contrary to conventional wisdom that all multichannel customers are more valuable than single-channel customers, the results show that multichannel customers are the most valuable segment only for hedonic product categories. The findings reveal that traditional channel customers of low-risk categories provide higher monetary value than other customers. Moreover, for utilitarian product categories perceived as high (low) risk, web-only (catalog- or store-only) shoppers constitute the most valuable segment. The findings offer managers guidelines for targeting and migrating different types of customers for different product categories through different channels.

This article provides a more integrative approach toward channel choice than previous research by considering all stages of the buying process (search, purchase, and after-sales), and by taking channel attributes, experience, and spillover effects into account when examining consumers' channel choice intentions. The authors show that such an integrative perspective is important as channel attributes, experience, and spillover matter for consumers' channel choices in all stages of the buying process. Notably, the study stresses the importance of channel experience and spillover effects for explaining consumers' channel choice intentions in the different stages of the buying process. Channel experience effects occur when using the channel increases the likelihood that the consumer will use the very same channel on the next occasion. Spillover effects result when the likelihood of using a channel in one stage of the buying process affects the likelihood of choosing that channel in another stage. The results show that both effects influence consumers' channel choice intentions over and above channel attributes. Importantly, the model results strongly pledge for studying attribute, experience, and spillover effects simultaneously.

Technology enables a firm to produce a granular record of every touchpoint consumers make in their online purchase journey before they convert at the firm's website. However, firms still depend on aggregate measures to guide their marketing investments in multiple online channels (e.g., display, paid search, referral, e-mail). This article introduces a methodology to attribute the incremental value of each marketing channel in an online environment using individual-level data of customers' touches. The authors propose a measurement model to analyze customers' (1) consideration of online channels, (2) visits through these channels over time, and (3) subsequent purchases at the website to estimate the carryover and spillover effects of prior touches at both the visit and purchase stages. The authors use the estimated carryover and spillover effects to attribute the conversion credit to different channels and find that these channels' relative contributions are significantly different from those found by other currently used metrics. A field study validates the proposed model's ability to estimate the incremental impact of a channel on conversions. In targeting customers with different patterns of touches in their purchase funnel, these estimates help identify cases in which retargeting strategies may actually decrease conversion probabilities.