Advancing the marketing-operations interface in omnichannel retail

Abstract

Omnichannel retail has experienced enormous growth in the last decade, becoming the new normal for many consumer products (McKinsey & Company, 2021). Many retailers have moved from being either pure bricks-and-mortar or online-only to serving customers across channels. For example, traditional retailers such as Walmart and Best Buy have opened e-commerce channels. Conversely, online-first retailers and vertically integrated brands like Amazon and Nike have added physical stores to their e-commerce channels (Avery et al., 2012). In contrast to multichannel retail where channels coexist without any coordination, omnichannel retail combines expansion into different channels with coordination and integration to facilitate seamless customer journeys (Akturk et al., 2018; Bijmolt et al., 2021; Hübner et al., 2016; Rooderkerk & Kök, 2019; Verhoef et al., 2015). To integrate their channels, retailers have adopted omnichannel fulfillment models such as “buy online pick up in-store” and “ship-from-store.” Channels have been (re)designed in terms of omnichannel customer journeys. To illustrate, digital vertical-native brands, such as Bonobos (men's wear) and Warby Parker (eyewear) employ “zero-inventory” showrooms where shoppers can inspect a product but not take it home. Such omnichannel fulfillment models combine the strengths of the different channels within a single customer journey: the store for physical inspection, and the online channel for convenient fulfillment.

Omnichannel retail aims at facilitating customer switching between channels across and within customer journeys. Achieving this requires retailers to carefully consider the challenges that customers experience in combining channels within a given customer journey. This includes difficulty in accessing online information from within the store, or in obtaining reliable information as to whether a product found online is available for inspection in a given store (Rooderkerk & Kök, 2019). The friction created from traversing channels within a given customer-journey stage¹ or between two consecutive stages is reduced through information technology and a variety of omnichannel fulfillment solutions (see, e.g., Akturk et al., 2018; Hübner et al., 2022). Balancing the advantages of seamless omnichannel integration with the cost of seamlessness represents a standard operations management (OM) trade-off exercise. Trading off effectiveness and efficiency must consider both the marketing and the operations perspective: Omnichannel fulfillment models that are effective with respect to measures like sales conversion and service quality may not appear to be efficient with respect to measures like fulfillment cost and lead time.

Following Browning (2020) we observe that the marketing-operations interface in omnichannel retail is manifest in several areas, such as developing and managing new technologies to support omnichannel retail, new product development in omnichannel retail (Gallino & Rooderkerk, 2020), on-demand production in omnichannel settings (e.g., 3D printing), and leveraging omnichannel solutions for product support.

Customer behavior and fulfillment emerge as key areas of focus in this special issue, building around key decisions that arise from the interaction between marketing and operations when implementing and managing omnichannel retail.

Omnichannel consumer behavior and fulfillment models require retailers to involve both their operations and marketing functions in decision-making. Table 1 lists key decisions facing retailers concerning a specific type of omnichannel customer behavior and fulfillment, as well as the opportunities and threats that retailers should consider in making these decisions.

Section 2 made clear that understanding and mitigating the potential information barriers between online and offline channels are key to success in the omnichannel context. Ren et al. (2023), the first paper in this special issue, study the effect of sharing brick-and-mortar store product availability in an omnichannel context with consumers subject to asymmetric assortments. Using data related to housewares, toys, and apparel of a North-American retailer, they show that online sharing of offline product availability data increased overall sales, particularly from customers within the trading area of the store. They show that sharing this information shifted sales from the physical to the online channel. Consumers were observed to switch to the online channel when they became aware that local stores might not have the product in stock, with this shift to online accompanied by a slight increase in the return rate. This study shows the importance of jointly considering marketing and operations aspects of omnichannel initiatives, unveiling interesting (unintended) side-effects: Cross-channel product assortment transparency in omnichannel retail not only turns out to boost overall sales, but it also increases return rates because of customers migrating to the online channel.

To the extent that e-marketplaces such as Taobao and Amazon are part of omnichannel customer journeys, friction involved with the use of this channel type could result in substantial losses to retailers. However, the online-offline integration of platforms has received little attention so far. Addressing this gap, Fang et al. (2023) compare two fulfillment models that arise when, under competitive pressure, platforms decide to provide third-party sellers support for channel integration. In the first fulfillment model, the so-called (i) informational online-offline channel integration, the platform provides so-called “SAME” labels to signal that the identical product is also available at third-party sellers' sites. The second model, called (ii) transactional online-offline channel integration, constitutes the buy online, pickup in-store (at one of the third-party's physical sites) fulfillment. Using data from a Chinese B2C platform, Fang et al. (2023) show that offering (i) informational integration dampens a platform's sales growth while (ii) transactional integration has no significant effect on sales growth. They further reveal how these effects are moderated by the seller's inter-platform function usage. Platforms that feel competitive pressure to respond to third-party seller demands by developing cross-channel integration may reduce friction and channel cannibalization effectively by prioritizing a buy-online, pickup-in-store model.

Current omnichannel literature has relied heavily on analytical modeling to portray the mechanisms in omnichannel retail (e.g., Gao & Su, 2017; Wu & Chen, 2022), or on quasi-experimental work that analyzes the effect of channel expansion-integration and the introduction of omnichannel fulfillment models (e.g., Akturk et al., 2018; Avery et al., 2012; Fang et al., 2023; Gallino & Moreno, 2014; Ren et al., 2023). This work has mainly been descriptive and sales-centric. Our special issue has sought to add empirical work to this important topic. The presentation of customer behavior and fulfillment models in Table 1 suggests that ample opportunities exist for both retailers and customers to gain an advantage from omnichannel fulfillment, and empirical research can lead to improved decision-making in this context. The growing availability of omnichannel systems and data encourages researchers to investigate the omnichannel marketing-operations interface. Key research areas include: