Cross-channel effects of omnichannel retail marketing strategies: A review of extant data-driven research

The authors review 50 empirical retailing research papers that have appeared over the last 20 years to take stock of what we know, need to know better, and do not know yet about within-retailer cross-channel effects of omnichannel retail marketing strategies on (a) consumer responses over their purchase journeys, i.e., online and/or offline search, purchase intention, frequency, amount, returns, loyalty, and (b) the retail firm's aggregate outcomes (e.g., sales, costs, profits, product returns) by channel and overall. Specifically, the authors focus on five strategies: (1) the addition of online channel by an offline retailer; (2) the addition (or subtraction) of offline channels by an online retailer; (3) addition of mobile shopping channel (website and/or app) by offline and/or online retailer; (4) cross-channel integration strategies; and (5) retail marketing mix strategies. The author/s integrate findings from empirical research on these strategies into a number of ‘insights’ about ‘what we know’. Prominent among these are the following: Adding a transactional online channel to an offline channel improves the retailer's overall sales even though offline channel sales can be cannibalized to some degree. Adding an offline channel by an online retailer, however, boosts online channel sales as well as overall sales of the retailer. Similarly, adding a mobile shopping channel usually increases customer purchase frequency and amount and overall sales of the retailer in the long-term. Strategies for greater cross-channel integration generally have a positive effect on a retailer's overall performance while online advertising has positive effects on offline channel consideration and sales as well as overall sales of a multichannel retailer. Other insights or findings that need further study or open questions are also identified. The paper closes with managerial implications of the derived empirical insights, and suggestions for future research.     

Acquiring customers through online marketplaces? The effect of marketplace sales on sales in a retailer's own channels

Online retailers are increasingly using third-party online marketplaces (e.g., Amazon, Taobao) as an alternative sales channel to their website. While cross-channel sales elasticities have been established for many sales channel combinations (e.g., adding bricks to clicks), we lack an understanding of whether the use of third-party marketplaces grows or cannibalizes a retailer's sales. Practitioners argue that firms can build their e-commerce business through acquiring customers by selling on the marketplace. Indeed, a marketplace could complement a retailer's offering (e.g., acquiring new customer segments), although inventory effects might mitigate this complementarity. Alternatively, cannibalization might occur from losing customers from one's website to the online marketplace. The present research investigates which of the two opposing forces prevails using a time series of category sales data from one of the largest global marketplace sellers. The authors use vector autoregressive modeling to show that marketplace sales increase sales on a retailer's website (0.014% for every 1% in marketplace sales). This effect is strongest for categories with large choice and low product prices. Acquiring customers through the marketplace might be cheaper than through other sources (estimated at 24% of initial sales). However, online retailers should be aware that this strategy strengthens the marketplace and may have potential negative long-term consequences (e.g., through marketplace control of the customer relationship).     

Now what? Evaluating the sales effects of introducing an online store

This study creates a framework for evaluating the sales impact of adding an online channel to an existing network of physical stores. Using a unique database consisting of pooled customer data from a Swedish retailer's online and offline stores, it investigates the purchase behavior of customers before and after the introduction of an online channel. The data overcome a crucial obstacle present in previous studies in that they permit matching of individual-level customer data for both online and offline behavior. The results show significant and substantial effects of online channel introduction on customer acquisition as well as on cannibalization of physical stores.     

The effect of search channel elimination on purchase incidence,order size and channel choice

This study investigates the impact of eliminating a search channel on purchase incidence, order size, channel choice and, ultimately, sales and profits. We analyze customer panel data from a large retailer over a five-year period. The retailer conducted a randomized field test in which the firm eliminated its catalog for half of the panel. We find that channel elimination decreases purchase incidence, especially for customers who, before the test, were heavy users of the telephone purchase channel that aligns with the catalog search channel. As expected, channel choice for purchases is shifted toward the internet and away from the telephone channel. Interestingly, order size per purchase increases. We investigate the impact of channel elimination on profits across different customer segments. We calculate a net positive impact because the savings from eliminating the catalog compensate for lower sales revenues.     

Information effects of warehouse automation on sales in omnichannel retailing

The recent development of an omnichannel business environment provides a seamless shopping experience throughout the customer journey. Although previous studies have identified the importance of rapid product delivery, consumers cannot evaluate delivery quality until it has arrived. This study argued that warehouse automation and retail channel brand characteristics lead to informative signals and to firms' higher sales in the omnichannel context. By analyzing panel data from the Japanese retail market, we tested the effects of warehouse automation and the moderating effects of omnichannel, online, and offline brand offerings on the effectiveness of the warehouse automation signal. Results showed that warehouse automation signaling positively affects firms’ sales and has a positive interaction effect with omnichannel offerings.     

Integrating Bricks with Clicks: Retailer-Level and Channel-Level Outcomes of Online–Offline Channel Integration

This research examines the impact of online–offline channel integration (OI), defined as integrating access to and knowledge about the offline channel into an online channel. Although channel integration has been acknowledged as a promising strategy for retailers, its effects on customer reactions toward retailers and across different channels remain unclear. Drawing on technology adoption research and diffusion theory, the authors conceptualize a theoretical model where perceived service quality and perceived risk of the Internet store mediate the impact of OI while the Internet shopping experience of customers moderates the impact of OI. The authors then test for the indirect, conditional effects of OI on search intentions, purchase intentions and willingness to pay. Importantly, they differentiate between retailer-level and channel-level effects, thereby controlling for interdependencies between different channels. The results of three studies provide converging evidence and show that OI leads to a competitive advantage and channel synergies rather than channel cannibalization. These findings have direct implications for marketers and retailers interested in understanding whether and how integrating different channels affects customer outcomes.     

零售业顾客缺货反应研究评述

零售业主要是销售消费用品,直接面向终端顾客。关于缺货反应的研究,对后期的零售业具有重大的借鉴意义。缺货问题涉及供应链管理、顾客关系管理等诸多方面,它的研究对制造商、经销商、零售商都有很大的指导作用。否则,商品缺货可能导致零售门店损失销售额,也会削弱消费者对零售商和缺货商品品牌的信赖。     

Managing a Global Retail Brand in Different Markets: Meta-Analyses of Customer Responses to Service Encounters

This study investigates how retailers can leverage their brand to shape customers’ satisfaction with service encounters. It develops and tests hypotheses about how brand, store, and consumer factors moderate customer responses to experience clues during retail service encounters. Six meta-regression analyses synthesize and compare results from 842 satisfaction equations describing customers’ encounters with a global retailer operating 400 stores in 32 countries. The results show how customers weigh their perceptions of service encounters differently depending on brand, store, and consumer factors. In markets where customers believe the retailer has high holistic brand quality, they place less weight on experience clues within the store. In markets where customers believe the retailer’s service brand promise, they place more weight on in-store experience clues. In markets where the retailer promises utilitarian value, customers weigh functional experience clues more heavily. In markets with an online purchasing channel, the effect of experience clues common to offline and online store environments is magnified, and unique clues are diminished. In addition, customers heavily weigh experience clues that fit their goals. In general, retail success factors include high brand quality (which makes customers more forgiving), a service brand promise that is mirrored in the store image (which makes customers attend to the experience clues aligned with them), and the careful monitoring and managing of retail touchpoints (to customize experience clues to each market). In this way, retailers can use customer-based strategies to effectively design and manage their global retail brand in different markets.     

The Effects of Channel Experiences and Direct Marketing on Customer Retention in Multichannel Settings

In customer relationship management (CRM), it is critical for managers to understand how and when customers terminate their relationships with the company in order to make more accurate predictions for CLV. However, in many non-contractual settings, customer churn is not easily observed, which presents difficulty for estimating customer retention. In this research, we present a framework for estimating multichannel customer relationship dynamics in a non-contractual setting that flexibly allows for relationship revival and investigates the effects of different channel experiences and marketing communication on retention and profitability. We use a multi-segment, multivariate hidden Markov modeling framework to model three managerially relevant customer behaviors: purchase amount, purchase incidence, and channel choice. Using data from a multichannel clothing retailer, we uncover two latent relationship states that customers migrate to and from — an active state and an inactive state characterized by different levels of purchase frequency, responsiveness to marketing, and profitability. We find that an offline (retail-store) channel can be used to migrate customers from an inactive state to an active state, effectively serving the purpose of “education” or “revival,” whereas an online channel is most effective in keeping the existing active customers active, thus serving the purpose of “retention”. Using counterfactual analysis, we highlight an opportunity for the multichannel firm to optimize marketing strategies to dynamically manage and increase the retention and hence also the value of its customer base.     

Why is Price Dispersion Higher Online than Offline? The Impact of Retailer Type and Shopping Risk on Price Dispersion

When physically similar products, of similar quality, are offered by retailers both online and offline, we often observe that the dispersion in prices of these products online is greater than the price dispersion offline. This observation runs counter to early theories that suggested price dispersion online would be smaller than that offline due to the ease of search and information availability online. This paper investigates and provides an explanation for this puzzling phenomenon by examining the impact of two important drivers of price dispersion: retailer type and consumers’ shopping risk. Retailer type refers to whether a retailer is a pure offline, pure online, or dual channel retailer. Shopping risk is defined as the product of consumers’ perceived risk of shopping and the transaction uncertainty related to shopping at different types of retailers.A game-theoretic approach is adopted to model consumers’ price search and product purchase, as well as price competition within and across retailer types in online and offline markets. Equilibrium pricing strategies are derived for different retailer types competing for different consumer segments with different levels of perceived shopping risk. The impact of retailer type and shopping risk on online versus offline price dispersion are quantified, and conditions when price dispersion is greater online than offline are identified.Results indicate that price dispersion is greater online when the number of pure online retailers is sufficiently large and is increasing in the number of pure online retailers. In addition, a reduction in online shopping risk may actually increase online price dispersion. Results further suggest that even without any online sales, dual channel retailers should maintain their online presence for the purpose of information dissemination, which justifies the importance for pure offline retailer to incorporate webrooming strategies, where consumers can search for prices online but purchase offline.     

Evolution of retail formats: Past,present, and future

In this paper, the authors review current literature on retail formats and propose a new customer-centric framework for retailers to focus on as they continue to innovate and evolve. Specifically, they review the literature on how formats compare in their attributes and compete with each other; the role of customer behavior in format choice; and developments in multichannel and omnichannel retailing. They propose a framework for retail formats suggesting two paths – either reduce friction in the customer journey or enhance customer experience. They discuss the challenges faced by offline (physical store-first) and online (digital-first) retailers and elaborate on strategies each type of retailer is pursuing to address these challenges. Finally, they offer directions for future research in this domain. They conclude by calling for newer digital-first and physical-first players to continue coming up with different customer-centric formats, which they predict will slowly morph into integrated retailers, leaving space for newer players to enter the market and hence keep the wheel of retailing spinning.     

Better or Worse? Effects of online promotion habits on customer value: An empirical study

Online frequent and uninterrupted price discounts easily cause customers to form general tendencies to purchase promotions, or ‘online promotion habits’. Compared with offline promotion shopping, the distinct features of online promotion shopping make customer behaviours highly changeable and leave the effects of online promotion habits on customer value a puzzle. Using a dataset of real transactions from a leading online apparel retailer in China, this study makes continuous observations of customers’ online promotion habits. Drawing on the behavioural learning theory, we empirically investigate the dynamic effects of online promotion habits on customer value. The results reveal that after customers form online promotion habits, their customer value increases significantly. Furthermore, among customers with online promotion habits, online promotion habits exert an inverted U-shaped effect on customer value. Namely, as online promotion habits strengthen, customer value increases accordingly, yet negative outcomes show if online promotion habits exceed a certain level. We discuss the theoretical and managerial implications of our findings, which will enable researchers and practitioners to measure and dynamically manage customers’ online promotion habits.     

An omnichannel approach to retailing: demystifying and identifying the factors influencing an omnichannel experience

ABSTRACT

The purpose of this research is to identify the factors that influence an omnichannel experience. Omnichannel is an emerging approach to retailing that responds to the changing nature of how customers shop in alternation between online and offline shops, and the increasing use of digital devices (e.g. smartphones and tablets), as a consequence retailers are focusing and establishing a seamless integrated approach to their services. Omnichannel is now a hot topic in retailing but there is a lack of empirical studies into the factors that influence an omnichannel experience. Using a mixed methods approach, we propose and empirically test a conceptual model that identifies four factors influencing an omnichannel experience: brand familiarity; customisation; perceived value, and technology readiness. We conceptualise omnichannel to include three key channels; in-store, online and mobile. Two hundred and forty-six questionnaires were collected and analysed using PLS-SEM and 11 interviews were carried out with marketing/ omnichannel professionals. Our results indicate that brand familiarity has a strong influence on omnichannel (in-store, online and mobile) while perceived value has a negative impact on the mobile experience. Our results show that retailers need to consider multiple factors, such as brand familiarity, customisation, perceived value and technology readiness as influencing factors of an omnichannel experience, and plan the use of multiple touchpoints simultaneously to enhance their overall customer’s experience. Although this study demonstrates the significant factors influencing an omnichannel experience, questions remain regarding the exact use of each touchpoint by customers and the extent of overlap between the touchpoints. which .     

Engaging the unengaged customer: The value of a retailer mobile app

Mobile apps are becoming a go-to tactic for retailers because they offer the promise of highly convenient digital engagement. We hypothesize that two types of customers are best served by these apps — “offline-only” customers currently purchasing exclusively from the retailer's physical store, and “distant” customers who reside far from the physical store. For offline-only customers, the app complements the physical engagement they currently have. For distant customers, the app offers convenient engagement their remoteness currently precludes. We model app access and purchase behavior of 629 customers who downloaded a retailer's app. We find that apps generate more incremental sales among distant customers compared to near customers, and more incremental sales among offline-only customers compared to online customers. On an illustrative base of 100 K app users, we find accessing the app would generate $2.3 M in incremental sales. Consistent with our segmentation results, we find that the users with the greatest purchase lift (9.5%) due to app usage are those that are distant and offline-only. Our results confirm the economic value of retailer apps and their role as a segmentation strategy to enhance customer engagement.     

Omnichannel retailing operations with coupon promotions

This paper explores an omnichannel retail system under which the retailer offers coupons via online channels for market share and profit. It investigates the action mechanism of coupon promotion on omnichannel price and operational decisions by employing a theoretical model. Three coupon distribution modes are investigated; a scenario in which the omnichannel retailer does not offer coupons, offers coupons with a common face value, or offers coupons with a different face value. The results show that the distribution of coupons does not always lead to increased market share. Rather, market volume may be reduced if the competition between different channels is intense. When conducting a coupon promotion, the retailer always charges a higher price, but if the negative effects of coupon promotion for the competitive channel are relatively large, the retailer will reduce their price. Larger cross-selling revenue comes from ‘Buy Online, Pick Up in Store’ channel, indicating a stronger willingness to offer coupons and higher profits for the retailer. If the retailer takes the channel characteristics and consumers' channel preferences into consideration and offers different coupon face values across channels, they will derive higher profits.     

Assessing customers’ perceived value of the online channel of multichannel retailers: A two country examination

Given the constant and often dramatic technological advancements that facilitate retailing, especially online channel adoption by industry and customers, research focusing on customers perceived value of the online channel of multi-channel retailer’s requires conceptual and empirical elaboration. This study advances understanding of customer perceived online channel value and how customer perceptions of value effect online channel satisfaction and online channel loyalty. Using data from a multi-country study, we provide a deeper understanding for multi-channel retailers of how to balance investments in various value drivers to enhance online channel satisfaction and customer loyalty.     

Using online data for offline decisions: A geostatistical approach for evaluating the patronage potential of a baby-care retailer

Even though the online channel is generally not bounded by space, much insight can be derived from examining the variation in online patronage across retail space. In this paper, we propose the use of a Bayesian approach utilising the integrated nested Laplace approximation (INLA) within its framework to estimate the risk ratios as well as probabilities of online patronage. To this end, we used publicly available data (such as household access to broadband connection, population figures and business location data) in combination with online transaction data from a focal retailer to estimate and identify which locations (i.e., postcodes) have the highest probabilities of patronage from online customers of the retailer. The three covariates adjusted for were presence of a competitor, average income at the postcode level and internet access at the postcode level; of these, internet access was found to be the most significant influencing factor on online patronage of the retailer. Overall, the resultant spatial maps provide useful predictions of how the estimated risk ratios and exceedance probabilities vary across the geographic market and the implication on opening a new offline outlet and targeting customers are discussed.     

How to increase multichannel shopping satisfaction? An adapted Kano based stage-gate approach to select new technologies

Today, brick-and-mortar retailers with integrated online shops have many alternatives to increase their customers’ shopping satisfaction: They could invest in (for the retailers) new physical store technologies (e.g., beacons or magical mirrors if not implemented up to now), new online shop technologies (e.g., visual tagging or webcams), or in new less technology-based improvement options (e.g. events or product testing). We propose an adapted Kano based stage-gate approach to support multichannel retailers confronted with such selection problems. The approach is applied to a major European sporting goods retailer. 37 improvement options are pre-selected and evaluated by current and potential customers. It can be shown that instore returns, instore services, reserve&collect, click&collect, customization, product testing, and magical mirrors are drivers of satisfaction for the current customers and should be implemented in contrast to, e.g., geofencing or beacons. The potential customers are more technology-savvy, but show similar categorizations as a current customer segment and so confirm the selection.     

Cannibalization or synergy? Consumers' channel selection in online–offline multichannel systems

This paper develops and empirically validates customer shopping motives taking account of customer channel selection in multichannel systems. As each channel is associated with certain advantages and disadvantages from a customer's perspective, we develop – based on behavioral considerations – a customer typology to classify different segments of customers. This enables us to empirically analyze the interrelationship between distinct shopping motives prior marketing research has suggested and cannibalization and synergetic effects in online–offline multichannel systems. Our results show that a higher degree of customers' convenience orientation in contrast to the degree of risk aversion and service orientation encourages the selection of the online channel over the offline channel. In addition, we develop and empirically analyze a typology of customers to classify distinct segments of consumers, highlighting the associated interrelationship of individual shopping motives and cannibalization and synergetic effects. Our results indicate that the desire for service, rather than risk aversion, could potentially cannibalize customers away from the online channel.     

How customer experience incongruence affects omnichannel customer retention: The moderating role of channel characteristics

Although a positive customer experience is known to be an important source of competitive advantage, it is unclear how customer experience can be effectively managed in an omnichannel setting. Drawing on goal theory, this study explores the effect of incongruity between online customer experience and offline customer experience on customer retention in an omnichannel context. It also examines the moderating effects of three channel characteristics: transparency, convenience, and seamlessness. Our hypotheses are tested with online survey data, and the results indicate that in an omnichannel context, customer experience incongruence has a negative effect on customer retention, but channel transparency, convenience, and seamlessness can effectively mitigate this negative effect. The findings have both theoretical implications for research related to omnichannel business and customer experience and practical implications for managers of omnichannel services.