Antecedents and consequences of cross-effects: An empirical analysis of omni-coupons

As the modern retail industry evolves from multi-channel to seamless omni-channel retailing, retailers are increasingly adopting omni-channel strategies, such as the usage of omni-coupons. A consumer may obtain an omni-coupon from a digital (catalog) channel and purchase either online or via the telephone channel. Past studies have not examined such cross-channel effects at the purchase incidence level. Using customer transaction data from an omni-channel retailer, we investigate the key drivers of cross-effects, and the impact of such cross-effects on two consumer purchase outcomes (purchase value and cross-buying). We specifically study two types of cross-effects, a) catalog-to-online and b) digital-to-telephone, and find that the effect of time variables and individual characteristics on them is asymmetric. We also show that the impact of such cross-effects on purchase outcomes depends on whether the omni-coupon was sourced digitally or from a catalog. Retailers aiming to increase cross-buying should prioritize catalog coupons, while those aiming to increase purchase value should prioritize digital coupons.     

Financial consequences of adding bricks to clicks

Many e-commerce retailers are adding “bricks to clicks” – that is, opening an offline channel in addition to their digital sales channel(s). Taking the perspective of such an online pure player, this research assesses the effects of offline channel additions on the financial performance (e.g., sales, profits) and customer behavior (e.g., basket size, return rate) in the extended channel network as well as the initial online channel of the retailer. Across two studies, one at the zip code level and the other at the customer level, we find that the channel addition of a fashion and lifestyle retailer is synergistic in terms of increasing not only overall sales but also profits. At the same time, the new offline channel does not significantly cannibalize the existing online shop, as new customers are attracted through the channel addition. The effects of channel additions, however, are influenced by characteristics of customers gained before the channel addition and of the trade area around the newly opened stores: among existing customers, those who bought more in the online channel do not react as positively to the addition of an offline channel, and trade areas with socioeconomic characteristics that are often viewed as disadvantageous for digital retailing (e.g., an older population, lower average income) show a stronger positive sales effect of a brick-and-mortar addition. The attractiveness of the offline channel for these customer segments highlights that adding bricks to clicks might be most attractive for those customers who were previously unwilling to purchase from an online-only retailer.     

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.     

Efficient replenishment in the distribution channel

Efficient replenishment (ER), a business process that involves the reduction of order cost to facilitate deliveries of goods from the manufacturer to the retailer, is becoming increasingly important in distribution channel management. While a well-executed ER program is expected to lower total channel costs and increase channel profit, very little is known about how this incremental channel profit is distributed between the manufacturer and the retailer and how it varies across the two common channel relationship structures, retailer price leadership and manufacturer price leadership.In this paper, we develop the conditions under which the manufacturer and the retailer gain more or less from the adoption of ER based on a game theoretic channel model of bilateral monopoly under the two channel relationship structures. We develop analytic results on the impact of ER on purchase quantity, price and the distribution of profits in three cases, namely, (1) when only the retailer adopts ER, (2) when both the manufacturer and the retailer adopt ER, and (3) when the manufacturer and the retailer are vertically integrated in the distribution channel, which adopts ER.The results, which can be generalized for all demand functions, show that the manufacturer benefits from the retailer's adoption of ER only when the manufacturer's holding cost relative to the retailer's is sufficiently large, relative to its order cost relative to the retailer's. By adopting ER, the retailer gains more than what the manufacturer gains even if the manufacturer is the price leader. Both the parties are likely to gain more if they both adopt ER than if only the retailer adopts ER. The incremental channel profit due to the retailer's ER adoption is highest in a vertically integrated distribution channel and is greater in a retailer-led channel relationship than in a manufacturer-led relationship.     

Maximizing Profits for a Multi-Category Catalog Retailer

It is a common trend in the retail industry for catalog retailers to mail multiple catalogs, each promoting different product categories. The existing catalog mailing models do not address the issue of optimizing multi-category catalog mailing. We address this research gap by introducing a model that integrates the when and what components of a customer's purchase decision into the how much component (number of catalogs) of a firm's cross-selling strategy. In addition to comparing the impact of category-specific versus full product catalogs in generating sales in a specific category, the study also finds relative impacts of various category-specific catalogs. We jointly estimate the probability of purchase and purchase amounts in multiple product categories by using multivariate proportional hazard model (MVPHM) and a regression based purchase amount model in a Hierarchical Bayesian framework. The model accounts for unobserved heterogeneity, and uses a control function (CF) approach to account for endogeneity in catalog mailing. The results from the Genetic Algorithm (GA) based optimization suggest that the catalog mailing policy as per the proposed model would be able to generate 38.4 percent more customer lifetime value (CLV) from a sample of 10 percent of the households as compared to the current catalog mailing policy of the retailer by reallocation of the catalogs across customers and mailing periods based on their propensity to buy.     

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.     

Building With Bricks and Mortar: The Revenue Impact of Opening Physical Stores in a Multichannel Environment

A crucial decision firms face today is which channels they should make available to customers for transactions. We assess the revenue impact of adding bricks-and-mortar stores to a firm's already existing repertoire of catalog and Internet channels. We decompose the revenue impact into customer acquisition, frequency of orders, returns, and exchanges, and size of orders, returns, and exchanges. We use a multivariate baseline method to assess the impact of adding the physical store channel on these revenue components. As hypothesized, store introduction cannibalizes catalog sales and has much less impact on Internet sales. Also as hypothesized, returns and exchanges increase. Interestingly, transaction sizes of purchases, returns, and exchanges do not change. The “availability effect” produces a net increase in purchase frequency across channels. This more than compensates for increased returns, producing a net increase in revenues of 20% by adding the store channel. Our findings yield a deeper understanding of the revenue relation between channels, and of the dynamic cross-channel effects of marketing actions.     

Customer retailer loyalty in the context of multiple channel strategies

With an increasingly competitive retail environment and decreasing customer switching costs, customer retailer loyalty is a critical goal for merchants of all types. We investigate customer retailer loyalty in the context of multiple channel retailing strategies. Results show that multiple channel retail strategies enhance the portfolio of service outputs provided to the customer, thus enhancing customer satisfaction and ultimately customer retailer loyalty. These results suggest that multiple channel retailing can be a useful strategy for building customer retailer loyalty.     

On manufacturers complementing the traditional retail channel with a direct online channel

With the explosion of the Internet and the reach that it affords, many manufacturers have complemented their existing retail channels with an online channel, which allows them to sell directly to their consumers. Interestingly, there is a significant variation within product categories in manufacturer's use of the Internet as a direct distribution channel. The main objective of this study is to examine the strategic forces that may influence the manufacturer's decision to complement the retail channel with a direct online channel. In particular, we are interested in answering the following questions:

1. Why is it that in some markets only a few firms find it optimal to complement their retail channels with a direct Internet channel while other firms do not?
2. What strategic role (if any), does the direct Internet channel serve and how do market characteristics impact this role?

To address these issues we develop a model with a single strategic manufacturer serving a market through a single strategic retailer. In addition to the focal manufacturer's product the retailer carries products of competing manufacturers. Consumers in this market are one of two types. They are either brand loyal or store loyal. The retailer sets the retail price and the level of retail support, which impact the demand for the manufacturer's product. The retailer's decisions in turn depend on the wholesale price as well as the Internet price of the product if the manufacturer decides to complement the retail channel with an online channel. Our analysis reveals that the optimality of complementing the retail channel with an online channel and the role served by the latter depends critically upon the level of support that the retailer allocates to the manufacturer's product in the absence of the online channel. The level of support allocated by the retailer, in the absence of the online channel, depends upon the retail margins on the manufacturer's product relative to that on rival products in the product category. When the size of the brand loyal segment is small relative to the size of the store loyal segment then in the absence of the online channel, the manufacturer can lower wholesale price and enhance retail support, especially when the retail margins on the rival products are low. In contrast, when the size of the loyal segment is large and the retail margins on rival products are high the manufacturer will find it more profitable to charge a high wholesale price even if that induces the retailer to extend low levels of support. If the manufacturer decides to complement the retail channel with an online channel, some consumers who would have purchased from the retailer might prefer to purchase online. Our analysis reveals that when consumers' sensitivity to price differences across the competing channels exceeds a certain threshold it is not optimal for the manufacturer to complement the retail channel with an online channel. However, this price sensitivity threshold itself depends upon product/market characteristics, suggesting that manufacturers seeking to complement their retail channels with an online channel should look beyond the nature of threat the online channel poses to the retail channel in devising their optimal distribution strategies. When the retail margins on rival products are sufficiently small, complementing the retail channel with an online channel when optimal allows the manufacturer to price discriminate and enhance profits. In contrast when retail margins on rival products are sufficiently high, complementing the retail channel with an online channel serves to enhance retail support. We also identify market conditions under which profits of both the manufacturer and the retailer are greater with the online channel than that without it. This is particularly interesting since the online channel competes with the retail channel.     

What drives competitive webrooming? The roles of channel and retailer aspects

ABSTRACT

Competitive webrooming, the phenomenon in which consumers gather product information online but ultimately purchase the product in an offline store of a competing retailer, has gained traction and become a major threat for retailers. To gain a deeper understanding of its drivers, we surveyed 1081 retail customers about their most recent consumer electronic product purchase to examine the impact of channel-related aspects as well as retailer-related aspects – a dual approach that has not been applied previously. A channel’s anticipated after-sales service and price level are the strongest predictors for webrooming. Moreover, retailer aspects determine whether customers simultaneously switch retailer when webrooming. A retailer’s assurance of delivery, including payment modalities, return policies, and product obtainment, as well as competitive product prices motivate consumers to switch retailer when webrooming. These results suggest that customers have a fundamental need for certainty within and after the buying process, which can be satisfied by both channel and retailer. Additionally, this is the first study to empirically test for interactions between channel and retailer aspects, as they are likely to occur in real shopping situations. We identified two interactions: First, a retailer’s assurance of delivery can compensate for an anticipated lack of a channel’s after-sales service, dampening the impact of the latter on competitive webrooming. Second, retailer’s price attractiveness acts in a similar vein. Hence, to steer customers into channels and/or keep them with the company, retailers should emphasize their price attractiveness as well as assurance of delivery.     

Price and quality decisions in a vertically-differentiated supply chain with an “Online-to-Store” channel

Because of the prevalence of “Online-to-Store (OS)” channel, customers can purchase differentiated products online and pick up in-store. We develop a Stackelberg game-theoretic model to study the impact of an OS channel on quality levels, demands, prices, and profits of a manufacturer and a retailer in a supply chain. We assume that the retailer acts as a Stackelberg leader, and the manufacturer acts as a Stackelberg follower. The manufacturer produces and sells two products with vertically-differentiated quality levels to the retailer who in turn sells the products to customers through a Store channel, an Online channel, or an OS channel. The retailer incurs a handing cost if the OS channel is available, and consumers bear a shipping cost and a transaction cost when the products are purchased from the Online and Store channels, respectively. We find that the manufacturer should reduce both products’ quality levels and wholesale prices, whereas the retailer can increase the selling prices for a relatively small shipping cost and a not too small handling cost. When the products are available both online and in-store, however, the quality levels, wholesale prices and selling prices might increase for a small shipping cost and a not too small handling cost. Compared to the case in which both products are available online only with the OS channel, adding the Store channel is always beneficial for both parties. The intuition behind these results hinges on the trade-off between the handling cost and the increased market demand for the retailer. Moreover, the quality levels, the wholesale prices of both products, and the selling price of the low-quality product would decrease, while the selling price of the high-quality product increases for a sufficiently low transaction cost and a not too small shipping cost.     

Optimal generic and brand advertising efforts in a decentralized supply chain considering customer surplus

While the previous researches of advertising efforts decisions focus on only the firms' profit target, no literature introduces corporation social responsibility target into advertising efforts decisions of a supply chain (SC). To fill this gap, we consider a two-stage SC with a manufacturer and a retailer where the SC members consider the customer surplus. Both the retailer and the manufacturer can invest in generic advertising efforts to influence and increase the products' sales volumes. This paper investigates the following four scenarios: (1) The retailer cares the customer surplus (Model I); (2) The manufacturer cares the customer surplus (Model II); (3) Both the retailer and the manufacturer care the customer surplus (Model III); (4) We then extend the model III to the case that the manufacturer invests in both the generic and brand advertising efforts (Model IV). The objective of this paper is to determine the optimal retail price, the optimal advertising efforts, and the optimal profits of SC members, and find the influence of customer concern level on the SC performance. Finally, numerical examples are conducted to investigate the influence of the customer concern levels of the retailer or the manufacturer on the profits of the SC members and the entire SC. We also study the joint impacts of the customer concern levels of the retailer and the manufacturer on the SC performance. We find that the SC obtains the highest profits when the retailer's customer concern level and the manufacturer's customer concern level are relatively high, and the best cooperative strategy for the retailer and the manufacturer is that they improve customer concern level simultaneously.     

Basket Composition and Choice Among Direct Channels: A Latent State Model of Shopping Costs

Shoppers of multi-channel retailers often place orders using different channels on different shopping occasions. The differential use of channels is related to both basket composition and channel characteristics, such as the ability of the channel to provide additional information that resolves uncertainty about the purchase. In this paper, we examine the impact of basket composition on the choice among direct channels. We develop a two-stage, shopping cost model with two, latent states. Given a shopping basket, the shopper first decides if she needs additional information about items in the basket. If she is uncertain about the items in the basket meeting her needs, she uses an information rich channel, such as the retailer's website or call center, and risk reduction costs become salient in addition to the other shopping costs. If she does not require additional information, she places her order by choosing among all available channels, and she may incur a welfare loss from making a purchase that does not optimally meet her needs. We operationalize welfare loss with Shannon information and various metrics based on purchase history.Our empirical setting is a data set from a catalog retailer that offers multiple direct channels. Our estimates show that basket composition impacts channel choice. Large baskets shift to the Internet channel, suggesting that the Internet channel has lower ordering costs. High-risk baskets shift to call centers and this suggests that the call center has lower risk reduction costs. Collectively these estimates provide evidence for the notion of channel specialization—some channels are better at addressing certain shopping costs compared to others. Our estimates also show that electronic self-service channels have high initial access costs and a significant learning curve compared to the call center suggesting that these channels might be better suited to heavy users. We use the estimated model to quantify the value of channels, to identify categories that need risk reduction, and to segment and target shoppers for Internet ordering based on basket size and the potential to accumulate experience.     

Exploiting the installed base using cross-merchandising and category destination programs

We investigate two ways to increase sales and customer loyalty by taking advantage of a store's installed base of current customers. We propose a classification of products into two types. Products of Type 1 are products for which consumers have a loyalty to a specific retailer and, as far as possible, always shop at that retailer for these products. The other products (Type 2) are not associated with any retailer and are bought at whichever retailer consumers happen to shop when they plan or remember to buy the product. With this in mind, we test the potential of two marketing tools to help retailers increase their share of sales of the Type 2 segment. Using a category destination program we show that one can successfully transform Type 2 into Type 1 products. Using cross-merchandising promotions, we show that one can increase the sales of Type 2 products thereby gaining a larger share of discretionary purchases than what one would receive from a straight random allocation. Both series of tests yielded significant increases in sales and profits and were deemed successful by the retailers who implemented them.     

The omnichannel continuum: Integrating online and offline channels along the customer journey

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.     

Electronic Logistics Service Quality (e‐LSQ): Its Impact on the Customer’s Purchase Satisfaction and Retention

The Internet retailing industry continues to grow rapidly. Several Internet retailers are, however, struggling to retain customers due to the high level of competition among incumbents. We propose that customer satisfaction with the order fulfillment process is an important determinant of overall customer satisfaction with the retailer, as well as with the extent of customer retention enjoyed by the retailer. This paper offers a new concept for electronic logistics service quality and investigates the relationship between the quality of online fulfillment and the ensuing retention of customers, using archival data on 260 online retailers. The structural equation model results indicate that satisfaction with the physical distribution quality and cost are positively related with customer’s purchase satisfaction and customer retention. Additionally, the results indicate that while purchase satisfaction is a strong indicator of customer retention, underlying drivers of purchase satisfaction do not have nearly the same impact on customer retention directly as they have on purchase satisfaction.     

Does online observational learning matter? Empirical evidence from panel data

The information presented on a product sales page plays an important role in consumers' purchase decisions. This study examines the persuasive effect, whether a customer's choice is heavily driven by information inferred from others' behavior, and how these impacts are moderated by market age and product type. Results show that online customer choice was significantly affected by historical cumulative sales and times saved. Positive cumulative sales and shop service quality have a significant positive impact on product sales. The times saved have no direct impact on product sales. For different types of products, the times saved of experiential products has a significant impact on product sales, while the shop service quality information of search products has a greater impact on product sales. The influence of online observation learning on product sales will be significantly moderated by a combination of product type and market age. These findings not only offer important theoretical contributions to e-commerce research but also provide practical implications for online sellers and managers of social commerce platforms.     

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.     

How information processing and mobile channel choice influence product returns: An empirical analysis

The mobile internet is starting to overtake the desktop device‐based internet as a purchase channel. Its impact on consumer behavior is therefore increasingly important to understand. This study seeks to understand and measure, if usage of mobile devices for online purchases leads to a lower decision quality and, in effect, to more product returns. In doing so, the impact of information environments on the end‐to‐end consumer purchase decision‐making process is better understood and it is investigated, if the information environment of mobile devices leads consumers to take more error‐prone purchase decisions. An exclusive data set spanning more than 140 million transactions of a European online retailer is used to empirically analyze changes in product return behavior after mobile channel adoption. The results show that mobile channel usage is positively related to product returns, overall and for both, purchases made with mobile devices and purchases made with desktop devices, although prior literature predicts that returns from desktop purchases should not increase. These findings suggest that through new channels, consumers’ information environment is altered sufficiently to affect their decision accuracy. Moreover, the results indicate that previous research may be overestimating the positive effect of mobile channel adoption on sales by disregarding changes in product return behavior.     

Substitution or Promotion? The Impact of Price Discounts on Cross-Channel Sales of Digital Movies

Technology is transforming the marketing function in many ways, and this transformation is particularly apparent for information goods such as movies where digital technologies provide marketers with new distribution channels, which in turn create new opportunities for cross-channel effects. However, these digital channels also provide researchers with new opportunities to measure micro-level customer behavior to understand the impact of cross-channel effects in real-world settings.In this paper, we study cross-channel effects between movies sold in digital purchase (commonly known as Electronic Sell Through or EST) and digital rental (commonly known as Video-On-Demand or VOD) markets. We do this using a unique sales dataset from a major digital movie retailer provided by a major movie studio. Our analysis takes advantage of a 14-week field experiment that allows us to measure the impact of price discounts on own- and cross-channel sales. We use this experiment to estimate own and cross price elasticities, whether price discounts cannibalize future sales, and most importantly whether price discounts in one channel affect sales for the same product in a presumably competing channel.Our analysis indicates that digital movie consumers are highly sensitive to price promotions. However, we also find that, contrary to expectations, price promotions in a digital sales channel for a movie do not seem to cannibalize digital rentals. Indeed, our results suggest that, if anything, price promotions for digital movie sales can increase digital rentals. We explore a variety of explanations for this counterintuitive result, including the possibility that the ease of information transmission online through third-party websites, blogs, and online discussion areas may create information spillovers such that price discounts in one channel may increase product awareness in other competing sales channels. From a managerial perspective, our results suggest that cross-channel cannibalization can be reduced or even reversed in the presence of information spillovers, and that there are many new opportunities for marketers to directly measure these cross-channel effects using experimental data from online platforms.