Social Contagion and Customer Adoption of New Sales Channels

We develop and test hypotheses regarding the role of social contagion in customer adoption of new sales channels. We examine two aspects of social contagion (local contagion and homophily) and two channels (Internet and bricks-and-mortar store). Drawing on diffusion theory, we propose a conceptual framework that identifies the factors associated with new channel adoption. Using longitudinal data from a major catalog company and a discrete-time hazard model, we find that (1) social contagion plays a major role in the adoption of new sales channels, (2) both local contagion and homophily influence channel adoption, (3) longer-tenured customers are less influenced by social contagion, and (4) adoption of the Internet channel is more influenced by social contagion than adoption of the bricks-and-mortar store. Managerially, our results suggest that marketing programs that encourage social contagion, for example, word-of-mouth campaigns, be targeted based on both physical and socio-economic proximity, and that such campaigns will play a bigger role in the adoption of new-to-the-world channels.     

Redesigning after-sales service: Impact on incumbent product distribution channels

With the growth of multi-channel retailing, many firms that have traditionally relied upon third-party service providers to offer after-sales service (AS) have introduced direct AS channel. While there exist a few studies that examine the effects of adding a direct sales channel on the sales revenue of incumbent channels, there are no studies investigating the effects of adding direct AS channel. This study tries to fill this research gap by exploring cross-channel effects of including AS through the firm's direct brand stores on performance (i.e., revenue, assortment width, and extent of upselling) in both direct and indirect channels. A matched difference-in-difference quasi-experimental design was used to compare the sales outcomes of test and control groups using a five-year longitudinal dataset from a large dual-channel consumer durables firm. Results reveal that providing AS through the firm's direct channel has a positive significant effect on the revenue and upselling in the indirect channel, but no significant impact on assortment width in the indirect channel. However, unlike hypothesized, it results in significantly lower revenue, assortment width, and upselling in the direct channel. We interpret these negative effects as arising from customer confusion and perceived retail crowding. Overall, our research highlights that implementation of going direct with AS should be done with utmost care. Our findings would serve as a building block for future studies that are conducted to understand the dynamic cross-channel effects of introducing direct AS, and would be useful for drawing comparisons and contrasts.     

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.     

Pricing of mall services in the presence of sales leakage

For a shopping mall, sales leakage occurs when consumer purchases facilitated by the mall are finalized outside it. These sales include, for example, catalog orders filled at the leased premises in a physical mall; For an Internet mall, they include the ones consumers make on an on-line store’s website after learning about the store from an Internet mall website. While these sales are difficult to track in the physical mall, Internet malls like Yahoo can track them by placing cookies on consumers when they visit the mall. The challenge for a mall owner then is to design an appropriate pricing model which takes sales leakage into account. In fact, Yahoo currently uses an All-Revenue-Share Fee with Yahoo collecting from on-line stores a share of all sales revenue, regardless of whether the purchase was made through the mall or directly from the store’s own URL. We explore this new All-Revenue-Share Fee model, compare it with the commonly used Fixed Fee model and the two-part tariff model, and identify the model with the highest profits for the mall under different conditions. We suggest that although an All-Revenue-Share Fee is appealing for Internet malls due to its ability to capture sales leakage directly, it may cause the stores to refrain from joining the mall in certain circumstances. Thus, in certain situations charging a fixed monthly fee can actually be more profitable for the mall versus the All-Revenue-Share Fee model. We also examine how mall and product category characteristics as well as market expansion affect the optimal pricing strategy. We show that a mall should price discriminate across product categories, not just by charging different amounts of fees, but by using different pricing models. Our research provides many managerial implications on how to price over time.     

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.     

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.     

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.     

Key Issues in Multichannel Customer Management: Current Knowledge and Future Directions

Multichannel customer management is “the design, deployment, and evaluation of channels to enhance customer value through effective customer acquisition, retention, and development” (Neslin, Scott A., D. Grewal, R. Leghorn, V. Shankar, M. L. Teerling, J. S. Thomas, P. C. Verhoef (2006), Challenges and Opportunities in Multichannel Management. Journal of Service Research 9(2) 95–113). Channels typically include the store, the Web, catalog, sales force, third party agency, call center and the like. In recent years, multichannel marketing has grown tremendously and is anticipated to grow even further. While we have developed a good understanding of certain issues such as the relative value of a multichannel customer over a single channel customer, several research and managerial questions still remain. We offer an overview of these emerging issues, present our future outlook, and suggest important avenues for future research.     

Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com

We investigate the cross channel effects of search engine advertising on Google.com on sales in brick and mortar retail stores. Obtaining causal and actionable estimates in this context is challenging: Brick and mortar store sales vary widely on a weekly basis; offline media dominate the marketing budget; search advertising and demand are contemporaneously correlated; and estimates have to be credible to overcome agency issues between the online and offline marketing groups. We report on a meta-analysis of a population of 15 independent field experiments, in which 13 well-known U.S. multi-channel retailers spent over $4 Million in incremental search advertising. In test markets category keywords were maintained in positions 1-3 for 76 product categories with no search advertising on these keywords in the control markets. Outcomes measured include sales in the advertised categories, total store sales and Return on Ad Spending. We estimate the average effect of each outcome for this population of experiments using a Hierarchical Bayesian (HB) model. The estimates from the HB model provide causal evidence that increasing search engine advertising on broad keywords on Google.com had a positive effect on sales in brick and mortar stores for the advertised categories for this population of retailers. There also was a positive effect on total store sales. Hence the increase in sales in the advertised categories was incremental to the retailer net of any sales borrowed from non-advertised categories. The total store sales increase was a meaningful improvement compared to the baseline sales growth rates. The average Return on Ad Spend (ROAS) is positive, but does not breakeven on average although several retailers achieved or exceeded break-even based only on brick and mortar sales. We examine the robustness of our findings to alternative assumptions about the data specific to this set of experiments. Our estimates suggest online and offline are linked markets, that media planners should account for the offline effects in the planning and execution of search advertising campaigns, and that these effects should be adjusted by category and retailer. Extensive replication and a unique research protocol ensure that our results are general and credible.     

Internet and distance channel use and European consumer complaint behavior

This exploratory study analyzes the effect of distance-shopping channel choice (i.e. the format first used by consumers in a retail transaction) on consumer complaint behavior, with a special focus on the Internet channel. It analyzes 2011 Eurobarometer data using a logistic regression model controlling for sociodemographic and country-specific variables to measure the impact of using the Internet, post/catalog, and telephone channels on complaint behavior. The results indicate that consumers using the Internet channel exhibit the greatest likelihood of complaint behavior when compared to consumers using traditional distance-shopping channels. Implications and suggestions for retailers are discussed, as are the contributions to the consumer complaint behavior literature.     

Marketplace,reseller, or web-store channel: The impact of return policy and cross-channel spillover from marketplace to web-store

With the advent of e-commerce, new platform sales have been created in the online retailing industry, and choosing the best platform has become a challenge for manufacturers. For instance, marketplace and web-store are two e-channels for selling goods directly to end customers. In the marketplace, manufacturers sell their products directly to online customers through e-tailers' platforms and share revenue with e-tailers. In the web-store channel, manufacturers sell their products directly to end customers through their platforms and do not need to e-tailers' platforms. However, some manufacturers and e-tailers continue with reseller channel yet. Reseller channel is another conventional channel in which manufacturers distribute their products to e-tailers, then e-tailers choose retail prices and sell them to consumers. Therefore, with these three different channels, the key question is when and under what conditions manufacturers can choose marketplace or reseller channel in addition to their web-store channels to grow their market share. In this paper, we analyze these three different e-channels and the conditions that manufacturers adopt the marketplace or reseller channel. For this purpose, we consider a model with two manufacturers and one e-tailer in which the manufacturers have their web-store channels, and they are willing to adopt another channelـ reseller or marketplace. The manufacturers offer a return policy in their web-store channels as a competitive strategy for attracting more customers. We find that offering return policy in web-store channels has no effect on the choice between the marketplace and reseller channel, but it has an impact on the amount of manufacturers' profits in each channel. Also, we demonstrate that regardless of offering return policy, as the coefficient of cross-channel effect increases, the manufacturers' profits, whether they choose reseller channel or marketplace channel, increase. But, as the coefficient of cross-channel effect increases, the e-tailer's profit increases when both manufacturers choose reseller channel, otherwise decreases. If manufacturers offer a return policy, the e-tailer's profit is highest when both manufacturers choose reseller channel, and if they do not offer a return policy, the e-tailer's profit is highest when both manufacturers choose marketplace channel.     

Store-, Market-, and Consumer-Characteristics: The Drivers of Store Performance

Four factors have traditionally been identified in influencing store performance: store-, market-, and consumer characteristics and competition. Given partially conflicting and, in some cases, dated findings in the literature we want to re-assess the effects. In particular, past research has usually considered only two out of the four constructs at any time, which is likely to result in erroneous interpretation of results. We draw upon a unique cross-sectional sample of grocery stores with a wide array of store characteristic, store performance, trade area, and consumer demographic variables. Using structural modeling, our prime interest is to assess the differential impact of store attractiveness, market potential, and socio-economic status on two different store performance measures, while controlling for competitive effects. We find that the market potential of a store is by far the most important driver of store sales performance and sales productivity performance. With one exception, the model and the data support the hypothesized relationships about the direction and the strength of the impact of a store's attractiveness, market potential and socio-economic characteristics of the trade area on a store's performance.     

The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry

There are growing interests in understanding how word-of-mouth (WOM) on the Internet is generated and how it influences consumers’ purchase decisions at retail outlets. A unique aspect of the WOM effect is the presence of a positive feedback mechanism between WOM and retail sales. We characterize the process through a dynamic simultaneous equation system, in which we separate the effect of online WOM as both a precursor to and an outcome of retail sales. We apply our approach to the movie industry, showing that both a movie's box office revenue and WOM valence significantly influence WOM volume. WOM volume in turn leads to higher box office performance. This positive feedback mechanism highlights the importance of WOM in generating and sustaining retail revenue.     

Does Online Information Drive Offline Revenues?: Only for Specific Products and Consumer Segments!

While many offline retailers have developed informational websites that offer information on products and prices, the key question for such informational websites is whether they can increase revenues via web-to-store shopping. The current paper draws on the information search literature to specify and test hypotheses regarding the offline revenue impact of adding an informational website. Explicitly considering marketing efforts, a latent class model distinguishes consumer segments with different short-term revenue effects, while a Vector Autoregressive model on these segments reveals different long-term marketing response.We find that the offline revenue impact of the informational website critically depends on the product category and customer segment. The lower online search costs are especially beneficial for sensory products and for customers distant from the store. Moreover, offline revenues increase most for customers with high web visit frequency. We find that customers in some segments buy more and more expensive products, suggesting that online search and offline purchases are complements. In contrast, customers in a particular segment reduce their shopping trips, suggesting their online activities partially substitute for experiential shopping in the physical store. Hence, offline retailers should use specific online activities to target specific product categories and customer segments.     

The role of accounting information in revenue management

Revenue management (RM) uses differential pricing and other techniques to manage customer demand for a company's products and services. It judiciously trades off yield and spoilage, and brings rational approaches to pricing for goods and services with a limited shelf life. Because many types of businesses find that growing revenue has a disproportionate impact on operating profits, firms that know and manage their customer base often achieve better bottom-line results by growing revenue rather than by cost-cutting. Initially developed as a marketing tool for pricing airline tickets, today's numerous RM applications can benefit from accounting tools that help assess whether applications will enhance operating profit and monitor their success in doing so. Knowledge of a firm's cost structure, operating leverage in particular, and when to treat RM adjustments as special orders, are the principal accounting lynchpins. Opportunity cost variances and insights from the theory of constraints contribute to effective revenue management/profit enhancement programs. Use of proper accounting information and analytic techniques can help a tolerated union of necessity between RM programs and firm strategy become a desirable marriage of mutual choice.     

The Internet of Things (IoT) in retail: Bridging supply and demand

A sales channel serves two primary functions: delivering information and products to customers. Omnichannel retailing allows for the decoupling of these two functions as consumers can learn about products through channels that differ from those used to purchase them. This separation requires a sophisticated inventory and supply chain operation, as well as integration of all customer touchpoints, in order to match fast-moving supply and demand. The Internet of Things (IoT) can play a fundamental role in channel integration because it allows companies to rebalance supply and demand. We classify IoT initiatives on an opportunity map, presenting a strategic framework that distinguishes initiatives by the value they create and by their major area of impact. We justify the adoption of IoT in terms of its enabling capabilities—those immediately realized by deploying IoT sensor data—but its true potential resides in its enhancing capabilities—unanticipated benefits following IoT adoption—at the intersection of supply and demand.     

Apparel acquisition via single vs. multiple channels: College students’ perspectives in the US and China

Drawing on both the diffusion of innovation and market channel literature, this study compared college students from China and the US regarding predictors of channel choice. Moreover, the research identified barriers impeding use of non-store channels. Logistic regression analyses indicated that intention to use multiple channels is positively related to convenience orientation and Internet connectivity in the Chinese sample, and negatively related to age in the US sample. Content analysis revealed the primary barrier to catalog shopping was that respondents could not see how clothing looked in three dimensions; for Internet shopping, it was the difficulty in assessing clothing quality.     

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.     

“One-deal-fits-all?” On Category Sales Promotion Effectiveness in Smaller versus Larger Supermarkets

Even within a store chain and format, supermarket outlets often exhibit substantial differences in selling surface. For chain managers, this raises the issue of correctly anticipating the promotion lift, and of profitably managing promotion activities, across these outlets. In this paper, we conceptualize why and how store size influences the category sales effectiveness of four promotional indicators (depth of the promotional discount, display support, feature support, and whether the promotion is quantity-based). We then estimate the net moderating effect on four product categories for 103 store outlets belonging to four chains. For each of the promotion instruments, we find the percentage sales increases to be lower in large stores. For instance, whereas a 10% point increase in feature activity enhances category sales by about 1.64% in a 700 m² store, this figure drops to only 1.03% in a 1300 m² store – a 59% reduction. This moderating effect is especially pronounced for discount depth, the relative sales lift from a typical price cut being about 78% lower in the larger-sized outlet. However, since large outlets also have larger base sales, the picture changes when we consider absolute sales effects. The net outcome is that deeper discounts or quantity-based promotions do not systematically generate larger or smaller absolute sales bumps in large stores, whereas for in-store displays and features, we obtain a clear positive (be it less than proportional) link between store size and absolute category sales lift. When it comes to margin implications, we show that large stores gain higher profit from price cuts than small outlets only as long as the retailer keeps part of the manufacturer discount to himself. Managers can use these insights to improve their promotional forecasts across outlets, as well as to tailor their mix of instruments to store selling surface.