George Balabanis and Vangelis Souitaris

Introduction

Why is differentiation important in online environments? The virtual absence of switching barriers on the Internet allows consumers to compare various offerings and --with few clicks of the mouse-- to switch to firms that offer better value through differentiated features³. For example (among other factors) differentiation in terms of education of the customers in how to get the most benefit from the service (customer care) and coaching of how to reduce the time and efficiency of transaction (convenience) made a difference between the success of e-grocery stores such as Tesco and Ocado in Britain and the failure of Webvan, Streamline and HomeGrocer in the US ⁴.

Furthermore, market scope (i.e. the market extent to which products or services are offered) is extremely important in online environments. Evolving Internet technology is the ideal tool to serve present-day fragmented consumer markets,⁵ as it allows firms to track individual customers every time they visit a site and subsequently focus their offerings to the specific needs of individual segments⁶. Kim and his colleagues (see note 5) stressed that “….focus is a necessary condition for a successful e-business competitive strategy”. The identification of online consumer segments was highlighted as one the important and necessary avenues of research in the field of e-commerce ⁷.

In practice, many retailers currently work with marketing agencies which use standard geodemographic classifications (for example Acorn and Mosaic) or behavioural segmentations (for example recent years has seen the introduction of E-Types by CACI and Onliners from Acxiom both intended to identify different types of Internet usage). Tesco for instance has aligned a handful of bespoke behavioural segments. However, analysts accept that these commercial systems have limitations. They cope well with the hard factors, such as product usage, but they don’t capture so well the ‘benefits’ for the customer. That is the hardest area to segment – why a person is likely to choose a provider.⁸ In the literature too there seems to be a consensus that of all the available approaches, benefit segmentation is the most strategically meaningful and actionable approach.⁹ Benefit segmentation categorizes consumers on the basis of common motivations to purchase a product or service.¹⁰ Hence, in the context of retailing, which is the focus of this paper, we define market scope using benefit segmentation, which requires an understanding of consumers’ motivations to shop online as well as the benefits they seek from online retailers.

Although firms can pursue differentiation strategies without market segmentation, differentiation is usually a necessary accompaniment of market segmentation. Dickson and Ginter¹¹ concluded that “a strategy of segment development is feasible only when product differentiation either already exists or is an accompanying strategy. Within this framework, product differentiation and market segmentation are clearly not alternative management strategies. A product differentiation strategy can be pursued with or without a market segmentation strategy, but [not vice versa].”

Existing research have demonstrated that differentiation and market focus strategies (when considered separately) have positive effect on performance¹². This study extends our knowledge, being novel in two respects:

a) Our focus is on the under-researched issue of interaction between differentiation and market scope strategies and their combined effect on performance.

b) Differentiation and scope strategies are seen from a ‘demand-driven’ perspective (a methodological novelty). We look at firm strategy as perceived by the customer (conducting a consumer survey) rather than adopting the common ‘supply-driven’ perspective, which looks at strategy from the company’s point of view. Differentiation has strategic importance only when it exists in the mind of the customer, in terms of some perceived characteristic of the product that adds value for the user. Moreover, market scope should reflect the ‘market that exists out there’ rather than the one in the collective mind of the organisation ¹³.

We also adopt a demand-driven perspective in the selection of the performance variable. In contrast to existing supply-driven research, which routinely uses profitability as the criterion variable, we examine the effects of differentiation and scope on the intermediate and more actionable performance goals of customer satisfaction and loyalty. Building customer loyalty in is an important driver of sustainable profitability and growth. For example, a 5% decrease in customer defection was found to increase profitability by 25% to 95%. ¹⁴ Customer satisfaction is one of the most important determinants of loyalty, and influences performance through positive word-of-mouth-customer acquisition.

Overall we depart from a recent paper by Wirtz and Lihotzky in this journal, ¹⁵ who used a supplier-driven perspective to illustrate how to tailor ‘retention’ strategies to different business models, and then called for research from a demand-driven perspective to prove the effectiveness of strategies (which is our research angle). ¹⁶ The main objective of the study is to examine the interaction between differentiation and scope and their influence on satisfaction and loyalty from a demand-driven perspective. The focus is in one industry sector (online grocery retailing) in order to remove the influence of industry effects that may confuse the examined relationships. We intend to contribute to the existing literature on Internet strategy by bringing together strategies of differentiation and scope. We also intend to offer practical implications for e-tailers on how to define the market scope of their strategies and differentiate their offerings accordingly.

The paper is structured in three sections. First, the relevant literature on benefit segmentation of online shoppers, as well as differentiation that can increase satisfaction and loyalty, is discussed. A set of hypothesis linking the three is developed. Second, the research design employed and measurement used is explained. Finally, the results and their implications are discussed.


Literature Review

Defining scope-benefit segmentation of online shoppers

Benefit segmentation of shoppers in general, and online shoppers in particular, by definition should start with the unveiling of the heterogenous motivations to shop. Motivation is the best way to explain shoppers’ reactions to the market place and shopping behavior in general, and is subsequently manipulated to develop appropriate strategies.¹⁷ Past research on shopping motivation (that departs to a certain extent from mainstream consumption and buying motivation theories) is influenced by the work of Tauber. ¹⁸ He argued that it is important to make a distinction between shopping, buying and consuming and between their underlying behavioural determinants. This opens up a new theoretical sub-field, which is shopping motivation. Tauber envisioned that retail innovations (vending machines in his age) that aim to reduce the “shopping effort” may not be as successful in the marketplace because the shopping process may offer more benefits than mere exposure to products. He identified two broad categories of shopping motives: personal and social. Personal motives include enactment of a culturally prescribed role, diversion from daily routine, provision of self-gratification, learning about new trends, obtaining physical activity, and receiving sensory stimulation from the retail environment. Social motives, on the other hand, include social interaction (meeting friends, making acquaintances, people-watching), communication with others who have similar interests, associating with reference or aspiration groups, gaining a feeling of higher status and authority, and the pleasure of bargaining and negotiating. Based on Tauber’s work, Westbrook and Black condensed shopping motivations into seven dimensions (anticipated utility, role enactment, negotiation, choice optimisation, affiliation, power and authority and stimulation) and then identified six motivation-based benefit segments that did not display any demographic differences. ¹⁹

In a recent study, Rohm and Swaminathan utilised shopping motives (collated from past research in conventional shopping) as a motivation base to explain the propensity to buy online versus off-line.²⁰ Studying a mixed sample of on-line and off-line shoppers, they identified four general types of segments: convenience shoppers, variety seekers, balanced buyers (moderately motivated by both convenience and variety-seeking), and store-oriented shoppers (seeking immediate possession and social interaction). Their results showed that variety-seeking and balanced shoppers are the most likely to shop online, whereas store-oriented shoppers were the least likely to shop on the Internet. More interestingly, they found that different shopping groups tend to buy certain product categories online, but not others.

Wolfinbarger and Gilly were the first to look specifically at motivation of on-line shoppers.²¹ They conceptually proposed two types of online shoppers: goal-oriented and experiential e-shoppers. Goal-oriented shoppers, who represent the largest segment, are motivated by convenience, selection, information and lack of sociality. In their words, “goal oriented shoppers achieve freedom and control and lack of commitment in the online environment, as they experience little pressure to purchase before they are absolutely ready.” On the other hand, experiential shoppers’ main motives are recreation and experience. Experiential shopping is associated with surprise, uniqueness, positive sociality, deals and involvement with a product class.

In general, past research has identified an extensive number of motivations for offline shopping. A potential problem is that most of the latest work that involves also on-line shoppers is based or replicates to some extent, motivation research conducted 30 years ago. In our view, Wolfinbarger and Gilly’s shopping motivation scheme is the most relevant for our study, as it is based exclusively on observation of online shoppers without the potential risk of being contaminated by unproven inferences that online shoppers have similar motivations as conventional shoppers. Therefore, their conceptual distinction between goal-oriented and experiential shopping, based on difference in motives, will assist our hypothesis development and be used as a base to define scope in the online shopping environment.
Differentiation strategies that can increase satisfaction and loyalty in retailing

Online retailers can differentiate themselves on a number of ways. However, not every differentiation has an impact on performance or is perceived as valuable by customers. Thus, it is important to focus on differentiation strategies that can actually provide an advantage to the firm by increasing satisfaction and loyalty. To understand differentiation, we need first to understand the relevant criterion variables, customer loyalty and satisfaction.

The existing literature has identified two categories of loyalty: behavioural (i.e. repurchase probability) and attitudinal loyalty. A behavioural definition may be problematic as it does not make a distinction between true loyalty and spurious loyalty (i.e., loyalty that may result from a lack of available alternative products or high switching barriers). Attitudinal definitions of loyalty can address this problem. Thus, loyalty is defined as "a deeply held commitment to rebuy or repatronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior." ²²

In summary, e-loyalty represents a customer’s favourable attitude toward the e-retailer, which results in repeat buying behaviour. Loyalty is closely related to satisfaction. Oliver defines satisfaction as the “consumer’s sense that consumption provides outcomes against a standard of pleasure versus displeasure.” In general, loyalty necessitates satisfaction, but satisfaction does not always lead to loyalty. It appears that switching barriers can moderate this relationship. ²³ In online environments, this relationship was also found to be moderated by consumer characteristics (like convenience motivation) and attributes of the e-tailers (e.g. perceived value and trust). ²⁴

There exist a variety of models that examine the relationship between loyalty, satisfaction and differentiation strategies in retailing.²⁵ Despite some recent evidence suggesting that ‘brick and mortar’ models of loyalty also apply to online environments, ²⁶ a stream of research has conceptually modeled satisfaction and loyalty antecedents in an online context. Szymanski and Hise ²⁷ argued that online convenience, merchandising, site design, and financial security are the main determinants of e-satisfaction. In a more comprehensive model, Gommans et al ²⁸ identified five broad categories of differentiators that affect e-loyalty: (1) value proposition (customized products, large set of choices, product quality, guarantees, well-known brands, and pricing); (2) brand building (brand image building and community building); (3) trust & security (trust, third-party approval, privacy, reputation, reliability, authentication and non-repudiation); (4) customer service (fast response to customer inquiries, ease of contact, free online applications, easy payment methods, fast delivery; delivery options; customer reward system); and (5) website & technology (fast page loads, easy to navigate/browse, personalized website features, language options, effective search functions, server reliability, content, and quick shopping checkout processes). Similarly, Smith’s model ²⁹ indicated that web site usability, features and benefits, purchase process, service, support, dialogue and relationships are the most important differentiators that affect e-satisfaction and subsequently e- loyalty.

In contrast, to the previous conceptual studies, Srinivasan et al ³⁰ provided empirical evidence that eight key online retail differentiation strategies (dubbed the 8Cs) influence e-loyalty: (1) Customisation - tailoring the web environment to the customer; (2) Contact interactivity - the ability to interact dynamically with the customer; (3) Cultivation - the extent to which the e-tailer provides relevant information and incentives; (4) Care - the attention paid to pre and post purchase activities; (5) Community - the social environment facilitated by the e-tailer; (6) Choice- the degree of choice offered; and (7) Character - the creativity of the website.

All of the above factors, except convenience, were found to affect e-loyalty. In addition, Sirohi et al ³¹ found that the quality of the stocked items as well as value for money perception were found to have an important impact on store loyalty.
Hypotheses development

As aforementioned, there exists a disconnection between the two streams of literatures (i.e., benefit segmentation based on shopping motivation, and the differentiation strategies that can increase loyalty and satisfaction). The latter focuses on differentiation strategies that impact all types of customers (i.e., broad scope), ³² whereas the former does not really specify the mechanism through which satisfaction or loyalty is created within the shopper segments. ³³ This study will try to unite these two streams of research by examining the effect of online differentiation strategies on the satisfaction and loyalty of benefit segments of shoppers. Our conceptual framework is shown in Figure 1, and its development is explained below.