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Online shopping in digital stores and shopping in brick-and-mortar stores offer different forms of experiences. It starts from the environment or setting in which the shopper is situated — being present in a 3D physical retail space or viewing a 2D screen of a computer or mobile device. It is the difference between how much and what specifically a shopper can see and absorb when looking around in a physical store compared with looking at a screen. The difference in setting may have a further impact on behaviour, like how shoppers find products and how they inspect them.

Imagine a shopper, Dan, entering a large fashion store. Dan’s head immediately turns around as much as 180 degrees scanning the scene. Just a few steps in front of Dan there is a low desk with shirts, and another desk with sweaters to the left; to the right Dan observes shirts hanging on a rectangle-shaped stand, and he notices how their designs differ from those on the desk; along the walls are more shirts and trousers, etc. Dan decides to approach first the shirts to the left because they have multiple colours, lifting one or two to look more closely at them; later he also turns to the wall to see trousers and tries to match them with shirts. As Dan’s shopping trip advances he may enter deeper into the store to check on some accessories or another variety of shirts. Very early in the visit the shopper can figure out what may be found in main sections of the scene. Then starts a sort of discovery tour that may be guided by a master goal but progresses as the shopper identifies relevant and visually attractive items (stimuli). The scene is ‘updated’ as the shopper goes deeper into the store, or into adjacent halls, and details that were more distant and vague before become sharper and clearer.

A different kind of shopping process usually occurs in online website stores: first of all because much fewer products (stimuli) can be observed in a relatively short glimpse of the screen-scene. The way merchandise in the online store is located and explored is much more gradual.  An online store actually encourages a more goal-driven search process (e.g., choosing names of categories from a menu, selecting attribute options to narrow down the search to a relevant selection of products). Then starts a back-and-forth process of exploration of different items (e.g., by clicking on item titles or images and entering product pages), and visiting additional major categories of products. However, the experience of search and exploration is so different: whereas in the physical store the shopper can ‘wash the eyes’ with shapes, designs and colours of products, and follow the eyes through the shopping trip, it is much harder to do so in an online store where one has to go step-by-step or in a piecemeal manner. Nevertheless, online shoppers have more flexibility and a wider span of possibilities for viewing product options simultaneously on the screen of a desktop or laptop computer than on the screen of a smartphone.

Certainly there are more clever and creative e-commerce or store websites that are able to generate an improved experience of exploration and inspection of products. For example, there are online stores that show grids composed of tiles of images representing major categories and sub-categories of products. The images are more lively, and some of them exhibit motion as well. With some images, hovering with a mouse on the product photo (before clicking) changes the angle in which a garment or handbag, for instance, is shown. On product pages, some options may be selected that immediately affect the product image (e.g., colours, dimensions, designs); products may be rotated dynamically or by selecting from a line of static thumbnail images under the main frame.

A large majority of shoppers enquire about products online before visiting a physical store. According to a Google/Ipsos survey (‘Omnichannel Holiday Study’, Nov. 2017-Jan. 2018), 78% of US holiday shoppers searched products before going into a store; the online search helps shoppers in planning their shopping trip to the store, narrow down the options they should be seeking at the store, but it also ‘inspires the purchase’ (thinkwithgoogle.com, October 2018). In another research by Publicis (‘Shopper First Retailing’, 2018), an even higher proportion of shoppers, 87%, report that they begin searches in digital channels (online, mobile), up from 71% in 2017 (RetailDive.com, 15 August 2018). Searching the Internet is regarded as a productive method to look for directions and learning about product options, as preparation for making purchase decisions. Shoppers do not feel obliged also to make the purchase online, even if they browse the e-commerce website of an online-only retailer (‘e-tailers’) or of a mixed retailer that operates both a website store and physical stores. Consumers like especially to consult reviews of peer users who have already had experience with products they consider.

This learning process seems functional and goal-driven where shoppers need some guidance to put order into their shopping journey. Online sources, including e-commerce websites, seem to provide an efficient solution for this purpose. The process may indeed inspire shoppers with ideas, perhaps to the extent of helping the shopper to focus on viable and worthwhile purchase options and avoid wandering too long clueless in a store. In such a case in particular, visiting the online store of a mixed retailer can prove most useful before arriving to one of its physical store locations — and this makes the website an even more effective tool for the retailer.

However, retailers that operate physical stores would not want shoppers to come too prepared with their minds pre-determined what to buy. While shoppers usually have a general plan of what they are looking for, final purchase decisions are still made mostly in-store. Hence it is so important for physical stores to be designed and arranged in an appealing and stimulating manner — to allow consumers to complete successfully their shopping trip in-store, and furthermore encourage and induce them to purchase a few more ‘treasures’ they discover in the store.

It may be relevant to consider here two scenarios:

For retailers that operate physical stores in multiple, even numerous locations, there should be a stronger incentive to leave their customers with enough reasons to conclude their shopping in-store rather than on the website store. Thus, the online store has to be visually attractive, user-friendly and informative, but it does not have to be fully equipped with features that convince customers to complete their shopping and purchasing online. The website should not go all the way in effort to draw shoppers from physical stores. Whereas the online store may provide more functional, productive experiences (e.g., efficient, time-saving), the physical store would be more capable in creating pleasant emotional experiences (e.g., excitement, thrill, joy). The positive emotions invoked should not be taken lightly because they drive purchases.

For e-tailers with no physical stores there should be greater need to invest in the quality and feel of experiences they can provide in their e-commerce websites. The introduction of shoppers to the online store should be more delightful as well as informative and user-friendly. Visual elements and interactive features have to be inviting and helpful in guiding the visitor into different sections of the store — on the ‘main stage’ of the screen estate and not just through the menu and search engine.

The latter applies, nonetheless, also to mixed retailers that have stores in just a few locations (e.g., major cities) and wish to reach much greater numbers of customers that do not have a store near them. It may also be relevant when targeting customer segments who for any reason have little time free to travel to a store, and in regions where shoppers are reluctant to go out during harsh weather conditions (e.g., steaming hot and dusty or freezing cold and snowy). [Note: Location data might be used to channel a reduced or enhanced version of a store website according to whether the user is in vicinity of a physical store by the retailer, a form of ‘geo-fencing’].

Delicatessen in Gstaad

The brick-and-mortar stores remain very much in demand. According to a Google/Ipsos online survey (‘Shopping Tracker’, US, April-June 2018), 61% of American shoppers prefer shopping with brands that also have physical stores than ones that are online only. Key benefits suggested for shopping in physical stores are the immediacy in which shoppers are likely to obtain the products they require; getting hands-on — seeing and interacting with products before buying; and being more fun than shopping online (35% feel so) (thinkwithgoogle.com, John McAteer, November 2018). The Publicis study indicates more generally that 46% of shoppers prefer to buy in physical stores (vis-à-vis 35% who prefer shopping using their laptops and 18% on mobile phones) (RetailDive). Apparently, shoppers are not blind to benefits and advantages of shopping in physical stores over online stores, and many are not ready to leave them to fade out.

It is not suggested that online stores necessarily have to be made to appear like physical stores on the screen — mimicking the scene of a brick-and-mortar store may be perceived as just artificial, awkward and inconvenient (though retailers who also have physical locations can integrate actual store images into relevant sections of the online store). On the one hand, the retailer (or e-tailer) should take advantage of the strengths of the digital medium in organising, displaying and tracing information in the online store. On the other hand, online stores may have to breakaway in some degree from rigid structures of tables, lists and matrices. Grids of image tiles make a good start. Yet, more versatile visualisation possibilities have to be considered to provide visitors of store websites (or mobile apps) a more stimulating presentation of the variety of products the store has to offer. The interactive presentation should expose visitors to an array of products available (e.g., by type, use purpose, or brand), and lead their way from there into sub-categories and specific product models or brands.

  • Virtual Reality (VR) technology may be used to emulate a view of a store in 3D space, but the equipment needed to create a truly compelling experience is not in reach of most consumers, at least not yet. The more crucial question is: why should consumers prefer an imitation or illusion when almost everyone can visit real physical stores and shops. At least one aspect VR is unlikely to provide adequately is the social experience.

Instead of treating online shopping and shopping in physical stores as substitutes competing with each other, the more sensible approach for mixed retailers is to create ways in which they can combine and complement each other. The connection can be a two-way street, especially given that shoppers use mobile devices more frequently during store visits (71% of shoppers according to Publicis study cited by RetailDive). From online to store, for example, a mobile app of the retailer used in-store can help the shopper navigate and find the way to the places of products that he or she detected and learned about in a preliminary search and study online (e.g., Home Depot). From in-store to online, the shopper may use the app of the retailer in-store to find more information about products found in the store by scanning a barcode for the product of interest (e.g., Sephora [cosmetics] allows access to product reviews, order history of the shopper, and more) [examples adopted from McAteer in thinkwithgoogle]. More technologies that help in bridging between the virtual and physical domains of shopping include beacons and augmented reality (AR).

  • There are other areas not covered above in which online shopping is distinguished from in-store shopping and require more attention, such as customer service, specifically providing advice and assistance to shoppers, and the fulfillment of orders (a ‘click-and-collect’ programme is another way of linking the physical and online stores).

The physical and digital (virtual) domains have each their strengths in creating different forms of shopping experiences. Physical stores and shops have built-in advantages in evoking emotional experiences while shopping — they are tangible and more direct, can provide good personal care, and may attract and excite shoppers by means of interior design and visual merchandising in their physical spaces. Furthermore, beyond vision, physical stores allow shoppers to enact other senses (e.g., touch, smell) that cannot be experienced in the digital domain. It is unsure how much a store website (or app) can give rise to a similar emotional experience and attachment in shoppers, yet there are aspects that can be borrowed into the digital domain that would make it seem not just functional but also more appealing and immersive. Nonetheless, mixed retailers may have the best opportunity to combine the strengths from the physical and digital domains and link them to produce shopping experiences that are more productive and enjoyable altogether.

Ron Ventura, Ph.D. (Marketing)

 

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Consumers like to talk about the brands in their lives. Brands may be connected to their personal history or to a narrative which describes their current lifestyle; people can tell others about a variety of brand experiences they have had, for better or worse. Consumers use likewise word-of-mouth information they receive from friends and relatives, but not only from them. They refer to product reviews, user-generated blogs, as well as stories, opinions and suggestions conveyed in forums of digital social networks from people they may not know so well but consider convincing or trustworthy. The proliferation of user-generated content through Web 2.0 and mobile applications did a great deal to facilitate the spread of word-of-mouth (WOM) and increase consumer reliance on this type of information. However, it does not preclude the still dominant transfer of brand-related WOM offline between people more closely connected in face-to-face meetings and phone conversations.

But brands do not exert WOM to the same extent. Some brands get more of such informal publicity than others. The question thence becomes: What characteristics of a brand make it more interesting, important or relevant to consumers to talk about with friends, family and others? In such discourse consumers could be mainly in the role of providers or receivers of information, and they may share personal experiences, viewpoints, and recommendations, or conversely warnings, regarding any brand.

Researchers Lovett, Peres, and Shachar (2013) took the challenge of investigating the relations of brand characteristics to stimulation of WOM shared among consumers, and they offer some interesting insights, especially on the differences between offline and online channels. At start, it should be clarified that drivers for engaging in WOM are originated in the consumers for satisfying their personal needs; the brand characteristics may be seen as operational instruments that link with the drivers that stimulate brand-related WOM. The researchers identify three main drivers in their guiding theoretical framework:

  • Social driver — Concerned with a need of consumers to express themselves to others, showing their uniqueness, for self-enhancement, and out of desire to socialize with others;
  • Emotional driver — Associated with excitement and pleasure of satisfaction (emotional sharing);
  • Functional driver — Related to the need to obtain information and the tendency to provide information to others, moderated by aspects such as complexity and knowledge.

The researchers collated information on over six hundred US national brands of products and services as well as corporate and retailer names (covering the period of 2008-2010). The brands spanned across 16 broad product categories (e.g., beverages, children’s’ products, clothing, department stores, cars, media and entertainment).

  • Data sources on brand characteristics included a consumer survey in the US (primary source) and several datasets of proprietary research programmes (secondary sources), the major of them is the Young and Rubicam Brand Asset Valuator (characteristics corresponding to brand equity “pillars”:  Differentiation, Relevance, Esteem, and Knowledge).
  • The level of WOM generated about a brand (operated as count of mentions of a brand) was modelled and analysed separately in offline conversations and online settings or forums. Data of brand mentions in face-to-face and in phone conversations were obtained from the TalkTrack project of Keller and Fay (a diary-based survey) whereas data on online WOM were adopted from the Nielsen McKinsey Incite tool (a search engine that can retrieve brand mentions in settings such as discussions groups, blogs and microblogs). [The count of brand mentions was modelled under the assumption that it follows a Negative-Binomial distribution.]

We will take here a quick look at results and insights from the research that I find the more revealing and interesting, with an emphasis on distinctions between offline and online channels:

The Social Driver — A brand that is better differentiated from competitors can make an easier and more effective vehicle for a consumer to express his or her own uniqueness to others. Greater brand differentiation contributes to more brand mentions offline and online. Yet, the positive effect on WOM online is stronger. There could be greater motivation for consumers to utilise brands for highlighting their uniqueness when communicating online because they can address much larger audiences than offline, and a reference to the relevant brand can efficiently deliver the message, particularly when cues of visual appearance or sound cannot be used. Brand differentiation is a newly studied characteristic in relation to WOM in this research project.

The volume of brand WOM also increases with higher perceived quality of the brand’s products, and is larger for more prestigious, premium brands. Associating with brands of higher quality products (represented by Esteem) can serve to demonstrate the consumer’s expertise in a category — it has a positive effect on WOM offline and online, but the effect online is twice as large.  A premium brand characterization, that reflects a higher social status, has a significant effect only in an online channel. Enhancing one’s self-image through expertise or social status, as with highlighting personal uniqueness, is possibly felt more needed by consumers in the less intimate interactions that take place online with people whom they are less familiar with than those they interact with face-to-face or on the phone. A consumer may have more to “prove” to or impress “friends” who are known primarily and even solely as members in his or her virtual social network.

The Emotional Driver — Being excited about a brand seems as a very plausible motive to arouse consumers to talk about it. Lovett and his colleagues indicate that excitement, a brand personality trait, has not been studied yet in the context of WOM.  As expected, brands that evoke more excitement lead consumers to engage more in WOM about the brand, both offline and online. While the effects of excitement are similar between the channels, there is a distinction between them, as addressed below, with respect to the emotional driver in general.

The researchers expected that a higher level of WOM would be generated when satisfaction with a brand is very high or very low. Their model results showed, however, that only very low satisfaction yields a peak in WOM, and that as satisfaction rises the level of WOM drops (i.e., a relationship described by a monotonic descending concave curve). The finding that very low satisfaction induces consumers to talk (critically) more about a brand is frequently supported in other studies.

  • The proposition about the effect of very high satisfaction may have not been supported, according to the researchers, because it has confounded with the effects of esteem and excitement included in their model and not in previous research. But one cannot ignore that the dataset included satisfaction scores for just a third of the brands analysed, as reported, and scores for the remaining 2/3 of brands with missing data were imputed based on the distribution of the available scores. Consequently, it is hard to conclude based on the evidence whether the effect of high satisfaction indeed exists.

The Functional Driver — This driver has two dimensions: obtaining information and providing information through WOM. Consumers often require assistance when learning complex product information (e.g., prior to purchase) or dealing with complex technical details and instructions (e.g., for correct product utilisation). Complexity matters primarily to those who wish to obtain information. This research reveals that greater complexity is related to more brand mentions only in offline conversations. That is, more immediate, direct and intimate interactions offline between consumers are adopted as more suitable for discussing together and clarifying information that is complex and more difficult to comprehend about products. It may be added that such conversations are also more likely to be held between consumers who know each other better, and that allows for a better flow of interaction. Less complex information can be obtained from online forums. Online conversations, as the authors argue, tend to be asynchronous, and entail longer delays in responding to questions that may hinder clarification of confusing matters and information exchange. Complexity is another characteristic included in this study yet not in previous research in the context of WOM.

Interestingly, consumers also engage more in WOM on younger (i.e., newer) brands when communicating offline but not online —  brands possibly perceived as innovative, intriguing, exciting or still ambiguous appear also to be more appropriate to talk about in person.

From the perspective of those who provide information, producing and disseminating WOM on brands would depend on how knowledgable consumers feel they are on the subject.  The results confirm that brands that are perceived to be more familiar to consumers and better known are more likely to be talked about, similarly offline and online.

The researchers further extracted and compared the relative importance of each main driver between the two settings of offline and online channels. The social driver is the most important stimulant of online WOM followed by the functional and lastly the emotional driver. In contrast, in offline conversations the emotional driver is the most important, followed by the functional driver, and relatively the least important driver is social. Notably, while the emotional driver has a positive effect in both types of channels, it is more prominent in driving brand mentions in conversations offline. These differences exemplify the difference in nature between offline and online interactions — offline interactions are more intimate and open between people, more accommodating to share excitement and satisfaction, whereas online interactions are less personal, tend to promote “broadcasting” information to many people and social signalling with verbal cues.

  • The different nature of offline and online channels may also be evident in an almost complete separation between lists of leading brands (top 1o) in number of their brand mentions between those two settings: Offline we find Coca-Cola, Verizon, Pepsi, Wal-Mart, Ford, AT&T, McDonald’s, Dell Computers, Sony, and Chevrolet. Online, on the other hand, arrived on top the brands of Google, Facebook, iPhone, YouTube, Ebay, Ford, Yahoo, Disney, and Audi. Only Ford is on both lists. The contrast between “new” and “old” or “physical” and “virtual” brands speaks for itself.

The models furthermore demonstrate the positive role of brand equity in encouraging consumers to talk more about a brand. Stronger brands — more encompassing in their areas of activity and influencing many more people — command more conversation (e.g., information exchange and sharing opinions). First, we may recognize an implicit effect of brand equity on WOM through factors represented in the models such as perceived quality, differentiation, knowledge, and visibility that contribute to enhancing the equity of a brand. Second, nonetheless, the researchers included in their two models a control variable of brand equity, represented as the inclusion of brands in the list of 100 top brands constructed by Interbrand. It is thereby confirmed that brands on this list enjoy higher WOM. One should keep in mind, however, that being more frequently the subject of conversation, offline or online, is evidence of greater importance and relevance of a brand, and in turn may increase its equity further, when WOM is positive, but may also decrease its equity when the WOM is negative.

The authors acknowledge some limits of their research. In particular: (1) The brands included are the most talked about in the US (i.e., covering reduced variation in level of WOM over brands); (2) The models refer to “offline” and “online” in wholesome as types of channels — more research is needed to investigate effects on WOM in separate online spaces like the blogosphere and social media networks; (3) Since the units of information are brands rather than individual consumers, the ability to describe and explain the processes in which consumers exchange, produce or obtain WOM information on  brands is impaired, inviting more research in this respect.

Marketing communication managers may use the results (effect estimates) and insights from these models of WOM to identify characteristics of brands in their responsibility that can be expected to yield more WOM and learn of gaps between actual and expected levels of WOM when planning where and how to invest their effort for evoking more WOM on their brands. However, it is most important for marketers, as Lovett, Peres, and Shachar stress in their article, to keep offline and online channels distinguished and plan their measures for each environment separately — what may work well in an online environment can prove ineffective offline, and vice versa. In each environment it is necessary to emphasise different aspects and goals and take appropriate measures.

Ron Ventura, Ph.D. (Marketing)

Reference:

On Brands and Word-of-Mouth; Mitchell Lovett, Renana Peres, & Ron Shachar, 2013; Journal of Marketing Research, 50 (August), pp. 427-444.

The authors won a grand award for their research project in a joint-competition of the Wharton Customer Analytics Initiative and the Marketing Science Institute.

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