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Posts Tagged ‘Segmentation’

Psycographic-oriented research of consumer lifestyles based on surveys for collecting the data is losing favour among marketers and researchers. Descriptors of consumer lifestyles are applied especially for segmentation by means of statistical clustering methods and other approaches (e.g., latent class modelling). Identifying lifestyle segments has been recognized as a strategic instrument for marketing planning because this kind of segmentation has been helpful and insightful in explaining variation in consumer behaviour where “dry” demographic descriptors cannot reach the deeper intricacies. But with the drop in response rates to surveys over the years, even on the Internet, and further problematic issues in consumer responses to survey questionnaires (by interview or self-administered), lifestyle research using psychographic measures is becoming less amenable, and that is regrettable.

The questionnaires required for building lifestyle segmentation models are typically long, using multi-item “batteries” of statements (e.g., response on a disagree-agree scale) and other types of questions. Initially (1970s) psychographics were represented mainly by Activities, Interests and Opinions (AIO). The measures cover a wide span of topics or aspects from home and work, shopping and leisure, to politics, religion and social affairs. But this approach was criticised for lacking a sound theoretical ground to direct the selection of aspects characterising lifestyles that are more important, relevant to and explanatory of consumer behaviour. Researchers have been seeking ever since the 1980s better-founded psychology-driven bases for lifestyle segmentation, particularly social relations among people and sets of values people hold to. The Values and Lifestyles (VALS) model released by the Stanford Research Institute (SRI) in 1992 incorporated motivation and additional areas of psychological traits (VALS is now licensed to Strategic Business Insights). The current version of the American model is based on that same eight-segment typography with some updated modifications necessary to keep with the times (e.g., the rise of advanced-digital technology) — the conceptual model is structured around two prime axes, (a) resources (economic, mental) and (b) motivation or orientation. Scale items corresponding to the AIOs continue to be used but they would be chosen to represent constructs in broader or better-specified contexts.

Yet the challenge holds even for the stronger-established models, how to choose the most essential aspects and obtain a sufficient set of question items consumers are likely to complete answering. Techniques are available for constructing a reduced set of items (e.g., a couple of dozens) for subsequent segmentation studies relying on a common base model, but a relatively large set (e.g., several dozens to a few hundreds of items) would still be needed for building the original model of lifestyle segments. It is a hard challenge considering in particular the functions and limitations of more popular modes of surveys nowadays, online and mobile.

Lifestyles reflect in general the patterns or ways in which people run their ordinary lives while uncovering something of the underlying motives or goals. However,  ‘lifestyles’ have been given various meanings, and researchers follow different interpretations in constructing their questionnaires. The problem may lie in the difficulty to construct a coherent and consensual theory of ‘lifestyles’ that would conform to almost any area (i.e., product and service domain) where consumer behaviour is studied.  This may well explain why lifestyle segmentation research is concentrated more frequently on answering marketing questions with respect to a particular type of product or service (e.g., banking, mobile telecom, fashion, food). It can help to select more effectively the aspects the model should focus on and thereby also reduce the length of the questionnaire. The following are some of the concepts lifestyle models may incorporate and emphasise:

  • Values that are guiding and driving consumers (e.g., collectivism vs. individualism, modernism vs. traditionalism, liberalism vs. conservatism);
  • In the age of Internet and social media consumers develop new customs of handling social relations in the virtual world versus the physical world;
  • In view of the proliferation of digital, Internet and mobile communication technologies and products it is necessary to address differences in consumer orientation and propensity to adopt and use those products (e.g, ‘smart’ products of various sorts);
  • How consumers balance differently between work and home or family and career is a prevailing issue at all times;
  • Lifestyles may be approached through the allocation of time between duties and other activities — for example, how consumers allocate their leisure time between spending it with family, friends or alone (e.g., hobbies, sports, in front of a screen);
  • Explore possible avenues for developing consumer relationships with brands as they integrate them into their everyday way of living (e.g., in reference to a seminal paper by Susan Fournier, 1998)(1);
  • Taking account of aspects of decision-making processes as they may reflect overall on the styles of shopping and purchasing behaviour of consumers (e.g., need for cognition, tendency to process information analytically or holistically, the extent to which consumers search for information before their decision).

Two more issues deserve special attention: 

  1. Lifestyle is often discussed adjacent with personality. On one hand, a personality trait induces a consistent form of response to some shared stimulating conditions in a variety of situations or occasions (e.g., responding logically or angrily in any situation that creates stress or conflict, offering help whenever seeing someone else in distress). Therefore, personality traits can contribute to the model by adding generalisation and stability to segment profiles. On the other hand, since lifestyle aspects describe particular situations and contexts whereas personality traits generalize across them, it is argued that these should not be mixed as clustering variables but may be applied in complementary modules of a segmentation model.
  2. Products that consumers own and use or services they utilize can illustrate  figuratively their type of lifestyle. But including a specific product in the model framework may hamper the researcher’s ability to make later inferences and predictions on consumer behaviour for the same product or a similar one. Therefore, it is advisable to refer carefully to more general types of products distinctively for the purpose of implying or reflecting on a pattern of lifestyle (e.g., smartphones and technology-literacy). Likewise, particular brand names should be mentioned only for an important symbolic meaning (e.g., luxury fashion brands, luxury cars).

Alternative approaches pertain to portray lifestyles yet do not rely on information elicited from consumers wherein they describe themselves; information is collated mostly from secondary databases. Geodemographic models segment and profile neighbourhoods and their households (e.g., PRIZM by Claritas-Nielsen and MOSAIC by Experian). In addition to demographics they also include information on housing, products owned (e.g., home appliances), media used, as well as activities in which consumers may participate. However, marketers are expected, by insinuation, to infer the lifestyle of a household, based, for instance, on appliances or digital products in the house, on newspaper or magazine subscriptions, on clubs (e.g., sports), and on associations that members of the household belong to. Or consider another behavioural approach that is based on clustering and “basket” (associative) analyses of the sets of products purchased by consumers. These models were not originally developed to measure lifestyles. Their descriptors may vicariously indicate a lifestyle of a household (usually not of an individual). They lack any depth in describing and classifying how consumers are managing their lives nor enquiring why they live them that way.

The evolving difficulties in carrying-out surveys are undeniable. Recruiting consumers as respondents and keeping them interested throughout the questionnaire is becoming more effortful, demanding more financial and operational resources and greater ingenuity. Data from surveys may be complemented by data originated from internal and external databases available to marketing researchers to resolve at least part of the problem. A lifestyle questionnaire is usually extended beyond the items related to segmentation variables by further questions for model validation, and for studying how consumers’ attitudes and behaviour in a product domain of interest are linked with their lifestyles. Some of the information collected thus far through the survey from respondents may be obtained from databases, sometimes even more reliably than that based on respondents’ self-reports. One of the applications of geodemographic segmentation models more welcome in this regard is using information on segment membership as a sampling variable for a survey, whereof characteristics from the former model can also be combined with psychographic characteristics from the survey questionnaire in subsequent analyses. There are furthermore better opportunities now to integrate survey-based data with behavioural data from internal customer databases of companies (e.g., CRM) for constructing lifestyle segments of their customers.

Long lifestyle questionnaires are particularly subject to concerns about the risk of respondent drop-out and decreased quality of response data as respondents progress in the questionnaire. The research firm SSI (Survey Sampling International) presented recently in a webinar (February 2015 via Quirk’s) their findings and insights from a continued study on the effects of questionnaire length and fatigue on response quality (see a POV brief here). A main concern, according to the researchers, is that respondents, rather than dropping-out in the middle of an online questionnaire, actually continue but pay less attention to questions and devote less effort answering them, hence decreasing the quality of response data.

Interestingly, SSI finds that respondents who lose interest drop-out mostly by half-way of a questionnaire irrespective of its length, whether it should take ten minutes or thirty minutes to complete. For those who stay, problems may yet arise if fatigue kicks-in and the respondent goes on to answer questions anyway. As explained by SSI, many respondents like to answer online questionnaires; they get into the realm but they may not notice when they become tired or do not feel comfortable to leave before completing the mission, so they simply go on. They may become less accurate, succumb to automatic routines, and give shorter answers to open-end questions. A questionnaire may take forty minutes to answer but in the estimation of SSI’s researchers respondents are likely to become less attentive after twenty minutes. The researchers refer to both online and mobile modes of survey. They also show, for example, the effect of presenting a particular group of questions in different stages of the questionnaire.

SSI suggests in its presentation some techniques for mitigating those data-quality problems. Two of the suggestions are highlighted here: (1) Dividing the full questionnaire into a few modules (e.g., 2-3) so that respondents will be invited to answer each module in a separate session (e.g., a weekly module-session); (2) Insert break-ups in the questionnaire that let respondents loosen attention from the task and rest their minds for a few moments — an intermezzo may serve for a message of appreciation and encouragement to respondents or a short gaming activity.

A different approach, mentioned earlier, aims to facilitate the conduct of many more lifestyle-application studies by (a) building once a core segmentation model in a comprehensive study; (b) performing future application studies for particular products or services using a reduced set of question items for segmentation according to the original core model. This approach is indeed not new. It allows to lower the burden on the core modelling study from questions on product categories and release space for such questions in future studies dedicated to specific products and brands. One type of technique is to derive a fixed subset of questions from the original study that are statistically the best predictors of segment membership. However, a more sophisticated technique that implements tailored (adaptive) interviewing was developed back in the 1990s by the researchers Kamakura and Wedel (2).

  • The original model was built as a latent class model; the tailored “real-time” process selected items for each respondent given his or her previous responses. In a simulated test, the majority of respondents were “presented” with less than ten items; the average was 16 items (22% of the original calibration set).

Lifestyle segmentation studies are likely to require paying greater rewards to participants. But that may not be enough to keep them in the survey. Computer-based “gamification” tools and techniques (e.g., conditioning rewards on progress in the questionnaire, embedding animation on response scales) may help to some extent but they may also raise greater concerns for quality of responses (e.g., answering less seriously, rushing through to collect “prizes”).

The contemporary challenges of conducting lifestyle segmentation research are clear. Nonetheless so should be the advantages and benefits of applying information on consumer lifestyle patterns in marketing and retailing. Lifestyle segmentation is a strategic tool and effort should persist to resolve the methodological problems that surface, combining where necessary and possible psychographic measures with information from other sources.

Ron Ventura, Ph.D. (Marketing)

Notes:

(1) Consumers and Their Brands: Developing Relationship Theory in Consumer Research; Susan Fournier, 1998; Journal of Consumer Research, 34 (March), pp. 343-373

(2) Lifestyle Segmentation With Tailored Interviewing; Wagner A. Kamakura and Michel Wedel, 1995; Journal of Marketing Research, 32 (Aug.), pp. 308-317.

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Consumers often use price information as a cue to infer the quality of products — it is a familiar phenomenon based on the belief that price and quality are positively correlated. Consider for instance  laptop computers: consumers may rely on price to predict the quality of a laptop model for which there is lack of information about attributes that determine its quality, or rather because they have a difficulty to understand the technical features and try to infer the laptop’s expected quality based on its (list) price. Wine is another excellent example for a product whose quality consumers try to assess based on its price. The perceived price-quality relation is not always well-substantiated, which may lead to some costly mistakes. Reliance on price to judge quality is contingent on individual, contextual (e.g., product type) and situational factors.

Consumers may rely on price as an informational cue for different purposes: (a) to reduce the risk of buying a product of an unacceptable low quality; (b) avoid or mitigate effort of evaluating complex product information; (c) anticipate differences in quality between product brands and models (but sometimes also their symbolic meanings associated with prestige and luxury). Price-quality judgements involve two essential steps: estimating the strength of a relationship between price and quality in a focal product category, and applying this judgement to predict the quality of a particular product item (e.g., a new product model). Consumers may differ in their proficiency both to assess the relationship and applying it in various every-day situations.

The magnitude of price-quality correlations varies between product categories, and most consumers are aware of it. However, their calibration of the price-quality relationship for particular product types is often flawed and consumers over-estimate the correlations. Consumers tend to follow a general belief about price-quality relation without properly testing it as a hypothesis in the product category under consideration for purchase; alternately they bias their judgement by considering only evidence consistent with the prior belief (e.g., as the load of information to process is larger and harder to grapple with, and when information is organised in a format that highlights price-quality correlation [1]). Consumers also differ in the first place in their propensity to hold a price-quality belief (i.e., how strongly are consumers price-quality schematic). Capturing the actual reliance on price as a quality cue may also turn to be elusive because applying such a rule depends on the amount and nature of product information available.

In a research recently published (2013) Lalwani and Shavitt study how consumer propensity to perceive a price-quality relationship is governed or moderated by thinking styles and modes of self-construal exerted from consumers’ relations with others in their groups of membership. They distinguish between (1) independents (individualists) who prefer to form their opinions and set personal goals on their own, in hope those will be accepted by their in-group peers but not to be censored by the latter, and (2) interdependents (collectivists) who are inclined to form opinions and set goals that are subordinated to those of the in-group to which they belong. They refer to cultural self-construal by acknowledging that independence has been associated more closely with Western nations or Caucasian societies and interdependence with South and East Asian nations or societies. The distinction is primarily relevant to the construction of price-quality judgements by its correspondence with analytic vs. holistic styles of thinking, respectively. The authors additionally examine specific conditions that may enhance or inhibit the use of price to infer quality.

Analytic thinking orientates to process and evaluate a single piece of information at a time — for example, examine a value for a product item on a specific attribute. The ‘analytic’ consumer may compare between a few models on a specific attribute but ignore any other attributes. In a pictorial image, analytic thinking implies that the individual would look at each object in the image separately rather than inspecting a collection of elements in a scene. Holistic thinking, on the other hand, orientates to observe and evaluate relations between attributes and objects. It is much less focused on single items of information in favour of considering collections of them and how they relate to each other. In a pictorial image, holistic thinking means that an individual more easily identifies combinations of elements and conceives inter-relations between them in the whole scene. The argument put forward, and tested, by Lalwani and Shavitt posits that interdependents (collectivists) who are reliant on their social connections, and who are more considerate of the needs and goals of others in their in-groups before their own, are more predisposed to apply holistic thinking; independents (individualists) who tend to focus on their single-self’s needs and goals before others are more inclined to adopt an analytic style of thinking. Holistic thinking that endorses relational processing is clearly essential for making judgements about a price-quality relationship. The authors are particularly concerned with the boundary conditions under which the advantage of holistic thinking in making price-quality judgements has an impact.

Lalwani and Shavitt take notice that independent and interdependent modes of self-construal are not exclusive of each other, that is, they may be exhibited simultaneously in the same person or within a particular society. Therefore, following previous research, the authors apply two scales, one to measure independence and the other for interdependence as opposed to treating these modes as polar ends of the same continuum. They find that a stronger tendency to perceive a price-quality relationship (a global belief) is predicted by greater inclination for interdependent self-construal. No similar relation is found with independent self-construal. This confirms that only interdependent self-construal may support consumer tendency to rely on a price-quality relationship. [2]

Asians and Hispanic (in the US), representing interdependent self-construals, have been found to utilise price to infer the quality of a “new” target product item (alarm clock) whereas Caucasians (independents) showed no significant sensitivity to differences in price for the target product. It is emphasised that the Asians/Hispanics participants not just considered price-quality information available on “base” items but also practically used price in its evaluation of quality for the target item.

The difference in type of self-construal does not clarify sufficiently how this should lead to differences in approach to the perceived price-quality relationship. That is where the difference between holistic and analytic thinking takes its role. If we look only at the distinction between American nationals and Indian nationals, it would be relatively difficult to understand why the Indians have been found to exhibit a stronger tendency to rely on price as a quality cue. This difference is partially explained (mediated) once the researchers account for a difference in tendency to think holistically — the Indians also have a stronger tendency for that type of thinking that better supports processing of relations between price and quality.

Even more convincing are the results from a study in which an exercise with a pictorial image was conducted to encourage (prime) analytic versus holistic thinking by participants (American Asians/Hispanic vs. Caucasians). As expected, holistic thinking facilitated reliance on price when evaluating the quality of a “new” target product item (calculator) for both Asians/Hispanic and Caucasians. That is, they evaluated the higher priced target brand to be of higher quality than a lower priced brand. Nonetheless, the Asian/Hispanic who are more likely to be ‘interdependent’ differentiated even more strongly the quality between higher- and lower-priced target brands — revealing their advantage for relational processing. In contrast, when both Asians/Hispanic and Caucasians are primed to think analytically, none of them seems to use price as a quality cue. This highlights the power of holistic thinking for making price-quality judgements; vice versa, “imposing” analytic thinking on those who have a stronger tendency for holistic thinking seems to over-ride their advantage in predicting quality based on price.

Lalwani and Shavitt point-out that an advantage for relational processing in using price as a quality cue takes effect in kind of intermediate conditions: when there is a logical basis and supportive evidence (e.g., market conditions, product information available) for relying on price to infer quality, yet neither when conditions are poor/prohibitive nor when evidence of a price-quality relationship is just obvious and applying it is fairly easy. This is demonstrated in two cases: (a) an advantage for relational processing with regard to non-symbolic, functional or practical products (e.g., paper towels) vs. symbolic products that are better able to express one’s identity (e.g., watches, bicycle) — the latter product type induces a price-quality tendency in both ‘independents’ and ‘interdependents’; (b) an advantage for relational processing when information is provided on (non-price) attributes of moderate bandwidth (e.g., quality, durability, reliability), not for broad, generalised evaluations/attitudes (everybody uses price) and not narrow, specific features (nobody uses price). When conditions are sufficient but not too permissive, only those who have the advantage will discriminate products on perceived quality according to price.

The distinction between independent and interdependent self-contrual is somewhat circumstantial with respect to the utilisation of price as a quality cue. It does not immediately make sense why the two behavioural phenomena should be related. References to national and ethnic origins may also be too liberal generalisations that do not contribute enough to our understanding except for exposing the relationship. At the bottom of a distinction between modes of self-construal regarding price-quality judgement underlies the important distinction between holistic and analytic thinking. Lalwani and Shavitt effectively suggest that the extent to which people think in terms of relations between objects or their attributes corresponds with their attitude towards relations with other people, and hence the latter’s connection with the relationship between price and perceived quality. The distinction between thinking styles therefore seems to shed more light on conditions that induce or limit reliance on price as a quality cue.

Yet, establishing a connection between self-construal. particularly represented by national or ethnic (sociocultural) origins, and reliance on price as a quality cue, can be most productive and helpful for segmentation — it facilitates the identification of and access to relevant segments for marketing initiatives associated with the price-perceived quality relationship. The implications may be in devising advertising messages or premium product offering that target consumers with expected greater tendency to make price-quality inferences.  Consequently those consumers would likely be more favourable towards and receptive of higher-priced products/brands. This research further contributes to previous knowledge in the field by suggesting conditions under which most consumers or only selective segments would be evoked to make price-quality judgements. Marketers may consider the breadth of attributes described (broader dimensions vs. features) in addition to the structure of information presented to consumers [e.g., rank-order products by quality vs. random order, [3]).

Source:

You Get What You Pay For? Self-Construal Influences Price-Quality Judgements; Ashok K. Lalwani and Sharon Shavitt, 2013; Journal of Consumer Research, 40 (August), pp. 255-267, DOI:
10.1086/670034

Notes:

[1] A Selective Hypothesis Testing Perspective on Price-Quality Inference and Inference-Based Choice; Maria L. Cronley, Steven S. Posavac, Tracy Meyer, Frank R. Kardes, & James J. Kellaris, 2005; Journal of Consumer Psychology, 15 (2), pp. 159-169

[2]  Statistical Note: The validity of the results of multiple regression analysis performed is contingent on the two scales of individualism-independence and collectivism-interdependence not being negatively correlated. Such evidence is not reported. Turning to the source (Oyserman, 1993) reveals, as logically expected, that some of the statements are in contradiction between the pair of scales. In this case, the version of scales adopted by the authors suggests less conflict and the correlation between them is near zero. On the one hand, it is a little surprising that not even a low negative correlation was found to indicate the contrast between these constructs. On the other hand, a strong negative correlation between the scales could mean that only the stronger predictor, ‘interdependence’, won over the other confounded predictor and thus came out as the single significant predictor.

[3] Ibid. 1.

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The advanced technology of mobile devices — smartphones and tablets — is giving consumers new powers when shopping at brick-and-mortar stores. These devices allow shoppers to obtain useful information in the right place at the right time as well as generate and share information in ways they could only dream of ten or twenty years ago. However, retailers that operate physical stores take special note of a practice of consumers to use their stores as a showroom for preliminary examination, that is, consumers visit and browse products displayed in a store but then make the purchase of the same product of interest from an online retailer, usually for a lower price — a form of behaviour that henceforth has been named ‘showrooming’.  This conduct may indeed be a cause of worry, but it is not an obstacle retailers of traditional stores cannot surmount, and it tells only part of the story of mobile-assisted shopping.

Consumers may perform multiple activities on their mobile device while in a store, like checking on additional technical information on product features and functionalities, compare prices, and consult with product reviews. These types of “market research” for learning by consumers are legitimate and actually should be encouraged — there is no justification nor excuse for retailers to try and block such activities. Especially at this time consumers will resent such action and may not forgive “a rude” shop manager who tries to interrupt their research activities (e.g., by disrupting wireless connectivity in the store’s premises). Moreover, mobile-assisted shoppers expect to be able to communicate through social networks (e.g., Facebook, Twitter) with friends and relatives but also with the store itself, when needed. The challenge of retailers is to tackle the threat of showrooming yet keeping with the new rules of the game, that is, information-rich shopping.

The Centre on Global Brand Leadership at Columbia Business School together with Aimia (a consulting firm on retail loyalty programmes) published last September a research report on “Showrooming and the Rise of the Mobile-Assited Shoppers. The research characterises different activities that mobile-assisted shoppers perform, assesses the extent of their utilisation and the business implications. At the heart of the research is a segmentation model comprising five groups of these shoppers who differ in types and levels of usage of their mobile devices during their shopping in brick-and-mortar stores.

A survey of 3,000 mobile-assisted adult shoppers in the United States, Canada and the United Kingdom was conducted online in late November 2012. A shopper qualified for the study if she or he confirmed owning a smartphone or a tablet with a data plan and using the device within the last twelve months to “aid in shopping for a product while in a store (e.g., looked up information or reviews on the product, compared prices, texted or called a friend for advice, etc.),” It is noted that smartphones receive greater emphasis than tablets throughout the report, understandably given the greater penetration of the former among consumers in 2012, but this situation is likely to change in coming years and both kinds of mobile devices are relevant.

We may already get an initial indication of the scale of using mobile devices while shopping in physical stores from the screening stage of the survey wherein it was found that the incidence rate of ‘qualified’ mobile-assisted shoppers (among Internet users!) was 21% — already a significant rate but it suggests that the phenomenon is not yet dominant and pervasive. With respect specifically to showrooming, it is estimated that as many as 70% of the mobile-assisted shoppers (M-Shoppers) showroomed at least once in the past year (i.e., “visited a store to look at a product, and purchased the product from an online retailer instead”). Not less conspicuous, as the researchers point out in their analysis, is the opposite finding that there are 30% of M-Shoppers who refrain from engaging in showrooming.

About half of M-Shoppers report comparing prices (52%) and looking up product information and reviews (50%) regularly (i.e., almost always, frequently or half-the-time) while in-store. Also, nearly 40% report texting or calling friends or family members regularly for advice from the store, an obvious course of action that the M-Shoppers can take, though it does not involve any unique advantages of smartphones’ capabilities and requires no advanced skills. The activities that are truly interesting and do matter, in addition to searching for price and product information on mobile websites, are such as (1) using a barcode or QR code of a product on the shelf (36% have ever done so); (2) posting an update on a social network (24%); (3) location-based check-in (e.g,, on Facebook, Foursquare) (22%);  or (4) mobile login to a store’s loyalty programme (17%). It is furthermore important to note that 75% of M-Shoppers report browsing websites of other enterprises vis-a-vis 70% visiting the retailer’s own website, signifying the essence of making the retailer’s website available to patrons in-store as a way of countering their browsing websites of competitors. To this we may add that 42% use the retailer’s app, another important tool that helps to increase the bond of M-Shoppers to the retailers of physical stores.

The primary driver for showrooming is the offering of a product of interest at a lower price from an online retailer (69% of M-Shoppers). But focusing on the lower price of the product item has a catch because the costs of purchase on the Internet include also delivery charges so that in the bill’s total this purchase may not be less expensive. Consumers who get attracted by lower prices online tend to neglect at least in the first moments to consider the additional costs. One of the frequent reasons for abandoning a shopping cart online occurs when e-shoppers reveal the delivery surcharges as they are about to complete their purchase order. Some M-Shoppers do take this into account and declare that they prefer to showroom when the online retailer offers shipping free of charge (42%). On the other hand, main incentives for preferring to buy at the physical store, even when M-Shoppers know it’s possible to buy the product from an online retailer at an equal or lower price, were immediacy of obtaining the product and greater convenience of buying in store; aspects such as customer service and trust are secondary motives.

The five segments can be distinguished, according to the report, as (a) those that pose greater problem or threat to brick-and-mortar retailers (three segments accounting for 38% of M-Shoppers); and (b) those that are less troublesome and even offer more opportunities (two segments accounting for 62%).

The greatest threat arises from M-Shoppers who are Exploiters — they are pre-determined to buy from an online retailer and intentionally enter the brick-and-mortar store only to examine the product closely first hand before making the order online. They truly use the store just as a ‘showroom’. Attention however: this segment constitutes just 6%(!) of M-Shoppers. They are not distinctively driven to purchase online by a lower product price but by free shipping by the e-tailer — free delivery home from a local store to the customer’s home can mitigate the Exploiter’s intention to buy online.

Two segments may be described as “swinging”: they are inclined to purchase online but are not fixed on it. The Savvys (13%) are “calculating but persuadable” — they deliberately search for information and study their possibilities when about to purchase a product, and decide on their findings. The Savvys are especially “digitally-attuned”, referring to various online sources (e.g., 60% researched product information vs. 49% of all M-Shoppers) and applying digital tools more than other M-Shoppers (e.g., 47% searched for online coupons vs. 34%, also 18% paid at checkout through smartphone vs. 10% of all M-Shoppers). The key to reach and persuade them is through helpful information and attractive offers and experiences in the mobile space. The researchers see them as a currently yet small segment of shoppers but strategically important for the future. The Price-Sensitives (19%), on the other hand, tend to be more opportunistic in their shopping behaviour. They do not plan to showroom but will do so once a lower price offer comes around. They are deal-prone and price discounts is the main way to attract them. The researchers suggest that a good tactic for the store owner regarding this segment would be to give them good reasons not to pull their smartphone out of their pocket or handbag.

The most promising segment appears to be one of Experience Seekers (32%) because they are most open and appreciative of retail initiatives, special offers and events that can increase their enjoyment and enhance their shopping experience. Price is just one of the considerations, and not the most influential one. Thus, if a brick-and-mortar retailer organises special merchandise displays and events with celebrity guests, provides personal treatment and better offers to loyal customers, as well as ways of interacting with the store on their mobile device, they have good chances of winning the Experience-Seekers over the e-tailers.

Last, the Traditionalists (30%) are basically more conservative M-Shoppers who prefer to shop and buy in physical traditional stores and who make less use of technologies of their mobile devices: they prefer shopping locally (34% vs. 19% of all M-Shoppers), trust physical stores more (27% vs. 14%), expect a better store return policy (23% vs. 15%), search less for product and price information (32%-34% vs. 50%-52%), and did not showroom in the past year. They are relatively less likely to have a tablet with a data plan; their more likely usage of the smartphone is apparently for consulting with friends and family members. As the report indicates, they are the least threatening segment to retailers of physical stores.

The segment of Exploiters is relatively a little larger in the UK (9%) where they may present somewhat more trouble to retailers; overall the three more problematic segments in the UK account for 46% of M-Shoppers compared with 35% in the US and 32% in Canada. The Experience-Seekers are the more prevalent in the US (36%) while Canada is distinctive by its high share of Traditionalists (43%!).

  • There is no mention in the report of the proportion of ‘showroomers’ in each segment nor of their frequency of doing so. Thus it is not known how segments differ in their extent of showrooming except for the fact that there are no showroomers among ‘traditionalists’ while in other segments M-Shoppers showroomed. This is a peculiar shortcoming of the report.

Competition between retailers that operate brick-and-mortar stores has always existed, and in fact shoppers may visit the website of another competing traditional retailer just as they visit the website of an e-tailer operating only an online shop to check on products available and their prices. Visiting the website of a competing traditional retailer would not change essentially the competition compared to visiting the physical stores. The particular concern of retailers about exclusively online e-tailers arises because the latter do not invest in constructing physical store environments and in setting-up appealing displays of merchandise, primarily for familiar and leading brands. It looks as if e-tailers rely on shoppers to scrutinize products closely at a physical store without making an effort of their own. It is widely agreed already that medium and large retailers need to have a website (regular and mobile-supported) to accompany their physical stores, but there are issues at question hanging over selling also online — how and to what extent it should be done, for instance:

  • Allowing M-Shoppers to access the online shop of a retailer while in his store and complete their transaction there may not matter to the retail business as long as revenue is generated. However, it could upset store managers that do not get this store-associated revenue attributed to them (e.g., for their prestige as well as bonuses). It may also cause sub-employment of their staff in-store.
  • Offering products in the online shop at lower prices than at their physical stores may draw M-Shoppers from referring to an e-tailer but it would discourage them from buying in the store even further.

Therefore, retailers need to work-out carefully the relationships between their physical stores and their regular, as well as mobile, website. Patrons of the brick-and-mortar stores should be served separate special offers not available to those who buy online; they may also be offered physical gifts, rather than price discounts, that only the patrons can enjoy immediately in-store. The report mentions that Walmart launched in recent months a geo-location mobile app that can identify and suit offers specific to the store a customer visits. Geo-location apps and mobile websites accessible if and only if customers are in-store may aid in two important ways: (1) Allow purchases made through an app be assigned to the relevant store where the app was used; and (2) The app or website admits a customer-patron to a loyalty programme where she receives deals and other benefits exclusively when in-store, whether she buys through the app/website or at the store’s cashier.

There are many possible avenues of action for retailers to overcome the threat, or rather the challenge, of showrooming. They can capitalise on advantages particular to the constructed environment of a brick-and-mortar store along with interacting through various forms of behaviour assisted by mobile-devices to attract and persuade M-Shoppers to complete their purchases with them, in-store.

Ron Ventura, Ph.D. (Marketing)

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The past thirty years in Great Britain have been marked by some major economic and social changes, most notably de-industrilisation, decline in job security, a transition to service economy, and the rise to dominance of the financial sector. These developments have occurred to differing degrees in other Western countries as well but perhaps not in as a dramatic way as in the UK. Only in the past month we have witnessed the awakening of a heated public debate on these socio-economic developments in reaction to the death of late Baroness Margaret Thatcher, Prime Minister of the UK between 1979 and 1990, due to her reforms in the 1980s. Most people would describe themselves nowadays as “middle class” and yet people are at difficulty to define and agree on what that status means. The gross division of the British society into upper class, middle class and working class does not seem to hold any longer.

The BBC’s research branch Lab UK launched in 2011 a major research project, the Great British Class Survey (GBCS), in co-operation with an academic team led by Professors of Sociology Mike Savage of London School of Economics and Political Science (LSE) and  Fiona Devine of the University of Manchester. They embarked on developing a new model of social class whilst taking, however, a different approach to defining the determinants of social status that is not based solely on occupation and other economic variables.  At the core of the project the BBC underlines the large Web survey it has carried out, in which 161,400 respondents in Great Britain participated; this survey was accompanied nevertheless by another national survey in a representative sample of about 1,000 respondents interviewed face-to-face (the use of two data sources is discussed later in the post-article).

The model developed by the research team working with the BBC includes seven classes. The model still identifies layers of social class but their organisation is different from previous models that relied primarily on indicators of education, occupation and economic wealth; the model thus reveals new types of class segments. Most remarkably, the “middle class” is more diffused, splintering horizontally across more unique and distinct class segments, also replacing the reduced traditional working class.

The unusual structure of this social class model can be attributed primarily to the acknowledgement by the researchers that the social standing of people depends not only on the stature of their occupation and their economic wealth but also on additional personal resources that people develop over time. They rely on a schema developed by French sociologist Pierre Bourdieu that recognizes in culture a crucial pillar contributing to a person’s competences and stature. Bourdieu identified three forms of capital: economic capital (wealth and income), cultural capital (based upon educational upbringing, it defines a person’s tastes and ability to appreciate and engage with cultural goods such as arts and food), and social capital (the breadth and nature of contacts and connections in a person’s social networks that can benefit him or her). The expansion of the concept of “social class” hereby suggested by the researchers deviates from the concept’s “classical” economic foundations but it nonetheless enriches the model by bringing it closer to the concept of “lifestyle” — a connection that should be well appreciated in a marketing context. It allows one, for instance, to account for whether a person has more fine tastes or a stronger tendency to open-mindedness that may enhance his or her standing in society. Savage and Devine and their colleagues argue in favour of their approach that:

“This recognition that social class is a multi-dimensional construct indicates that classes are not merely economic phenomena but also are profoundly concerned with forms of social reproduction and cultural distinction” (2, p. 5).

A quick review of the new seven class segments (1):

  • Elite — The most privileged group with highest levels on all types of capital, but particularly distinguished by the greatest economic capital.  The largest (over-) representation of CEOs and other senior managers is found in this class.
  • Established Middle Class — Not as wealthy as the elite but still very high on all three capitals. The most gregarious group that also scores the second highest on cultural capital.
  • Technical Middle Class — A small but distinctive new class that is prosperous but more secluded, concentrating on its links to other profession experts. They are distinguished by their social isolation and cultural apathy.
  • New Affluent Workers — A rising group of young people who are successful in their jobs, with middling levels of economic capital though without acquiring higher education; yet, they are socially and culturally active that appears to give them a leverage.
  •  Traditional Working Class — Relatively older people, they constitute the remaining working class of the past (their offsprings are believed to belong in the new segments of New Affluent Workers and the Emergent Service Workers.) They are low on all forms of capital though not completely deprived, reliant especially on current high values of their houses.
  • Emergent Service Workers — They are young and urban though less well-off economically than the new affluents, positioned in relatively basic and low paying jobs in services (e.g., at call-centers, bars and restaurants); they are also characterised as highly active socially and culturally.
  • Precariat — The most poor and deprived group of precarious proletariat with low scores also on social and cultural capital.

The young segments that represent the newer generation of the “working class” seem to be a more savvy generation, less indifferent to or accepting of their social status, better connected, and working to improve their well-being, not only at their jobs. Are they types of “middle class” or “working class”? This is unclear — those familiar classes seem more confounded. The place of the lowest social class is taken now by the Precariats. Division in the British class system may have changed in form and structure but it remains powerful: Savage argues that the society is increasingly polarised between the elite at the top and the ‘precariat’ class at the bottom and with divisions growing deeper (3).

Hereafter a question is raised: What does this model imply for consumer behaviour?  The model provides a new foundation upon which marketing researchers and managers may develop better understanding of consumers’ motives and drivers, and the background to their behaviour. It can help answer not just what consumers can afford but what they may aspire for. It may further reveal how consumers aim to achieve their goals or implement their interests, suggesting specifically what kinds of products and services are utilised in the course of doing so. But the social class model is not sufficient to that end — it has to be joined by another model that elaborates on consumer lifestyles. The new opportunity for improvement that unveils with the new model is in creating a more meaningful and congruent bridge between a social class model and a lifestyle model. This bridge would be primarily cultural but there may also exist a social common denominator.

  • Economic capital is measured by household income, household savings and house value (the latter two are joined in a ‘wealth’ index).
  • Cultural capital takes in consideration leisure interests, taste in food, taste in music, use of media, and travel destinations for holiday. The researchers have borrowed the conceptual distinction of Bourdieu between elevated “highbrow” genres of culture and “popular” culture, but they apply it in a more flexible manner. First, following recent research, the model assumes that respondents from any class may simultaneously practice genres of both “highbrow” and “popular” culture (i.e., each type receives a separate score). Second, they furthermore refrain from making judgement about forms of culture that may appear degrading and use the term “emerging” instead of “popular” for describing culture forms like sports, playing video games, browsing the internet and participating in social media networks. Forms of “highbrow” culture include among others engaging with classical music or jazz, visiting museums, art galleries, theatres, and French restaurants. On these facets “social class” and “lifestyle” meet.
  • Social capital is evaluated through two metrics: the number of occupation groups (out of 34 possible groups) of the people with whom a respondent has social connections and a mean status score of those occupations. Models of lifestyle should now also relate to socialising activities and the kinds of information consumers share, given the significant place in time and content that social media networks fill in their lives. A lifestyle model may contribute some additional information on connections in the “real world” and/or in the “virtual world” that the social class model does not seem to distinguish (though it accounts for use of social media under “cultural capital”.)

It is not proposed to build a single integrative model that stands the risk of diluting either construct of “social class” or “lifestyle”. Rather, the new social class model and a lifestyle segmentation model should be married by crossing one with the other, the former focusing on the resources consumers hold and the latter elaborating on how those resources are expressed and employed in reference to consumer behaviour.

We would want to know more about the psychographics of members of the new social classes to understand how they can be expected to behave as consumers. Here are two issues to consider for probing:

What kind of shoppers the New Affluent and Emergent Service workers are likely to be? — more critical, cautious and price-conscious or more easy-spending on any products and services and their brands? They may choose products and brands they believe can improve their well-being or their image in the eyes of others. How do these two segments differ? (hint: the emergent service workers are said to be more eager to “live the day”, more seeking experiences rather than products (1)).

Consumers in the Established and the Technical middle class segments both have plenty of economic resources but the former has a much more varied range of social connections and is more culturally active, mixing highbrow and emerging forms of culture — how does that distinguish them as consumers with respect to time and money they spend with family and friends at home or outdoors, on their personal interests and hobbies, on the Internet, etc.?

It should be noted that this model outcome could not be obtained if based only on the web survey of the BBC’s GBCS. The researchers found a strong selection bias in the large web sample, lifting it socially upwards, that is, the web sample exhibited over-representation of Britons from well-educated social groups. It means that this sample could not be adequate for modelling social classes of the whole British society. The GBCS received high publicity in media channels of the BBC which may have served well for recruiting a sample of its audience but not beyond that. However, the bias may also be due to low rates of Internet literacy and usage in older and less privileged social groups.

Compared with the second national sample in a parallel survey conducted by GfK, it clearly shows how the web survey is biased upwards with respect to occupations, household income and ‘wealth’. The model was built by a method of latent class analysis on an integrated sample dataset where respondents in the national sample received their original weights to reflect the correct composition of the population, while respondents in the web sample were “fragmented” by giving each a weight of 1/161,400. All cases are classified simultaneously, yet the class system structure is based more heavily on the national sample and the GBCS sample serves primarily to provide greater detail on the profiles of those classes.

  • The differences between the two samples remain clear: the Established Middle Class is the largest segment, 25% of GfK national sample but it “grows” to 43% of GBCS web sample; the Elite is just 6% of GfK sample but 22% of GBCS sample; conversely, the New Affluent Worker is 15% of GfK sample but just 6% in the GBCS sample; and the Precariat segment that takes 15% of the GfK sample is almost non-existent in the GBCS sample. (2)

The new British social class model recently published reveals additional important facets to social standing, based not just on economic resources but influenced also by social relationships and cultural capital. The enriched model also offers a bridge to associate with a lifestyle model that would shed more light on implications of the classes for consumer behaviour and marketing. It may also give encouragement to consumers that they can invest in their social and cultural capital to improve their well-being and social standing before they are able to increase their economic capital.

Ron Ventura, Ph.D. (Marketing)

Sources:

1. The Great British Class Survey (GBCS) Special Section on BBC News Online:

(a) “Huge Survey Reveals Seven Social Classes in UK”, BBC News: UK, 3 April 2013 http://www.bbc.co.uk/news/uk-22007058

(b) “Class Calculator: Can I have No Job or Money and Still Be Middle Class?”, BBC News Magazine, 4 April 2013    http://www.bbc.co.uk/news/magazine-21953364

2. “A New Model of Social Class: Findings from the BBC’s Great British Class Survey Experiment”, Mike Savage, Fiona Devine et al., Sociology (Online), April 2013 (link is available on BBC website, 1b)

3.  “The British Class System is becoming more polarised between a prosperous elite and a poor ‘precariat'”, Prof. Mike Savage discusses the results of the research, London School of Economics: British Politics and Policy at LSE (Blog), 4 April 2013,   http://blogs.lse.ac.uk/politicsandpolicy/archives/32264

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An IKEA store is a marvelous place.  You walk through halls, hall after hall after hall and so on, surveying with your eyes the different furniture items, accessories and other kinds of decorative. You are filled with curiosity and enthusiasm in search for that great enhancement to your home. In each hall furnitures are usually organized in a layout and structure of a complete set according to a given purpose such as a living room seating corner, a dining hall or a children room. There are many possible sets with different styles of items in a hall associated with a particular part of the house or apartment. As you look at a set and examine more closely the composing items you may start to image in your head how it may look in the target area of your own home. During the tour you may pick up some small items and put them in a bag. As for the larger items chosen you need to write down their details on a paper form to be retrieved later on at a storage hall. Everybody is busy at Ikea. The whole venue resembles somewhat an amusement park, or perhaps more like a beehive. It is a temple for celebrating consumption.

But to the likely disappointment of many residents in the central coast area of Israel this shopping and consumption attraction has been destroyed. On the Saturday morning of  5 February the Ikea store near the coastal city of Netanya burned down into ashes to the last wooden artefact.   The store served primarily Israelis living from Tel-Aviv in the south to Hedera in the north of the store location (about 30 km to each side). Israeli consumers who have become used to shop for furniture at relatively low prices and then construct themselves by instructions at home are about to be deprived of this possibility for six months to a year. It has been a strong anchor in an industrial and shopping compound of Netanya-Poleg. This calamity of the Ikea store leaves great uncertainty: how it will affect shopping behavior and spending of consumers who have been among its patrons, the employees of the store, and other retail businesses in the same compound.

An inquiry conducted by the fire brigades and police has found that rain was the likely cause of an electric failure of cables on the structure’s roof and the fire that started quickly extinguished a tar-based coveting of the roof; the suspicion of arson has been eliminated but negligence would still have to be examined. Because the fire started on the roof, internal alarm signals and all other kinds of precaution means (e.g., smoke detectors, water sprinklers, inter-hall emergency doors) were rendered useless — flames consumed the roof from the outside-in until it collapsed; the fire brigades could do little on their arrival to save the store. Notwithstanding the total damage caused, fortunately the fire happened when the store was closed. It is probably better not to think of what could have occurred if shoppers and employees were caught by inferno in the intermediate halls. The special layout of a maze that Ikea is so proud of can become a precarious, deadly trap in such circumstances for those people .

The damage is estimated  in the range of hundreds of millions of Israeli shekels (100 million NIS equals about $30m). Additionally, a loss of million shekels (~$300,000) is estimated for each day the store remains inactive. The store (23,000 square meters in two floors) was the first to open in the country in April 2001. A second store opened just last March (34,000 square meters) near the city of Rishon LeZion some 20km south of Tel-Aviv. Together the two stores received 3.5 million visitors during 2010. Sales turnover grew by 40% in 2010 with two stores from 2009 with only the Netanya store (from 500m to nearly 7o0m NIS ≈ from  $140m to $200m)(TheMarker 6/2/11). The great push that the new and larger store was planned to provide for the expansion of Ikea’s business in the country is now suspended for many months.

It is difficult to predict how consumers in the affected region who relied on the concept of Ikea for offering furniture will react, modifying or adapting their buying and home consumption behaviour. That is because Ikea offers more than a simple transaction — Ikea offers a deal with implications for the way of life of consumers. First, the deal says something like “we deduct a certain sum from the “normal” price of a whole furniture that you can save by constructing it yourself from our supplied components”. Second, Ikea gives consumers the opportunity to be involved in creating their own piece of furniture, taking the role of producers (i.e., Ikea customers become prosumers following Alvin Toffler). For people who like to build things with their own hands, there is actually additional benefit in buying the product disassembled and complete the job themselves. And there is also the feeling of achievement and satisfaction seeing the furniture one built him- or herself standing  at home. From personal experience I may add that joint work of members of the family can also help family bonding. Hence, doing-it-yourself is not just a type of cost (i.e., time and effort) for the “craftsman” consumer that has to be compensated by a price saving but can be a true source of additional value. The level of creativity is limited as people have to follow specified instructions, but thus even those who are not too capable at craftmanship can build furnitures the Ikea-way.

In reality, not all pieces of furniture can be assembled or constructed self-handedly (e.g., sofas that come complete). There also are complex sets like kitchen furnishing that have to be built at home by professional workers. In addition, not all Ikea customers truly like to do things themselves but they still prefer the products of Ikea for example for the quality of its woods and finishing of elements, and they are willing to pay a supplement to have someone come and build the furniture for them at their home.

To make a projection of how consumers may behave following the destruction of the Ikea store near Netanya, I propose to distinguish between four segments of consumers according to two dimensions: the propensity to produce things oneself and residence in the Tel-Aviv area versus north of Tel-Aviv closer to Netanya.

  • Consumers living north of Tel-Aviv who buy furniture from Ikea with intention to complete their construction themselves can be expected to defer their purchase for several months rather than turn to more standard furniture retailers. Unless the family is tied in other commitments (e.g., renovation works, entering a new home) it should not feel pressured to give up purchasing the furniture the way they like. This kind of purchase is usually not something done from one day to another and the extra time can be used comfortably to explore more options. Driving to Rishon LeZion will probably be too much trouble for them.
  • For consumers living north of Tel-Aviv who in any case prefer to get whole furnitures ready to use there is far less incentive to wait for Ikea to re-open its renewed store near Netanya. They are likely to search soon enough among the more traditional furniture retailers in their vicinity.
  • Consumers living in Tel-Aviv and its close satellite towns are likely to be quite indifferent between driving to Netanya or to Rishon Lezion. In rush hours when there are heavy traffic jams driving in either direction can take up to an hour and a half (otherwise it takes 20-30 minutes). So during the period that the Netanya’s store is incapacitated, consumers who wish to buy furniture to construct themselves, and save more money on the way, can continue to do so by simply turning southwards to Rishon LeZion. No substantial change in behaviour should be observed beyond that (if Ikea manages to handle the extra crowds properly).
  • For the remaining Tel-Aviv residents who are not keen on doing things themselves, they may return to explore and compare numerous more traditional retailers that exist in the Tel-Aviv area as people have done before the arrival of Ikea.

The situation with the 400 employees of Ikea Israel in Netanya is still unclear. This month they will remain on a paid leave. After that  it has been suggested by management that some employees might be transferred to the store in Rishon LeZion where they should be much-needed in coming months to serve larger traffic as suggested above while others could be sustained on a partial compensation until their return to work. But there probably would be a group of employees compelled to seek new employment. 

Prospects for other retail establishments (e.g., a food store, fashion stores, coffee-house) in the Netanya-Poleg compound can be quite grim in the year to come. Without Ikea many of them can expect to see  much weaker traffic. Over the years some furniture retailers situated their store structures next to roads approaching the Ikea store. But with far fewer passerby shoppers and no target to compare them against, these retailers are at risk of not having enough patronage to live on.

The revenue of Ikea International in the fiscal year ending 31 August 2010 rose 7.7% to  €23.1 billion (compared with some €145 million in 2010 for Ikea Israel). During 2010 Ikea openned worldwide 12 stores in total and its management seems to be more invigorated by its growth in China, Russia, and Portugal (Telegraph 14/1/11). The business of Ikea Israel could be just a fraction of Ikea worldwide, but there must be serious lessons for the international management to learn from the events in this small corner of the world, regarding the structures of its stores, its maze layout, and the measures the company takes anywhere to ensure the safety of its customers.  Other lessons may still to be anticipated as how to recuperate from such a crisis.

Ron Ventura, Ph.D. (Marketing)

Media sources: 

Ikea fire caused hundreds of millions in damage, destroyed store entirely , TheMarker, 6/2/11

http://english.themarker.com/ikea-fire-caused-hundreds-of-millions-in-damage-destroyed-store-entirely-1.341491

Ikea sales rise on strong demand from China,  Telegraph, 14/1/11

http://www.telegraph.co.uk/finance/china-business/8260893/Ikea-sales-rise-on-strong-demand-from-China.html

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