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Posts Tagged ‘Thoughts and Feelings’

When evaluating a restaurant, the quality of food is not like other factors considered — it has a special status. The same goes quite as much for other food establishments like coffee-houses. The customers or patrons may trade-off several factors which include the food, service, venue, price and location, yet food quality usually gets a much greater weight than the other attributes, suggesting that the decision process is practically not fully compensatory. The quality of the food, its taste and how much we enjoy it, is a “pre-condition” to dining at a restaurant. However, the balance with other attributes is important; in some cases, failure on those other attributes can be detrimental to the willingness of consumers to return to a restaurant or a coffee-house.

  • Some coffee-houses effectively function as ‘coffee-restaurant’ establishments by serving meals of a variety of food items suitable for every time of day (from eggs, salads and toasts to soups, pasta, hamburger or chicken-breast schnitzel with supplements).

Suppose that Dina and Mark, a fictional couple, are dining at a restaurant and find the dishes served to them being well-prepared and they enjoy very much the food’s taste. However, they are very unhappy with the sluggish service they get and inappropriate answers of the waiter, and feel the atmosphere in the restaurant is not pleasant (e.g., too dark or too noisy). The experience of Dina and Mark can be greatly hampered by factors other than food. How superior should the food be for our diners to be ready to tolerate bad service or a place they do not feel comfortable to be in for an hour or two?

On the other hand, Dina and Mark would likely expect the food (e.g., a dish like ‘risotto ai funghi’ [with mushrooms]) to uphold to a certain gratifying standard (i.e., that the ingredients are genuine, the texture is right, and the dish is overall tasty). If the food is not perceived good enough and diners do not enjoy it, this takes out the point of considering dining at the restaurant altogether. But if the food is good though not so special or great, yet the patrons Dina and Mark feel the staff truly welcome them, treat them warmly and cater to sensitivities they may have, they could still be happy to dine at such a restaurant again, and again. When the food is already satisfactory, additional facets of the experience such as great service and a pleasing ambience can increase substantially the desirability of a restaurant or coffee-house as a place consumers would  like to patronize. We may be looking at a decision process where at first food is a non-compensatory criterion, yet above a certain perceived threshold the balance customers-patrons strike between food and other attributes of their experience becomes more intricate and complex.

Browsing reviews of restaurants that are shared on TripAdvisor’s traveller website can provide helpful clues on how customers-patrons relate to food and additional factors in their appraisals of their experiences at restaurants. Reviews were sampled of Italian and Asian restaurants in Tel-Aviv and London (members-reviewers may be city locals, national and international travellers — examples are quoted anonymously so that reviewers and the specific restaurants they review are not identified by name).

Reviewers most often open by referring to the food they have had at the restaurant; next they may give their assessment of the service they have received, design and atmosphere, price or value, and location of the restaurant. Thus, a review may start by appraising the food as good / great / delicious, and then stating that the service was good / nice / efficient. Nonetheless, it is not uncommon for diners-reviewers to open with an assessment of the service they have received at the restaurant. There seems to be a greater propensity to open the review with service when it is superb, but also on the contrary when it is terrible. Occasionally a review will refer firstly to the atmosphere in the restaurant, which is formed by aspects such as interior design or décor, lighting, music and overall ambience. Atmosphere will appear first or at least early in the review particularly when it is superior or inferior.

Additionally, we can distinguish between reviews that are composed of a few short argument-like statements about the food, service and other attributes, and reviews that tell a story (i.e., a narrative-like review). There are diners-reviewers who go especially into detail of the dishes or items of food they, and possibly their companions, have ordered, and their opinion of the food. Yet reviewers may also describe how they were treated by the serving staff, particularly when they felt exceptionally welcome and cared for or annoyed and undesired. Reviews that have a narrative give a stronger impression of the course of dinner to the reader who can more easily visualize it.

It seems that when diners-reviewers say the food is ‘good‘, they do not throw it out of hand; they do mean that the food is truly good, fresh and tasty. This appraisal should be interpreted as a base threshold for being satisfied with the food. When the food is more than ‘good’, reviewers explicitly express it with adjectives like ‘great’, ‘delicious’, ‘fabulous’ or ‘amazing’. Conversely, descriptions of the food as ‘average’, ‘OK’, and moreover as ‘mediocre’, are certainly not compliments, more likely suggesting the food was barely satisfactory. Unless there was something else especially good about the experience in that restaurant like its service or venue, the reviewer would probably have little motivation to return.  Consider for example a reviewer who said about an Italian restaurant in Tel-Aviv: “The ONLY redeeming factor is, in my opinion, the ambience, which is really cozy and relaxed. Too bad they don’t serve food to match” (capitals in origin, rating: 2 ‘rings’ out of 5). Similarly, a reviewer of an Asian restaurant in London complimented it for its “friendly and attentive” waiting staff, but concluded: “So there were a lot of positives about this place, but I’m afraid the food just wasn’t good quality. It was very bland and boring” (rating: 2 ‘rings’). On the other hand, a review of an Asian restaurant in Tel-Aviv offers the opposite case wherein the reviewer states “AMAZING food, OUTRAGEOUS service” (title, capitals in origin), and ends with the conclusion “basically terrible service which was definitely the opposite of the wonderful tasty food we were served” — the rating for this restaurant experience: also 2 ‘rings’.

  • A prospective diner who looks for a restaurant to try for the first time may find the choice task confusing and daunting when reviews of the same restaurant are quite the opposite of each other in their content. Still, it usually does not take too long to realise the ratio of positive to negative reviews given to a restaurant, in addition to the chart of distribution of ratings it received.

Service appears as the second most important factor after food in a restaurant. Patrons want the waiting staff to be friendly and respectful (this of course is a two-way street), be attentive and not letting them feel forgotten, and to be flexible and kind enough to accommodate their personal sensitivities or preferences (e.g., less spicy, nuts-free, replace polenta with rice as supplement). Less pleasant or efficient service will not necessarily make diners-reviewers reject the restaurant if its food is excellent, but they could drop one grade off its rating (e.g., from 5 to 4). Inversely, when the diners-reviewers are happy with the quality and taste of food, then also meeting a warm and helpful waitress — or sitting in comfort in a beautifully designed venue — can make the whole experience so much better. Reviewers repeatedly emphasise when, on top of their pleasure of the food, they are impressed by a waiter or waitress who smiled to them, was friendly, attentive and helpful, and made them feel at home. A reviewer of an Italian restaurant in London explains why it is her favourite: “Quite simply, the food is absolutely gorgeous. Wonderful ingredients and very well cooked. But most of all the welcome that we received and service that we got from everyone is great” (rating: 5).

A particular aspect of service is the length of time a customer has to wait either to be seated at a table or while dining. Many restaurants take table reservations, but not all do. Not taking reservations is legitimate, but it is far less acceptable and even offensive when staff at a restaurant (including coffee-restaurants) run a waiting list at the doorstep and appear pleased with letting prospect customers gather and wait outside as if to show around how popular their establishment is; if you complain they may even hint at you how much they do not really need your patronage. Such past experience may have made a British reviewer visiting an Italian restaurant in Tel-Aviv be thankful when: “The staff were very pleasant and found us a seat on a very busy afternoon without behaving as if they were doing us an enormous favour”. In a different case, at an Asian restaurant in London, a reviewer commented: “Long wait to be seated, despite the place being half empty, as the servers were running around serving tables but not seating people”. Considerate restaurant proprietors may keep seats reserved for people waiting (e.g., next to the bar), and may even offer them a free drink if waiting is extended.

While at the table, diners dislike when waiters appear to forget them behind or somehow miss sight of them (e.g., waiting for menus, for taking order and bringing courses ordered, for the cheque). A reviewer in Tel-Aviv was critical pointedly of servers who “it seems lost interest”, and started chatting with their colleagues or playing on their phones. Waiting staff are expected to stand by, being ready to answer requests or voluntarily enquire if diners need anything. An American reviewer at another Italian restaurant in the city, coming “late one night”, appreciated that “my waitress made an effort to check on me regularly”. At an Italian restaurant in London, a reviewer noted that on arriving early for a meeting, “I was offered a newspaper to read while I waited which I thought a rather nice touch”; overall, he commended the service whereby “the staff proficiently and effortlessly ensured everyone felt special and were looked after”. Seemingly little touches matter!

In restaurants of fine cuisine it seems justified to wait patiently longer for an order (e.g., 20 minutes for a main course) as it could mean that the dish is freshly prepared with care for you in those very moments from start to finish [an advice received from my father]. In many ‘popular’ or casual restaurants, however, it would be much less the expectation, though it could depend on the type of food and how complicated it is perceived to prepare the dish. Furthermore, the sensitivity of customers-patrons to time spent could be subject to the occasion (e.g., meeting and dining leisurely in the evening vs. a pre-theatre dinner or a lunch break).

Reviews tend not to address directly the time until a dish ordered is served but more generally relate to the waiting time at any stage while being at the table. Some relevant references were traced in reviews of Asian restaurants in London: (a) A reviewer noted that “service can be slow” and “a bit hit and miss” (although the food and atmosphere were good); (b) Waiting for food was raised by a reviewer as an issue for concern: the waitresses seemed “understaffed” and having “stressed looking faces”, with the result that “We sat around with no food or drink for over 20 minutes before we could grab a waitresses’ attention” (the food was “fantastic” and the rating given could otherwise be 5 rather than 4 — the reviewer “would defiantly” return); (c) A reviewer who was overall happy with the friendly and efficient service and “freshly cooked and tasty delicious” food particularly remarked that the “food came quickly”.

The aesthetics of interior design of a restaurant or coffee-house can also have an impact on consumers’ attitude towards the place and on their behaviour. The style, materials, colours, surrounding decorations, furnishing, lighting etc. are instrumental in the way the design helps to create a certain atmosphere and mood (e.g., cold or warm; traditional or top-notch modern; quiet, ‘cool’ or energetic).

John Barnett and Anna Burles of ‘JB/AB Design’, a London-based agency specialising in design of coffee shops, offer six instructive guidelines on the ways design on different levels can contribute to brand experience. They start with creating a happening in the coffee shop (‘The shop is a stage’), followed by using appetizing imagery of food (‘customers eat with their eyes’); being authentic and relevant; persuasive visual merchandising; creative ambience; and giving customers good reasons to come and ‘gather around a table’ in  the coffee shop. Their recommendations sound mostly if not all adaptable to more types of food and drink establishments, including restaurants. In setting an authentic design, they advise to ‘say it like you mean it’ all round the shop : “The whole shop is a canvas for imagery and messaging that forms the basis of a conversation with your customers”.

Reviewers-diners talk less frequently of aspects of interior design and description of the space of the venue; broader references are made to atmosphere or ambience. In the case of an Italian restaurant in the Tel-Aviv area with an elegant modern design, three different reviewers noted it has “a very nice décor”, that it is “very spacious and modern”, and the “interior is beautiful, a lot of air”. A reviewer relating to an Italian restaurant in London wrote: “The décor seems a little dated, but there were some fun touches”. This reviewer also addressed music played in creating a pleasing atmosphere (“alternated nicely between Frank Sinatra and Luciano Pavarotti — perfect!”). A reviewer-diner mentioned earlier, who was impressed by the newspaper gesture, also said of that Italian restaurant: “The ambience was extremely relaxed and the décor is comfortable, plush and smart”. An Asian restaurant in Tel-Aviv was described by a reviewer as “pleasant, with very informal atmosphere, soft background music, and industrial/downtown décor”.

Some appraisals of design and atmosphere sound somewhat more reserved though still positive. For example, a reviewer said of a luxury Asian restaurant in London that it is “very dark inside, but somehow it is also very cooling place”. A reviewer in another luxury Asian restaurant was very impressed by a modern-futuristic design yet felt uncomfortable with it: “The place is playing with your perception, slightly disorienting with its colours and stairs and reflecting surfaces”. The reviewers quoted above were largely very happy with the food as well as the service. In just one case observed, a reviewer of an Asian restaurant in Tel-Aviv became very upset with the food and proclaimed “Sorry! But when we decide to go to the restaurant, we wish to have a good meal, NOT ONLY a trendy design” (capitals in origin, rating: 1). In this case the “rather nice designed place” could not compensate for a poor food experience. Customers-patrons welcome inspiring and modern designs, but the design must also feel pleasing to the eye and comfortable — be creative with designs but not be excessive.

A top priority for restaurants, and to a similar degree also for coffee-houses, remains taking the most care of the quality and taste of the food they serve. However, it is essential to also look after additional factors or facets that shape the customer’s experience such as service, design and atmosphere, price or value. The kind of service customers-patrons experience is especially a potential ‘game-changer’. Additionally, consumers may not be coming to a restaurant or coffee-house for its design but if it looks appealing the design and atmostphere can make the stay more comfortable and enoyable, and encourage patrons to stay longer, order more, and return. Food is a central pivot of customer appraisals, yet other facets of the experience can tilt it either way: spoil and even ruin the experience or instead support and enhance it.

Ron Ventura, Ph.D. (Marketing)

 

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The strength, impact and value of a brand are embodied, fairly concisely, in the concept of ‘brand equity’. However, there are different views on how to express and measure brand equity, whether from a consumer (customer) perspective or a firm perspective. Metrics based on a consumer viewpoint (measured in surveys) raise particular concern as to what actual effects they have in the marketplace. Datta, Ailawadi and van Heerde (2017) have answered to the challenge and investigated how well Consumer-Based metrics of Brand Equity (CBBE) align with Sales-Based estimates of Brand Equity (SBBE). The CBBE metrics were adopted from the model of Brand Asset Valuator (Y&R) whereas SBBE estimates were derived from modelling market data of actual purchases. They also examined the association of CBBE with behavioural response to marketing mix actions [1].

In essence, brand equity expresses an incremental value of a product (or service) that can be attributed to its brand name above and beyond physical (or functional) attributes. Alternately,  brand equity is conceived as the added value of a branded product compared with an identical version of that product if it were unbranded. David Aaker defined four main groups of assets linked to a brand that add to its value: awareness, perceived quality, loyalty, and associations beyond perceived quality. On the grounds of this conceptualization, Aaker subsequently proposed the Brand Equity Ten measures, grouped into five categories: brand loyalty, awareness, perceived quality / leadership, association / differentiation, and market behaviour. Kevin Keller broadened the scope of brand equity wherein greater and more positive knowledge of customers (consumers) about a brand would lead them to respond more favourably to marketing activities of the brand (e.g., pricing, advertising).

The impact of a brand may occur at three levels: customer market, product market and financial market. In accordance, academics have followed three distinct perspectives for measuring brand equity: (a) customer-based — an attraction of consumers to the “non-objective” part of the product offering (e.g., ‘mindset’  as in beliefs and attitudes, brand-specific ‘intercept’ in a choice model); (b) company-based — additional value accrued to the firm from a product because of a brand name versus an equivalent product but non-branded (e.g., discounted cash flow); financial-based — brand’s worth is the price it brings or could bring in the financial market (e.g., materialised via mergers and acquisitions, stock prices)[2]. This classification is not universal:  for example, discounted cash flows are sometimes described as ‘financial’; estimates of brand value derived from a choice-based conjoint model constitute a more implicit reflection of the consumers’ viewpoint. Furthermore, models based on stated-choice (conjoint) or purchase (market share) data may vary greatly in the effects they include whether in interaction with each competing brand or independent from the brand ‘main effect’ (e.g., product attributes, price, other marketing mix variables).

A class of attitudinal (‘mindset’) models of brand equity may encompass a number of aspects and layers: awareness –> perceptions and attitudes about product attributes and functional benefits (+ overall perceived quality), ‘soft’ image associations (e.g., emotions, personality, social benefits) –> attachment or affinity –> loyalty (commitment). Two noteworthy academic studies have built upon the conceptualizations of Aaker and Keller in constructing and testing consumer-based measures:

  • Yoo and Donthu (2001) constructed a three-dimension model of brand equity comprising brand loyalty, brand awareness / associations (combined), and perceived quality (strength of associations was adopted from Keller’s descriptors of brand image). The multidimensional scale (MBE) was tested and validated across multiple product categories and cultural communities [3].
  • Netemeyer and colleagues (2004) demonstrated across products and brands that perceived quality, perceived value (for the cost), and uniqueness of a given brand potentially contribute to willingness to pay a price premium for the brand which in turn acts as a direct antecedent of brand purchase behaviour [4]. Price premium, an aspect of brand loyalty, is a common metric used for assessing brand equity.

Datta, Ailawadi and van Heerde distinguish between two measurement approaches: the consumer-based brand equity (CBBE) approach measures what consumers think and feel about the brand, while the sales-based brand equity (SBBE) approach is based on choice or share of the brand in the marketplace.

The CBBE approach in their research is applied through data on metrics from the Brand Asset Valuator model developed originally by Young and Roubicam (Y&R) advertising agency (the brand research activity is now defined as a separate entity, BAV Group; both Y&R and BAV Group are part of WPP media group). The BAV model includes four dimensions: Relevance to the consumers (e.g., fits in their lifestyles); Esteem of the brand (i.e., how much consumers like the brand and hold it in high regard); Knowledge of the brand (i.e., consumers are aware of and understand what the brand stands for); and  Differentiation from the competition (e.g., uniqueness of the brand)[5].

The SBBE approach is operationalised through modelling of purchase data (weekly scanner data from IRI). The researchers derive estimates of brand value in a market share attraction model (with over 400 brands from 25 categories, though just 290 brands for which BAV data could be obtained were included in subsequent CBBE-SBBE analyses) over a span of ten years (2002-2011). Notably, brand-specific intercepts were estimated for each year; an annual level is sufficient and realistic to account for the pace of change in brand equity over time. The model allowed for variation between brands in the sensitivity to their marketing mix actions (regular prices, promotional prices, advertising spending, distribution {on-shelf availability} and promotional display in stores) — these measures are not taken as part of SBBE values but indicate nonetheless expected manifestation of higher brand equity (impact); after being converted into elasticities, they play a key role in examining the relation of CBBE to behavioural outcomes in the marketplace.


  • Datta et al. seem to include in a SBBE approach estimates derived from (a) actual brand choices and sales data as well as (b) self-reported choices in conjoint studies and surveys. But subjective responses and behavioural responses are not quite equivalent bases. The authors may have aimed reasonably to distinguish ‘choice-based’ measures of brand equity from ‘attitudinal’ measures, but it still does not justify to mix between brands and products consumers say they would choose and those they actually choose to purchase. Conjoint-based estimates are more closely consumer-based.
  • Take for instance a research by Ferjani, Jedidi and Jagpal (2009) who offer a different angle on levels of valuation of brand equity. They derived brand values through a choice-based conjoint model (Hierarchical Bayes estimation at the individual level), regarded as consumer-level valuation. Vis-à-vis the researchers constructed a measure of brand equity from a firm perspective based on expected profits (rather than discounted cash flows), presented as firm-level valuation. Nonetheless, in order to estimate sales volume they ‘imported’ predicted market shares from the conjoint study, thus linking the two levels [6].

 

Not all dimensions of BAV (CBBE) are the same in relation to SBBE: Three of the dimensions of BAV — relevance, esteem, and knowledge — are positively correlated with SBBE (0.35, 0.39, & 0.53), while differentiation is negatively although weakly correlated with SBBE (-0.14). The researchers reasoned in advance that differentiation could have a more nuanced and versatile market effect (a hypothesis confirmed) because differentiation could mean the brand is attractive to only some segments and not others, or that uniqueness may appeal to only some of the consumers (e.g., more open to novelty and distinction).

Datta et al. show that correlations of relevance (0.55) and esteem (0.56) with market shares of the brands are even higher, and the correlation of differentiation with market shares is less negative (-0.08), than their correlations with SBBE (correlations of knowledge are about the same). The SBBE values capture a portion of brand attraction to consumers. Market shares on the other hand factor in additional marketing efforts that dimensions of BAV seem to account for.

Some interesting brand cases can be detected in a mapping of brands in two categories (for 2011): beer and laundry detergents. For example, among beers, Corona is positioned on SBBE much higher than expected given its overall BAV score, which places the brand among those better valued on a consumer basis (only one brand is considerably higher — Budweiser). However, with respect to market share the position of Corona is much less flattering and quite as expected relative to its consumer-based BAV score, even a little lower. This could suggest that too much power is credited to the name and other symbols of Corona, while the backing from marketing efforts to support and sustain it is lacking (i.e., the market share of Corona is vulnerable).  As another example, in the category of laundry detergents, Tide (P&G) is truly at the top on both BAV (CBBE) and market share. Yet, the position of Tide on SBBE relative to BAV score is not exceptional or impressive, being lower than predicted for its consumer-based brand equity. The success of the brand and consumer appreciation for it may not be adequately attributed specifically to the brand in the marketplace but apparently more to other marketing activities in its name (i.e., marketing efforts do not help to enhance the brand).

The degree of correlation between CBBE and SBBE may be moderated by characteristics of product category. Following the salient difference cited above between dimensions of BAV in relation to SBBE, the researchers identify two separate factors of BAV: relevant stature (relevance + esteem + knowledge) and (energized) differentiation [7].

In more concentrated product categories (i.e., the four largest brands by market share hold a greater total share of the category), the positive effect of brand stature on SBBE is reduced. Relevance, esteem and knowledge may serve as particularly useful cues by consumers in fragmented markets, where it is more necessary for them to sort and screen among many smaller brands, thus to simplify the choice decision process. When concentration is greater, reliance on such cues is less required. On the other hand, when the category is more concentrated, controlled by a few big brands, it should be easier for consumers to compare between them and find aspects on which each brand is unique or superior. Indeed, Datta and colleagues find that in categories with increased concentration, differentiation has a stronger positive effect on SBBE.

For products characterised by greater social or symbolic value (e.g., more visible to others when used, shared with others), higher brand stature contributes to higher SBBE in the market. The researchers could not confirm, however, that differentiation manifests in higher SBBE for products of higher social value. The advantage of using brands better recognized and respected by others appears to be primarily associated with facets such as relevance and esteem of the brand.

Brand experience with hedonic products (e.g., leisure, entertainment, treats) builds on enjoyment, pleasure and additional positive emotions the brand succeeds in evoking in consumers. Sensory attributes of the product (look, sound, scent, taste, touch) and holistic image are vital in creating a desirable experience. Contrary to expectation of Datta and colleagues, however, it was not found that stature translates to higher SBBE for brands of hedonic products (even to the contrary). This is not so good news for experiential brands in these categories that rely on enhancing relevance and appeal to consumers, who also understand the brands and connect with them, to create sales-based brand equity in the marketplace. The authors suggest in their article that being personally enjoyable (inward-looking) may overshadow the importance of broad appeal and status (outward-looking) for SBBE. Nevertheless, fortunately enough, differentiation does matter for highlighting benefits of the experience of hedonic products, contributing to a raised sales-based brand equity (SBBE).

Datta, Ailawadi and van Heerde proceeded to examine how strongly CBBE corresponds with behavioural responses in the marketplace (elasticities) as manifestation of the anticipated impact of brand equity.

Results indicated that when relevant stature of a brand is higher consumers respond favourably even more strongly to price discounts or deals  (i.e.,  elasticity of response to promotional prices is further more negative or inverse). Yet, the expectation that consumers would be less sensitive (adverse) to increased regular prices by brands of greater stature was not substantiated (i.e., expected positive effect: less negative elasticity). (Differentiation was not found to have a positive effect on response to regular prices either, and could be counter-conducive for price promotions.)

An important implication of brand equity should be that consumers are more willing to pay higher regular prices for a brand of higher stature (i.e., a larger price premium) relative to competing brands, and more forgiving when such a brand sees it necessary to update and raise its regular price. The brand may benefit from being more personally relevant to the consumer, better understood and more highly appreciated. A brand more clearly differentiated from competitors with respect to its advantages could also benefit from a protected status. All these properties are presumed to enhance attachment to a brand, and subsequently lead to greater loyalty, making consumers more ready to stick with the brand even as it becomes more expensive. This research disproves such expectations. Better responsiveness to price promotions can help to increase sales and revenue, but it testifies to the heightened level of competition in many categories (e.g., FMCG or packaged goods) and propensity of consumers to be more opportunistic rather than to the strength of the brands. This result, actually a warning signal, cannot be brushed away easily.

  • Towards the end of the article, the researchers suggest as explanation that they ignored possible differences in response to increases and decreases in regular prices (i.e., asymmetric elasticity). Even so, increases in regular prices by stronger brands are more likely to happen than price decreases, and the latter already are more realistically accounted for in response to promotional prices.

Relevant stature is positively related to responsiveness to feature or promotional display (i.e., consumers are more inclined to purchase from a higher stature brand when in an advantaged display). Consumers also are more strongly receptive to larger volume of advertising by brands of higher stature and better differentiation in their eyes (this analysis could not refer to actual advertising messages and hence perhaps the weaker positive effects). Another interesting finding indicates that sensitivity to degree of distribution (on-shelf availability) is inversely associated with stature — the higher the brand stature from consumer viewpoint, larger distribution is less attractive to the consumers. As the researchers suggest, consumers are more willing to look harder and farther (e.g., in other stores) for those brands regarded more important for them to have. So here is a positive evidence for the impact of stronger brands or higher brand equity.

The research gives rise to some methodological questions on measurement of brand equity that remain open for further deliberation:

  1. Should the measure of brand equity in choice models rely only on a brand-specific intercept (expressing intrinsic assets or value of the brand) or should it include also a reflection of the impact of brand equity as in response to marketing mix activities?
  2. Are attitudinal measures of brand equity (CBBE) too gross and not sensitive enough to capture the incremental value added by the brand or is the measure of brand equity based only on a brand-intercept term in a model of actual purchase data too specific and narrow?  (unless it accounts for some of the impact of brand equity)
  3. How should measures of brand equity based on stated-choice (conjoint) data and actual purchase data be classified with respect to a consumer perspective? (both pertain really to consumers: either their cognition or overt behaviour).

Datta, Ailawadi and van Heerde throw light in their extensive research on the relation of consumer-based equity (CBBE) to behavioural outcomes, manifested in brand equity based on actual purchases (SBBE) and in effects on response to marketing mix actions as an impact of brand equity. Attention should be awarded to positive implications of this research for practice but nonetheless also to the warning alerts it may signal.

Ron Ventura, Ph.D. (Marketing)

Notes:

[1] How Well Does Consumer-Based Brand Equity Align with Sales-Based Brand Equity and Marketing-Mix Response?; Hannes Datta, Kusum L. Ailawadi, & Harald J. van Heerde, 2017; Journal of Marketing, 81 (May), pp. 1-20. (DOI: 10.1509/jm.15.0340)

[2] Brands and Branding: Research Findings and Future Priorities; Kevin L. Keller and Donald R. Lehmann, 2006; Marketing Science, 25 (6), pp. 740-759. (DOI: 10.1287/mksc.1050.0153)

[3] Developing and Validating a Multidimensional Consumer-Based Brand Equity Scale; Boonghee Yoo and Naveen Donthu, 2001; Journal of Business Research, 52, pp. 1-14.

[4]  Developing and Validating Measures of Facets of Customer-Based Brand Equity; Richard G. Netemeyer, Balaji Krishnan, Chris Pullig, Guangping Wang,  Mahmet Yageci, Dwane Dean, Joe Ricks, & Ferdinand Wirth, 2004; Journal of Business Research, 57, pp. 209-224.

[5] The authors name this dimension ‘energised differentiation’ in reference to an article in which researchers Mizik and Jacobson identified a fifth pillar of energy, and suggest that differentiation and energy have since been merged. However, this change is not mentioned or revealed on the website of BAV Group.

[6] A Conjoint Approach for Consumer- and Firm-Level Brand Valuation; Madiha Ferjani, Kamel Jedidi, & Sharan Jagpal, 2009; Journal of Marketing Research, 46 (December), pp. 846-862.

[7] These two factors (principal components) extracted by Datta et al. are different from two higher dimensions defined by BAV Group (stature = esteem and knowledge, strength = relevance and differentiation). However, the distinction made by the researchers as corroborated by their data is more meaningful  and relevant in the context of this study.

 

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The discipline of consumer behaviour is by now well versed in the distinction between System 1 and System 2 modes of thinking, relating in particular to consumer judgement and decision making, with implications for marketing and retail management. Much appreciative gratitude is owed to Nobel Prize Laureate in economics Daniel Kahneman for bringing forward the concept of these thinking systems to the knowledge of the wider public (i.e., beyond academics) in his book “Thinking, Fast and Slow” (2012). ‘System 1’ and ‘System 2’, though not always using these labels, have been identified and elaborated by psychologists earlier than Kahneman’s book, as the author so notes. However, Kahneman succeeds in making more crystal clear the concepts of these different modes of thinking while linking them to phenomena studied in his own previous research, most notably in collaboration with the late Amos Tversky.

In a nutshell: System 1’s type of thinking is automatic, associative and intuitive; it tends to respond quickly, but consequently it is at higher risk of jumping to wrong conclusions. It is the ‘default’ type of thinking that guides human judgement, decisions and behaviour much of the time. On the other hand, System 2’s type of thinking is deliberative, logical, critical, and effortful; it involves deeper concentration and more complex computations and rules. System 2 has to be called to duty voluntarily, activating rational thinking and careful reasoning. Whereas thinking represented by System 1 is fast and reflexive, that of System 2 is slow and reflective.

Kahneman describes and explains the role, function and effect of System 1 and System 2 in various contexts, situations or problems. In broad terms: Thinking of the System 1 type comes first; System 2 either passively adopts impressions, intuitive judgements and recommendations by System 1 or actively kicks-in for more orderly examination and correction (alas, it tends to be lazy, not in a hurry to volunteer). Just to give a taste, below is a selection of situations and problems in which Kahneman demonstrates the important differences between these two modes of thinking, how they operate and the outcomes they effect:

  • # Illusions (e.g., visual, cognitive)  # Use of memory (e.g., computations, comparisons)  # Tasks requiring self-control  # Search for causal explanations  # Attending to information (“What You See Is All There Is”)  # Sets and prototypes (e.g., ‘average’ vs. ‘total’ assessments)  # Intensity matching  # ‘Answering the easier question’ (simplifying by substitution)  # Predictions (also see correlation and regression, intensity matching, representativeness)  # Choice in opt-in and opt-out framing situations (e.g., organ donation)
  • Note: In other contexts presented by Kahneman (e.g., validity illusion [stock-picking task], choice under Prospect Theory), the author does not connect them explicitly to  System 1 or System 2 so their significance may only be indirectly implied by the reader.

In order to gain a deeper understanding of System 1 and System 2 we should inspect the detailed aspects differentiating between these thinking systems. The concept of the two systems actually emerges from binding multiple dual-process theories of cognition together, thus appearing to be a larger cohesive theory of modes of thinking. Each dual process theory is usually focused on a particular dimension that distinguishes between two types of cognitive processes the human mind may utilise. However, those dimensions ‘correlate’ or ‘co-occur’, and a given theory often adopts aspects from other similar theories or adds supplementary properties; the dual-system conception hence is built on this conversion. The aspects or properties used to describe the process in each type of system are extracted from those dual-process theories. A table presented by Stanovich (2002) helps to see how System 1 and System 2 contrast in various dual-process theories. Some of those theories are: [For brevity, S1 and S2 are applied below to refer to each system.)

  • S1: Associative system / S2: Rule-based system (Sloman)
  • S1: Heuristic processing / S2: Analytic processing (Evans)
  • S1: Tacit thought process / S2: Explicit thought process (Evans and Over)
  • S1: Experiential system / S2: Rational system (Epstein)
  • S1: Implicit inference / S2: Explicit inference (Johnson-Laird)
  • S1: Automatic processing / S2: Controlled processing (Shiffrin and Schneider)

Note: Evans and Wason related to Type 1 vs. Type 2 processes already in 1976.

  • Closer to consumer behaviour: Central processing versus peripheral processing in the Elaboration Likelihood Model (Petty, Cacioppo & Schumann) posits a dual-process theory of routes to persuasion.

Each dual process theory provides a rich and comprehensive portrayal of two different thinking modes. The theories complement each other but they do not necessarily depend on each other. The boundaries between the two types of process are not very sharp, that is, features of the systems are not all exclusive in the sense that a particular property associated with a process of System 1 may occur in a System 2 process, and vice versa. Furthermore, the processes also interact with one another, particularly in a way where System 2 relies on products of thought from System 1, either approving them or using them as a starting-point for further analysis. Nevertheless, occasionally System 2 may generate reasons for us merely to justify a choice made by System 1 (e.g., a consumer likes a product for the visual appearance of its packaging or its design).

Stanovich follows the table of theories with a comparison of properties describing System 1 versus System 2 as derived from a variety of dual process theories, but without attributing them to any specific theory (e.g., holistic/analytic, relatively fast/slow, highly contextualized/decontextualized). Comparative lists of aspects or properties have been offered by other researchers as well. Evans (2008) formed a comparative list of more than twenty attributes which he divided into four clusters (describing System 1/System 2):

  • Cluster 1: Consciousness (e.g., unconscious/conscious, automatic/controlled, rapid/slow, implicit/explicit, high capacity/low capacity)
  • Cluster 2: Evolution (e.g., evolutionary old/recent, nonverbal/linked to language)
  • Cluster 3: Functional characteristics (e.g.,  associative/rule-based, contextualized/abstract, parallel/sequential)
  • Cluster 4: individual differences (universal/heritable, independent of/linked to general intelligence, independent of/limited by working memory capacity).

Listings of properties collated from different sources (models, theories), interpreted as integrative profiles of System 1 and System 2 modes of thinking, may yield a misconception of the distinction between the two systems as representing an over-arching theory. Evans questions whether it is really possible and acceptable to tie the various theories of different origins under a common roof, suggested as an over-arching cohesive theory of two systems (he identifies problems residing mainly with ‘System 1’). It could be more appropriate to approach the dual-system presentation as a paradigm or framework to help one grasp the breadth of aspects that may distinguish between two types of cognitive processes and obtain a more comprehensive picture of cognition. The properties are not truly required to co-occur altogether as constituents of a whole profile of one system or the other. In certain domains of judgement or decision problems, a set of properties may jointly describe the process entailed. Some dual process theories may take different perspectives on a similar domain, and hence the aspects derived from them are related and appear to co-occur.

  • Evans confronts a more widely accepted ‘sequential-interventionist’ view (as described above) with a ‘parallel-competitive’ view.

People use a variety of procedures and techniques to form judgements, make decisions or perform any other kind of cognitive task. Stanovich relates the structure, shape and level of sophistication of the mental procedures or algorithms of thought humans can apply, to their intelligence or cognitive capacity, positioned at the algorithmic level of analysis. Investing more effort in more complicated techniques or algorithms entailed in rational thinking is a matter of volition, positioned at the intentional level (borrowed from Dennett’s theorizing on consciousness).

However, humans do not engage a great part of the time in thought close to the full of their cognitive capacity (e.g., in terms of depth and efficiency). According to Stanovich, we should distinguish between cognitive ability and thinking dispositions (or styles). The styles of thinking a person applies do not necessarily reflect everything one is cognitively capable of. Put succinctly, the fact that a person is intelligent does not mean that he or she has to think and act rationally; one has to choose to do so and invest the required effort into it. When one does not, it opens the door for smart people to act stupidly. Furthermore, the way a person is disposed to think is most often selected and executed unconsciously, especially when the thinking disposition or style is relatively fast and simple. Cognitive styles that are entailed in System 1, characterised as intuitive, automatic, associative and fast, are made to ease the cognitive strain on the brain, and they are most likely to occur unconsciously or preconsciously. Still, being intuitive and using heuristics should not imply a person will end up acting stupidly — some would argue his or her intuitive decision could be more sensible than one made when trying to think rationally; it may depend on how thinking in the realm of System 1 happens — if one rushes while applying an inappropriate heuristic or relying on an unfitting association, he or she could become more likely to act stupidly (or plainly, ‘being stupid’).

Emotion and affect are more closely linked to System 1. Yet, emotion should not be viewed ultimately as a disruptor of rationality. As proposed by Stanovich, emotions may fulfill an important adaptive regulatory role — serving as interrupt signals necessary to achieve goals, avoiding entanglement in complex rational thinking that only keeps one away from a solution, and reducing a problem to manageable dimensions. In some cases emotion does not disrupt rationality but rather help to choose when it is appropriate and productive to apply a rational thinking style (e.g., use an optimization algorithm, initiate counterfactual thinking). By switching between two modes of thinking, described as System 1 and System 2, one has the flexibility to choose when and how to act in reason or be rational, and emotion may play the positive role of a guide.

The dual-system concept provides a way of looking broadly at cognitive processes that underlie human judgement and decision making. System 1’s mode of thinking is particularly adaptive by which it allows a consumer to quickly sort out large amounts of information and navigate through complex and changing environments. System 2’s mode of thinking is the ‘wise counselor’ that can be called to analyse the situation more deeply and critically, and provide a ‘second opinion’ like an expert. However, it intervenes ‘on request’ when it receives persuasive signals that its help is required. Consideration of aspects distinguishing between these two modes of thinking by marketing and retail managers can help them to better understand how consumers conduct themselves and cater to their needs, concerns, wishes and expectations. Undertaking this viewpoint can especially help, for instance, in the area of ‘customer journeys’ — studying how thinking styles direct or lead the customer or shopper through a journey (including emotional signals), anticipating reactions, and devising methods that can alleviate conflicts and reduce friction in interaction with customers.

Ron Ventura, Ph.D. (Marketing)

References:

(1)  Thinking, Fast and Slow; Daniel Kahneman, 2012; Penguin Books.

(2) Rationality, Intelligence, and Levels of Analysis in Cognitive Science (Is Dysrationalia Possible); Keith E. Stanovich, 2002; in Why Smart People Can Be So Stupid (Robert J. Sternberg editor)(pp. 124-158), New Haven & London: Yale University Press.

(3) Dual-Processing Accounts of Reasoning, Judgment and Social Cognition; Jonathan St. B. T. Evans, 2008; Annual Review of Psychology, 59, pp. 255-278. (Available online at psych.annualreviews.org, doi: 10.1146/annurev.psych.59.103006.093629).

 

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It is usually not a pleasant feeling to be alone in a scary place or event — think of being stuck in a dark elevator or being involved in a car accident. People commonly seek to be with someone for comfort and company. But the companion does not always have to be another person. A research by Dunn and Hoegg (2014) provides corroboration that the need to share fear matters to humans while the identity of the companion, whether a person or an object, is less critical.  More specifically, sharing fear with a product from an unfamiliar brand may facilitate a quick emotional attachment with that brand without requiring to build a relationship over a lengthy period of time (1).

Fear is evoked by the presence or anticipation of a danger or threat. Feeling fear may be triggered by an unfamiliar event to which one is unsure how to respond (uncertainty) or an unexpected event at a specific moment (surprise); experiencing fear is furthermore likely when the event encountered is both unfamiliar and unexpected. It is important to note, nonetheless, that not every encounter with an unfamiliar or unexpected event necessarily leads to  fear. The Amygdala in the temporal lobe of the brain is the “centre” where fear arises. However, the amygdala like other brain structures is responsible for multiple functions. The amygdala is activated in response to unfamiliarity, unpredictability or ambiguity, but not every instance necessarily means the evocation of fear. For example, tension from facing an unfamiliar problem that one is at loss how to solve may not result in fear. Additionally, fear as well as other states of emotion are the outcome of appraisal of physical feelings (e.g., faster heartbeats, startle, warmth), considering the conditions in which they were triggered; it is a cognitive interpretation of their meaning (“why do I feel that way?”). Activation of other brain structures together with the amygdala may influence whether similar feelings triggered by an unexpected event are interpreted, for instance, as fear, anger, or surprise. The context in which an event occurs can matter a lot for the appraisal of emotions (2).

Dunn and Hoegg emphasise the emotional charge of consumer attachment with a brand versus cognitive underpinnings. Brand attachment has often been conceptualised as the product of a relationship between consumers and the target brand built over time. It should take a longer time to achieve a more solid brand attachment because of cognitive processes for establishing brand connections in memory and stronger favourable brand attitudes. However, this explanation is subject to criticism of missing the important role of emotions in bonding between consumers and a brand which does not necessarily require a long time. By focusing their studies on unfamiliar brands, Dunn and Hoegg intended to show that emotional attachment can emerge much more quickly when the consumers are distressed and are looking for a partner to share their fear with, and that partner or companion can be a brand of a given product.

On the same grounds, the researchers chose a scale of emotional attachment (Thomson, MacInnis and Park, 2005 [3]) as more appropriate over a scale that combines emotional and cognitive aspects of attachment and gives greater weight to cognitive constructs (Park, MacInnis et al., 2010 [4]). The emotional scale comprises three dimensions: (a) Affection (affectionate, friendly, loved, peaceful); (b) Passion (passionate, delighted, captivated); (c) Connection (connected, bonded, attached). Nevertheless, in the later research Park and MacInnis with colleagues offer a broader perspective that accounts for two bases of brand attachment: (i) a connection between self-concept and a brand; and (ii) brand prominence in memory.

While ‘brand prominence’ can be regarded as more cognitive-oriented (accessibility of thoughts and feelings in memory), a ‘brand-self connection’ entails the expansion of one’s concept of self to incorporate others, such as brands, within it — and that involves an emotional element. Park and MacInnis et al. emphasise the brand-self connection as the emotional core of their definition of brand attachment, while brand prominence is a facilitator in actualizing the attachment (analyses substantiate that brand attachment is a better predictor than attitudes of intentions to perform more difficult types of behavior reflecting commitment, and the brand-self connection is more essential for driving this behaviour). The three-dimension scale of emotional brand attachment seems very relevant for the research goals of Dunn and Hoegg, even though it is more restricted from a stand-point of the theoretical roots of brand attachment.

The desire to affiliate with others in scaring and upsetting situations is recognised as a mechanism for coping with negative emotions in those situations. Episodes of armed conflict, terrorist attacks, and natural disasters make people get closer to each other, unite and show solidarity. However, the researchers note that the act of affiliation is essential for coping rather than the affiliation target. That is, the literature on affiliation or attachment relates to interpersonal connections as well as attachment to objects (although objects are viewed as substitutes in absence of other persons [pet animals should also be considered]). We can find support for possible attachment to products and their brands in the human tendency to animate or anthropomorphise objects by assigning them traits of living beings, whether animals or humans. Brands may be animated in order to help consumers relate with them more comfortably, making them appear more vivid to them. It is one of the processes that facilitates the development of consumers’ relationships with their brands in use; consumers connect with brands also through the role brands fulfilled in their personal history, heritage and family traditions, and how brands integrate in their preferred lifestyles (5).

Dunn and Hoegg investigate how consumers connect with a brand on occasions of incidental fear. They make a clear distinction between events that may trigger fear (or other emotions) and fear appeals strategically planned in advertising (e.g., in order to induce a particular desired behaviour). Events that incidentally cause fear would be independent and uncontrolled. Additionally, the intensity and range of emotions felt is expected to differ when consumers actively participate in an event and hence experience it directly in contrast to watching TV ads — in direct consumer experiences, emotional feelings are likely to be more intensive and specific.  In a model for measuring consumption emotions developed and tested by Richins, fear is characterised as a negative and more active (as opposed to receptive) emotion, next to other emotions such as anger, worry, discontent, sadness and shame (6).

  • In their experiments, the researchers try to emulate incidental fear by displaying to participants clips from cinema films or TV series’ episodes, and present evidence that manipulations successfully elicited the intended emotions as dominant in response to each video clip. Yet, it remains somewhat ambiguous how real and direct the experience of watching scenes in a film or a TV programme is perceived and felt with regard to the emotions evoked.

The following are more concrete findings from the studies and their insights:

Emotional brand attachment is generated through perception that the brand shares the fear with the consumer — Study 1 confirms that emotional attachment with an unfamiliar brand is generated when a product (juice) by that brand is present and can be consumed during the fear-inducing experience (more than for emotions of sadness, excitement and happiness). But moreover, it is shown that the emotional attachment is mediated (conditioned) by perception of the consumer that the brand shared the fear with him or her.

Humans precede product brands —  Sharing fear with a brand contributes to stronger emotional brand attachment, but only if they still have a desire generated by fear to affiliate with others. If conversely that desire is satiated by a perception of the consumers that they are already socially affiliated with other people, the effect on brand attachment is muted.

  • Note: Participants in Study 2 were asked to perform a search with words related to feelings of affiliation and social connectedness (e.g., included, accepted, involved) to prime affiliation. Given the statements used to measure (non-)affiliation (e.g., “I feel disconnected from the world around me”), it is a little questionable how effective such a priming condition could be (though the authors show it was sufficient). It might have been more tangible to ask participants to think of people dear to them, family and close friends, and write about them.

Balancing negative and positive emotional effects on attitudes — Based on analyses in Study 2 the researchers also suggest that increased positive effect of emotional brand attachment may counterbalance and override a negative influence of ‘affect transfer’ on attitudes due to fear.

Presence of the brand and attention to it are required yet sufficient — Study 3 demonstrates that neither consumption of the product (juice) nor even touching it (the bottle), both forms of physical interaction, are really needed for feeling affiliated and forming emotional attachment — forced consumption in particular does not contribute to stronger perceived sharing or emotional attachment than merely seeing the product when feeling fear, that is making an eye contact and visually attending to the product in search for a companion. (Unexpectedly, in the case of action and excitement, consuming the drink increases emotional attachment.) Study 4 stresses, nevertheless, that the brand must be present during the emotional event for generating increased emotional attachment — having the brand nearby while experiencing the fear is essential for consumers to feel connected with the brand as their sharing partner (tested with a different product, potato chips).

The research paper suffers from a deficit in practice. That is, marketing managers and professionals might be disappointed to discover that it could be most difficult to have any control of those situations of incidental fear and to act on them to their advantage. In order to have any influence on the consumer a company would be required to anticipate an individual event in advance and to find a way to intervene (i.e., make their product present) without being perceived too intrusive or self-interested — two non-negligible challenges. An additional restriction is posed by the relation of the ‘fear effect’ to brands not previously familiar to the consumers.

Let us consider some potential scenarios where brands might benefit and the difficulties that are likely to arise in implementing it:

Undertaking medical treatments or tests — Some treatments can be alarming and frightening on occasion to different patients. A sense of fear is likely to enter already, and perhaps especially, while waiting. It is a opportunity for introducing the brand-companion in the waiting hall; even more so given that patients are usually not allowed to or prevented from using artifacts during the treatment (mostly no food and drinks). First, a company may have a difficulty to obtain access to places where patients wait for treatment. Second, consumers-patients are likely to bring products with them from home to entertain them (of brands they know). Third, patients often arrive with a family or friend companion, thus satisfying their need for affiliation with another person which dominates affiliation with an object. Still, there is room for ingenuity how to locate the brand close enough to the treatment episode (e.g., shops offering books or toys, especially for children, in the premises of a clinic or hospital).

Trekking or hiking in nature — Some routes, particularly in mountainous areas, can be quite adventurous, not to say dangerous. If a brand could find a way to introduce its product just before the consumer starts the hiking trip, it may benefit from being with him or her if fear arises. One problem is that hikers are advised and even required not to embark alone on more dangerous routes. Another problem is that those trekking or hiking sites often offer local brands, that while not being familiar to the consumers they also are not likely to be available to them at home, and thus the opportunity to develop a relationship based on the early emotional attachment is lost.

Offering legal, financial, insurance, and technical services in events of crisis — In various occasions of accidents, malfunctions, and disasters, people need help to cope with the crisis and the negative emotions it may evoke, particularly fear. A service provider would be expected to counsel the customer in his or her distress, and of course propose a solution (e.g. how to fix one’s home after a fire or an earthquake). Unfortunately,  one cannot make an eye contact with an intangible service. The company has to find creative and practical ways to make itself readily visible and accessible to the consumer when needed by offering instruments and cues for making contact (e.g., an alarm and communication device for the elderly and people with more risky medical conditions).

  • Dunn and Hoegg are aware of the limitation of the findings to unfamiliar brands. They reasonably propose that “because fear leads to a general motivation to affiliate, emotional brand attachment would be enhanced regardless of the familiarity with the brand” (p. 165). It should take further research, however, to substantiate this proposition.

Despite the possible difficulties companies will likely need to deal with, the doors are not completely shut to them to benefit from this phenomenon. But they must come up with creative and non-intursive solutions to make their brands and products present in the right place at the right time. At the very least, marketers should be aware of the potential effect of sharing fear with the consumer and understand how it can work in the brand’s benefit. It is worth remembering, after all, the saying “a friend in need is a friend indeed” whereby in some incidents the friend can be a brand.

Ron Ventura, Ph.D. (Marketing)

Notes:

(1) “The Effect of Fear on Emotional Brand Attachment”; Lea Dunn and JoAndrea Hoegg, 2014; Journal of Consumer Research, 41 (June), pp. 152-168.

(2) “What Is Emotion?: History, Measures and Meanings”; Jerome Kagan, 2007; New Haven and London: Yale University Press. Also see: “The Experience of Emotion”; Lisa Feldman Barrett, Bejta Mesquita, Kevin N. Ochsner, & James J. Gross, 2007; Annual Review of Psychology, 58, pp. 373-403.

(3) “The Ties That Bind: Measuring the Strength of Consumers’ Emotional Attachments to Brands”; Mathew Thomson, Deborah J. MacInnis, & C. Whan Park, 2005; Journal of Consumer Psychology, 15 (1), pp. 77-91.

(4) “Brand Attachment and Brand Attitude Strength: Conceptual and Empirical Differentiation of Two Critical Brand Equity Drivers”; C. Whan Park, Deborah J. MacInnis, Joseph Priester, Andreas B. Eisengerich, & Dawn Iacobucci, 2010; Journal of Marketing, 74 (November), 1-17.

(5) “Consumers and Their Brands: Developing Relationship Theory in Consumer Research”; Susan Fournier, 1998; Journal of Consumer Research, 24 (March), pp. 343-373.

(6) “Measuring Emotions in the Consumption Experience”; Marsha L. Richins, 1997; Journal of Consumer Research, 24 (September), pp. 127-146.

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Surveys, being a major part of marketing research, seem to be in perpetual movement of change and development. Many of the changes in recent years are tied with technological advancement. About fifteen years ago online surveys — delivered over the Internet — began to rise as a dominant mode of survey administration; but now, researchers are pushed to perform more of their surveys via mobile devices, namely smartphones and tablets, in addition or as a replacement to being administered on desktop and laptop computers.

Yet some important distinctions between those two modes can make the transfer of surveys between them flawed. Just as much as it was wrong to suggest in the past that survey questionnaires administered in face-to-face interviews could be seamlessly transferred to phone interviews, it would be wrong today to suggest a seamless transfer of surveys from web browsers on desktops/laptops to mobile browsers (or apps).

In the latest Greenbook Research Industry Trends (GRIT) Report of Q3-Q4 2015, the authors suggest that there is still much room for improvement in adjusting online survey questionnaires to run and display properly also on mobile devices. They find that 45% of their respondents on the research supplier side and 30% on the research buyer (client) side claim that their companies design at least three quarters (75%-100%) of their online surveys to work effectively on mobile phones; however, “that tells us that over 50% of all  surveys are NOT mobile optimized” (p. 14, capital letters are in origin). The authors hereby implicitly call on marketing researchers to do much more to get their online surveys fully mobile-optimized. But this is not necessarily a justified or desirable requirement because not all online surveys are appropriate and applicable to be answered on smartphones nor on tablets. There could be multiple reasons for a lack of match between these modes for administering a particular survey: the topic, the types of constructs measured and instruments being used, the length of the questionnaire, and the target population relevant for the research. Consumers use mobile devices and personal computers differently (e.g., purpose, depth and time) which is likely to extend also to how they approach surveys on these products.

  • The GRIT survey of marketing researchers was conducted in a sample of 1,497 respondents recruited by e-mail and social media channels, of whom 78% are on the supplier-side and 22% on the client-side. Nearly half (46%) originate in North-America and a little more than quarter (27%) come from Europe.

Concerns about coverage and reach of a research population have followed online surveys from the beginning. Of different approaches for constructing samples, including sampling frames (e.g., e-mail lists) and ad-hoc samples (i.e., website pop-up survey invitations), the panel methodology has become most prevalent. But this approach is not free of limitations or weaknesses. Panels have a ‘peculiar’ property: If you do not join a panel you have zero probability of being invited to participate in a survey. Mobile surveys may pose again similar problems, and perhaps even more severely, because users of smartphones (not every mobile phone is able to load surveys), and moreover tablets, constitute a sub-population that is not broad enough yet and the users also have rather specific demographic and lifestyle characteristics.

  • Different sources of contact data and channels are being used to approach consumers to participate in surveys. Companies conduct surveys among their customers for whom they have e-mail addresses. Subscribers to news media websites may also be included a in survey panel of the publisher. Members of forums, groups or communities in social media networks may be asked as well to take part in surveys (commissioned by the administrator).

Decreasing response rates in phone and face-to-face surveys has been an early drive of online surveys; these difficulties have got only worse in recent years so that online surveys remain the viable alternative, and in some situations are even superior. Online self-administered questionnaires (SAQ) of course have their own genuine advantages such as ability to present images and videos, interactive response tools and greater freedom to choose when to fill the questionnaire. However, as with former modes of data collection for surveys, response behaviour may differ between online surveys responded to on personal computers and on mobile devices (one should consider the difficulty to control what respondents do when filling SAQs on their own).

The GRIT report reveals that the greatest troubling aspects of panels for marketing researchers are the quantity and quality of respondents available through those sampling pools (top-2-box satisfaction: 36% and 26%, respectively). In particular, 33% are not at all satisfied or only slightly satisfied with the quality of respondents. The cost of panel is also generating relatively low satisfaction (top-2-box 34%). Marketing researchers are more satisfied with timeliness of fielding, purchase process, ease of accessing a panel and customer service (49%-54%). [Note: 33% is compared with ~20% for ‘quantity’ and ‘cost’ and ~12% on other aspects.]

The GRIT report further identifies four quadrants of panel aspects based on satisfaction (top-2-box) versus (derived) importance. The quality and quantity of respondents available in panels occupy the ‘Weaknesses’ quadrant as they generate less satisfaction while being of higher importance. Customer service and purchase process form ‘Key Strengths’, being of higher importance and sources of higher satisfaction. Of the lower-importance aspects, cost is a ‘Vulnerability’ whereas access and timeliness are ‘Assets’. The ‘Weaknesses’ quadrant is troubling especially because it includes properties that define the essence of the panel as a framework for repeatedly extracting samples, its principal purpose. The assets and strengths in this case may not be sufficient to compensate for flaws in the product itself, the panel.

Surveys allow researchers to study mental constructs, cognitive and affective: perceptions and beliefs, attitudes, preferences and intentions; they may broadly look onto thoughts, feelings and emotions. Survey questionnaires entail specialised methods, instruments and tools for those purposes. Furthermore, surveys can be used to study concepts such as logical reasoning, inferences, relations and associations established by consumers. In the area of decision-making, researchers can investigate processes performed by the consumers or shoppers, as reported by them. Advisedly, the findings and lessons on decision processes may be validated and expanded by using other types of methods such as verbal protocols, eye tracking and mouse tracking (web pages) as research participants perform pre-specified tasks. However, surveys should remain part of the research programme.

Much of the knowledge and understanding of consumers obtained through surveys cannot be gained from methods and techniques that do not directly converse with the consumers. Data from recording of behaviour or measures of unconscious responses may lack important context from the consumer viewpoint that may render those findings difficult to interpret correctly. Conscious statements of consumers on their thoughts, feelings, experiences and actions may not be fully accurate or complete but they do represent what they have in mind and often enough guide their behaviour — we just need to ask them in an appropriate and methodic way.


The examples below are brought to demonstrate why different approaches should be used collaboratively to complement each other, and how surveys can make their own contribution to the whole story:

  •  Volumes of data on actions or operations performed by consumers, as entailed in the framework of Big Data, provide ‘snapshots’ or ‘slices’ of behaviour, but seem to lack the context of consumer goals or mindsets to meaningfully connect them. One has indirectly to infer or guess what made the behaviour occur as it did.
  • Big Data also refers to volumes of verbatim in social media networks where the amount of data gives an illusion that it can replace input from surveys. However, only surveys can provide the kind of controlled and systematic measures of beliefs, attitudes and opinions needed to properly test research propositions or hypotheses.
  • Methods of neuroscience inform researchers about neural correlates of sensory and mental activity in specific areas of the brain, but it does not tell them what the subject makes of those events. In other words, even if we can reduce thoughts, feelings and emotions to neural activity in the brain, we would miss the subjective experience of the consumers.

 

It is not expected of marketing researchers to turn all their online surveys to mobile devices, at least not as long as these co-exist with personal computers. The logic of the GRIT’s report is probably as follows: Since more consumers spend more time on smartphones (and tablets), they should be allowed to choose and be able to respond to a survey on any of the computer-type products they hold in time and place convenient to them. That is indeed a commendable liberal and democratic stance but it is not always in best interest of the survey from a methodological perspective.

Mobile surveys could be very limiting in terms of the amount and complexity of information a researcher may reliably collect through them. A short mobile survey (5-10 minutes at most) with questions that permit quick responses is not likely to be suitable to study adequately many of the constructs previously discussed to build a coherent picture of consumers’ mindsets and related behaviours. These surveys may be suitable for collecting particular types of information, and perhaps even have an advantage at this as suggested shortly.

According to the GRIT report, 36% of researchers-respondents estimate that online surveys their companies carry out take on average up to 10 minutes (short); 29% estimate their surveys take 11-15 minutes (medium); and 35% give an average estimate of 16 minutes or more (long). The overall average stands at 15 minutes.

These duration estimates correspond to online surveys in general and the authors note that particularly longer surveys would be unsuitable for mobile surveys. For example, 16% of respondents state their online surveys take more than 20 minutes which is unrealistic for mobile devices. At the other end, very short surveys (up to five minutes) are performed by 10%.

There are some noteworthy differences between research suppliers and clients. The main finding to notice is that clients are pressing to shorter surveys, such that may also be applicable to respond to on mobile devices:

  • Whereas just near to 10% of suppliers perform surveys of up to 5 minutes on average, a little more of 15% of clients perform surveys of this average length.
  • Suppliers are more inclined to perform surveys of 11-15 minutes on average (approx. 33%) compared with clients (about 23%).
  • Suppliers also have a little stronger propensity for surveys of 16-20 minutes (20% vs. 16% among clients).

Researchers on the supplier side appear to be more aware and sensitive to the time durations online surveys should take to achieve their research objectives and are less ready to execute very short surveys as clients drive to.

  • Interestingly, the report shows that the average estimated time length in practice is similar to the maximal length respondents think an online survey should take. The authors propose these results can be summed up as “whatever we answered previously as the average length, is the maximal length”. They acknowledge not asking specifically about mobile surveys — the accepted maximum is 10 minutes. This limit is more in accordance with clients’ stated maximum for online surveys (52%) whereas only 36% of suppliers report such a goal (32% of suppliers choose 11-15 minutes as the maximum, above the expected maximum for mobile).

Online surveys designed for personal computers are subject to time limits, in view of respondents’ expected spans of attention, yet the limits are expected to be less strict compared with mobile devices. Furthermore, the PC mode allows more flexibility in variability and sophistication of questions and response scales applied. A smartphone does not encourage much reflective thought and this must be taken into consideration. Desktops and laptops accommodate more complex tasks, usually executed in more comfortable settings (e.g., consumers tend to perform pre-purchase ‘market research’ on the their personal computers and conduct quick queries of the last-minute during the shopping trip on their smartphones) — this works also to the benefit of online surveys on personal computers. (Tablets are still difficult to position, possibly closer to laptops than to smartphones.)

Online surveys for mobile devices and for desktops/laptops do not have to be designed to be the same in content of questionnaires (adapting appearance to device and screen is just part of the matter). First, there is justification to design surveys specifically for mobile devices. These surveys may be most suitable for studying feedback on recent events or experiences, measuring responses to images and videos, and performing association tests. Subjects as proposed here are afforded in common by System 1 (Automatic) — intuition and quick responses (immediacy), emotional reactions, visual appeal (creativity), and associative thinking.

Second, it would be better to compose and design separate survey questionnaires for personal computers and for mobile devices at different lengths. Trying to impose an online survey of fifteen minutes on respondents using mobile devices is at considerable risk of early break-off or worse of diminishing quality of responses as the survey goes on. At least a short version of the questionnaire should be channeled to the mobile device — though it still would not resolve issues of unfitting types of questions posed. Even worse, however, would be an attempt to shorten all online surveys to fit into the time spans of mobile surveys because this could make the surveys much less effective and useful as sources of information and miss much of their business value.

Marketing researchers have to invest special effort to ensure that online surveys remain relevant and able to provide useful and meaningful answers to marketing and business questions. Reducing and degrading surveys just in order to obtain greater cooperation from consumers will only achieve the opposite — it will strengthen the position of the field of Big Data (that worries some researchers), as well as other approaches that navigate the unconsciousness. Instead, marketing researchers should improve and enhance the capabilities of surveys to provide intelligent and valuable insights, achieved particularly by designing surveys that are best compatible with the mode in which the survey is administered.

Ron Ventura, Ph.D. (Marketing)

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The concept of brand attachment has become a frequent, almost integral component of attitudinal models of brand equity in commercial studies since the late 1990s. It has been introduced to represent an emotional bond that is expected to build between a brand and consumers to allow for their sustainable loyalty to the brand. Perceived quality and other assessments of a rational nature about branded products and services are generally not regarded as sufficient to connect a consumer with a brand. In addition, brand attachment is meant to represent a disposition towards a brand that is more solid and enduring regarding consumer-brand relations than brand attitude. However, what signifies and distinguishes that construct has not been properly and agreeably defined.  In a recent seminal article (2010), Park and MacInnis of the University of Southern California and their colleagues (*) offer an approach to fill this caveat coherently. The researchers define the construct of brand attachment, test and demonstrate how it differs from brand attitude strength.

We may find a spectrum of relationships between consumers and brands at different levels of depth and strength. What creates, for example, the deep attraction, to an extent of passion, of consumers to brands like Nike or Apple? On the contrary, the brand Nokia of mobile phones has for the past few years lost its favour with consumers. Last month it was revealed that Microsoft, which had acquired the mobile division from the Finnish mother company, intends to abolish the Nokia brand name but retain the “Lumia” name for new models of smart-mobile devices (e.g., phones, tablets, and whatever comes next); if indeed brand attachment by consumers to Nokia has diminished, no one would shed a tear. Coca Cola almost ruined its brand equity in 1985 due to its New Coke ordeal — apparently consumers were insistent on their attachment to the brand and what it represented to them to force the company to step back and save the brand. Brand attachment captures the affective linkage that is created between a brand and its customers.

A brand equity model may start from awareness of and basic familiarity with the brand of interest at its ground. On top of which should come associations of product attributes and functional benefits (tangible product assets) next to “softer” associations of feelings or personality traits assigned to the brand (intangible assets). After accounting for these building blocs, a bridge of attachment can be erected between the consumers and the brand, leading to commitment (a manifest of attitudinal loyalty). Several facets can be proposed based on pervious academic and applied research in the field to represent brand attachment: (a) respect for the brand and its leadership; (b) personal identification with the brand; (c) favourability of brand legacy and values; and possibly also (d) appreciation of how the brand treats its customers.

Park and MacInnis et al. develop a scale of brand attachment that formally specifies aspects of brand-self connection — it emphasises identification of the consumer with the brand; yet to this factor they add a second factor of brand prominence in memory. Thus, they suggest a scale constructed from two factors; they show that treating the scale as a composition of the two components has better validity than a single-unified scale. Furthermore, the authors demonstrate the effect of brand attachment on behavioural intentions as well as actual behaviour (self-reported and as registered in customer database records).  They cover a range of activities or actions that differ in their level of difficulty.  It is shown that brand attachment is able to predict the intention to perform the more difficult types of behaviour that brand attitude strength cannot.

Brand attitude strength is measured by the valence of an attitude (positive-negative) weighted by the confidence with which the consumer holds that attitude. However, research repeatedly has shown that attitudes get to impact behaviour when the valence is more extreme in either direction and confidence is strong. Attitudes do have an affective basis but it is generally sublime and concerned primarily with valence. That is, brand attitude alone does not contain a scope of emotions people may exhibit; it is very limited in its emotional capacity. Brand attachment, on the other hand, is more emotionally charged and can tell a better story about the relation of the consumer to the brand. Park and MacInnis et al. conceptually define brand attachment as “the strength of the bond connecting the brand with the self” (p. 2). This bond materializes when it is supported by a rich and accessible network of positive thoughts and feelings about the brand in the consumer’s memory.  A brand-self connection ascribes to the extent to which a consumer identifies with a brand as if they could merge together. In other words, the self (concept) of the consumer is extended so as to absorb the brand and make it part of his or her own self (image or goals). While the representation is cognitive, the researchers note, the brand-self linkage is inherently emotional. Brand prominence indicates in addition the ease and frequency with which  thoughts and feelings (underlying the connection) are brought to the consumer’s mind. The brand-self connection can “come to life” more readily when brand prominence is greater, hence the consumer experiences a stronger brand attachment.

  • The researchers first constructed a scale with five items for each of the two components. However, they sought to make the scale more parsimonious and practical to implement, and proposed a reduced scale of two items for brand-self connection and two items for brand prominence. Looking at the factor loadings suggests that it would be justified to keep four items for the first component and three items for the second. But in the researchers’  judgement parsimony should win over. For example, the item “feel emotionally bonded” could be discarded in favour of “feel personally connected”.

In their analyses, Park and MacInnis and their colleagues confirm that brand attachment and brand attitude strength are related yet empirically distinct constructs — while correlation between them is moderate-high they cannot be confounded. This supports the convergent and discriminant validity of brand attachment. The authors provide further support for the validity of attachment by showing an interesting relation to separation distress, a negative emotional state that may occur when losing a relationship with an entity people felt close to (e.g., feelings of depression, anxiety and loss of self). Brand-self connection and prominence each independently “contribute to the prediction of separation distress as indicators of brand attachment” (p. 8). The research additionally substantiates that brand attachment is distinct from attitude strength, the former being more strongly associated with separation distress.

Eventually, marketers would want to know how brand attachment is linked to behaviour. Three categories of difficulty are distinguished: (1) Among the most difficult forms of behaviour are buying always the new model of brand X, waiting to buy brand X versus an alternative brand, and spending money, time and energy to promote brand X (e.g., in pages and forums of social media and in blogs). (2) Moderately difficult forms of behaviour include paying a price premium for brand X and defending it when others speak bad of it. (3) The least difficult modes of behaviour include, for example, recommending brand X to others and buying the brand for others. Notably, recommending a brand to relatives or friends involves a certain personal risk for the endorser because one puts his or her own reputation or credibility on-line by suggesting to others to buy and use the particular brand. Yet, this alone is not considered hereby as a major cause of difficulty vis-á-vis the investment of time, money or energy to promote the brand (e.g., tell a story in a blog post, add photos).

With respect to intention to behave in ways that favour a brand (reflecting brand commitment) it is found that brand attachment predicts the intention to engage in behaviours regarded as the most difficult remarkably better than brand attitude strength. Brand attachment also better predicts intention to behave in moderately difficult ways but the difference from attitude strength, although also statistically significant, is rather small. There is no significant difference between attachment and attitude strength in predicting intention of performing the least difficult behaviours — they do equally well.  These findings bolster the importance of addressing brand attachment as a driver of brand commitment, particularly via more demanding modes of behaviour.

  • An additional test suggests that brand prominence is less essential than the brand-self connection component in predicting intentions. (Intentions were tested with respect to Nike.)
  • In a different set of analyses of actual behaviour (banking-investments), the researchers found furthermore that brand attachment is a better predictor of past purchases than brand attitude strength. In this case, however, brand attachment represented by both brand-self connection and brand prominence is predicting behaviour better than the former alone. That is, with regard to actual behaviour, brand prominence is an essential component.

Many brand owners would find utility in applying this scale of brand attachment (in a full or reduced form): from food (e.g., Nestlé) or toys (e.g., Lego) to banking (e.g., Royal Bank of Scotland) or carmakers (e.g., Peugeot). Take for instance Microsoft that now holds four brand names they may apply for marketing mobile devices: their own corporate name, Surface, Nokia or Lumia. Microsoft could use the aid of such a scale to decide which brand proves as better ground to build upon and which name is better eliminated. It may be a major factor in the contest of brand equity for mobile-smart devices of Microsoft versus Apple, Samsung Electronics, and Lenovo (Motorola).

Although the brand strength construct may capture a brand’s mind share of a consumer, attachment is uniquely positioned to capture both heart and mind share (p. 14).

The scale of brand attachment constructed by Park and MacInnis and their colleagues emphasises consumer identification with a brand, representing an emotional connection, and actualised through its prominence in memory. It does not cover other possible sources of attachment, but the approach taken is focused, concrete and well-substantiated. The researchers provide a valid scale for practitioners in brand management and research for measuring brand attachment, stand-alone or as part of a brand equity model.

Ron Ventura, Ph.D. (Marketing)

(*) Brand Attachment and Brand Attitude Strength: Conceptual and Empirical Differentiation of Two Critical Brand Equity Drivers; C. Whan Park, Deborah J. MacInnis, Joseph Priester, Andreas B. Eisingerich, & Dawn Iacobucci, 2010; Journal of Marketing, 74 (November), pp. 1-17.

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We can think of visual images in different forms. Pictorial images like a painting, a photograph or a drawing often depict a congruous scene of figures, objects and background, telling a story, enclosed in a frame. An image in a marketing context may represent product objects, people (e.g., customers, sellers, models, endorsers), a view of the scene of a retail store, etc.. But we may also refer to the visual image of a print advertisement as a visual scene that displays a complex layout of pictorial images, brand logo, text and additional graphic elements of decoration. Rather frequently the ad would show portions of pictorial images (like ‘clip-arts’) embedded in the whole scene, and the spatial arrangement of its objects or elements appears as discontinuous. Visual images may further be related with product packages, website pages on the Internet, video, or the view of a store’s front window and its interior space when one is present on premises of the physical site. Viewing a visual image  is an experience that may be, for example, enjoyable, challenging, annoying or disturbing. If the image leaves us indifferent, however, we would not spend enough time to figure out what we experience.

Lindt ChocolateWhen the object of a researcher’s study is a visual marketing material like an ad or product packaging it is most sensible to show the actual material or a pictorial image of it to consumers participating in the study. It is essentially more reliable for measuring affective and cognitive responses going beyond elementary memory-based measures of awareness. As we try to measure consumers’ recall of detail in an ad’s scene, its accuracy tends to decrease sharply and therefore any further references to content asked from respondents are likely to be of low reliability. The same is true when studying response to a retail scene — we should bring the research participants to the brick-and-mortar site itself, show them photographic images of its scene (i.e., layout, design, merchandise display) or computer-simulated images for a store in planning. Presenting an image of the material or retail scene is likely to enable researchers to capture emotion-laden responses more varied in type and intensity, and reach greater depth in the thoughts and feelings evoked in consumers-viewers vis-a-vis reliance on memory or mental images re-constructed by participants in their minds.

Pictorial images may be used productively, nonetheless, also if they do not appear related to a focal product, brand or company. A visual image can be utilised as an implicit bridge that helps to connect consumers’ mindsets with a brand of interest and to open-up the respondents to engage in a dialogue with an interviewer about personal or more private aspects of their lives (e.g., how a brand may function in the relations between a parent and his or her children). Relevant pictures with respect to the topic of research may be introduced by the interviewer or the interviewee. Professor of marketing Gerald Zaltman (Harvard Business School / Olson Zaltman Associates consulting firm) advises that pictorial images can help consumers to reveal and reflect attributes of a focal brand or company even though on surface the image shows no relation to that brand; the image serves as a metaphor whereby figures or objects in the image substitute for the brand (e.g., a gorilla has been shown by purchasing agents to suggest that managers from the vendor company have been stiff and stubborn in negotiations with them or  have demonstrated insensitivity to their needs). In Zaltman’s technique of metaphor elicitation (ZMET) the consumers bring pictorial images of their choice to their interviews through which they may describe the brand or tell a story about the role it plays in their lives (1).

Advertisements compete eagerly for grabbing the attention of consumers against editorial content as well as other ads in their own product category or in any other domain. It is a tough and demanding competition. The methodology of eye tracking, enhanced by advanced technology for taking different measures of eye movement and fixations, is especially suited for studying what captures attention to the ad and how information is attended to and could be utilised within the ad scene. It is generally assumed that the longer the latency of fixation on an object or element, the more thought a viewer dedicates to it, though the technique cannot directly reveal much more about the nature of affective reactions or cognitive processes.

Important and useful insights have been gained through eye tracking research. An extensive research by Pieters and Wedel (2) shows, for example, that the power of text to capture attention is sensitive to the surface size of its text-body but a picture can capture attention fast almost regardless of its size. Hence it is unnecessary for advertisers to fill an ad copy with larger pictures in expectation that it would increase the chances of capturing attention to the picture and to the ad as a whole. For text, however, surface size, determined by amount of text or font size, is significant (e.g., consider magazine ads that combine a colourful and vivid picture on top and a body of text of some explanation beneath it for achieving maximum effect). Regarding brand logos, it is found that the surface size of the logo is likely to distract viewers from reading text. However, greater interest in a brand logo for any other quality (e.g., the brand itself) can increase interest in reading the text, and secondarily, watching the pictures in the print ad. Text is attended by viewers of print ads particularly more elaborately when viewers have a declared goal of buying a product of the type advertised (Rayner and Castelhano, 3); this is compared with a task when viewers are asked just to rate an ad — then pictures get to play a greater role in viewer attention (i.e., number of fixations and time spent observing and processing). Consumers are more interested in text portions of a print ad that provide information on a focal product relative to pictures when a purchase of product of that type is seen expected.

In order to characterise more concretely the processing of visual information and better understand the valence and content of feelings and thoughts, the investigation process of research has to continue with other methods (e.g., experiments, interviews with probing). The approach I put forward aims to provide such expansion of insights: the technique allows to attach additional information reported by viewers to objects or elements they choose and relate to in the visual material (e.g., a print ad, a photograph). Its starting point is based on visual thinking rather than verbal explications, therefore I named it Visual Impression Metrics. The following chart of a framework model of communication depicts plausible factors that may trigger the processing of ‘objects’ in a visual marketing material from the consumers’ point-of-view:

Two notes to the chart: (1) The combination of verbal and visual elements that correspond with each other is fundamental to encoding; (2) From an information processing perspective, consumers may go back and forth between attention to and processing of various elements or objects in the whole image.

A pivotal strength of eye tracking is the ability to trace when attention is awarded unconsciously to objects in the ad in addition to conscious attention — viewers transit between these processes as they move from bottom-up to top-down (and vice versa) processing of the information found in the visual material. A consequence of this, however, is that respondents are not likely to be able to comment on objects they attended to unconsciously. An approach as described above, while more reliant on conscious processes, may be used in conjunction with eye tracking so as to shed more light on how consumers-viewers utilise information from objects in the visual scene, their meanings or implications for them.

In the other realm of research using visual images, a pictorial image is utilised as an aid to enquiring on a topic or concept rather than being the subject of research. An interviewer may show the respondent a picture selected by the research team and invite him or her to discuss it (e.g., what they see in the picture, what it reminds them of, what associations it brings up about a product/brand). When showing the same picture to a group or sample of respondents, it is possible to compare and aggregate how various consumers relate and react to the same image. On the other hand, a picture retrieved and brought by each consumer-respondent is much more capable to entail an idea associated with a brand that is meaningful and relevant to that individual. Gerald Zaltman’s method for eliciting metaphors by visual images is most appropriate to that end — it is free of the assumptions or expectations of the marketers or researchers. But on looking at the interviewing process, it is apparent that separating the thoughts of the interviewer from those of the interviewee is not obvious. A main theme of the instructions of Zaltman to interviewers for probing, as demonstrated in his book “How Customers Think” (Chapter 4 Appendix), is to avoid offering an interviewee their own explanations or interpretations of a reply just given by him or her nor implying their own understanding of the picture. An effective probing approach is to follow-up on a last reply of the interviewee using his or her own words (4). The line between desired and flawed probing in examples given, however, is not always sharp and clear — one needs to carefully make the vital distinction between guiding the interviewee (right) and leading the interviewee (wrong).

Selecting a pictorial image as a stimulus to trigger an “enquiry” in a survey (i.e., quantitative research) needs to be done by careful screening and examination, guided by pre-tests and/or qualitative research techniques, in order to present a picture that conveys the target concepts one wishes to study or test. Vice versa, key constructs (e.g., emotions, thoughts or associations) revealed in a qualitative study by using visual images should be substantiated through quantitative methods for the relevant target population of consumers. Thus, researchers would choose for a survey a pictorial image they appraise, according to findings of the qualitative study, as the best representative or conveyor of the concept of interest shared by the consumers. The method of Visual Impression Metrics, for instance, is suitable for certifying whether focal figures or objects as portrayed in the image scene carry the expected meaning.

The possibilities for research with visual images are numerous; they offer some intriguing opportunities for enriching our consumer insights. Visual images evoke more quickly intuitive and emotional responses, they often succeed in encouraging people to share their thoughts and feelings, and may engage forms of visual thinking that differ from verbal thinking. Depending on context and purpose, visual images can be used in marketing research to enhance the quality, reliability and validity of our findings, and thereby improve the knowledge of marketers about their consumers.

Ron Ventura, Ph.D. (Marketing)

 

Notes:

(1) “How Customers Think: Essential Insights into the Mind of the Market”, Gerald Zaltman, 2003, Boston, MA: Harvard Business School Press.

(2) “Attention Capture and Transfer in Advertising: Brand, Pictorial and Text-Size Effects”, Rik Pieters and Michel Wedel, 2004, Journal of Marketing, 68 (Apr.), pp. 36-50.

(3) “Eye Movements During Reading, Scene Perception, Visual Search, and While Looking at Print Advertisements”, Keith Rayner and Monica S. Castelhano, 2008; In Visual Marketing: From Attention to Action, Michel Wedel and Rik Pieters (eds.)[pp. 9-42], London, New-York: Lawrence Erlbaum Associates.

(4) Ibid. 1.

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