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Posts Tagged ‘Personality’

Revelations about the Facebook – Cambridge Analytica affair last month (March 2018) invoked a heated public discussion about data privacy and users’ control over their personal information in social media networks, particularly in the domain of Facebook. The central allegation in this affair is that personal data in social media was misused for the winning political presidential campaign of Donald Trump. It offers ‘juicy’ material for all those interested in American politics. But the importance of the affair goes much beyond that, because impact of the concerns it has raised radiates to the daily lives of millions of users-consumers socially active via the social media platform of Facebook; it could touch potentially a multitude of commercial marketing contexts (i.e., products and services) in addition to political marketing.

Having a user account as member of the social media network of Facebook is pay free, a boon hard to resist. Facebook surpassed in Q2 of 2017 the mark of two billion active monthly users, double a former record of one billion reached five years earlier (Statista). No monetary price requirement is explicitly submitted to users. Yet, users are subject to alternative prices, embedded in the activity on Facebook, implicit and less noticeable as a cost to bear.

Some users may realise that advertisements they receive and see is the ‘price’ they have to tolerate for not having to pay ‘in cash’ for socialising on Facebook. It is less of a burden if the content is informative and relevant to the user. What users are much less likely to realise is how personally related data (e.g., profile, posts and photos, other activity) is used to produce personally targeted advertising, and possibly in creating other forms of direct offerings or persuasive appeals to take action (e.g., a user receives an invitation from a brand, based on a post of his or her friend, about a product purchased or  photographed). The recent affair led to exposing — in news reports and a testimony of CEO Mark Zuckerberg before Congress — not only the direct involvement of Facebook in advertising on its platform but furthermore how permissive it has been in allowing third-party apps to ‘borrow’ users’ information from Facebook.

According to reports on this affair, Psychologist Aleksandr Kogan developed with colleagues, as part of academic research, a model to deduce personality traits from behaviour of users on Facebook. Aside from his position at Cambridge University, Kogan started a company named Global Science Research (GSR) to advance commercial and political applications of the model. In 2013 he launched an app in Facebook, ‘this-is-your-digital-life’, in which Facebook users would answer a self-administered questionnaire on personality traits and some personal background. In addition, the GSR app prompted respondents to give consent to pull personal and behavioural data related to them from Facebook. Furthermore, at that time the app could get access to limited information on friends of respondents — a capability Facebook removed at least since 2015 (The Guardian [1], BBC News: Technology, 17 March 2018).

Cambridge Analytica (CA) contracted with GSR to use its model and data it collected. The app was able, according to initial estimates, to harvest data on as many as 50 million Facebook users; by April 2018 the estimate was updated by Facebook to reach 87 millions. It is unclear how many of these users were involved in the project of Trump’s campaign because CA was specifically interested for this project in eligible voters in the US; it is said that CA applied the model with data in other projects (e.g., pro-Brexit in the UK), and GSR made its own commercial applications with the app and model.

In simple terms, as can be learned from a more technical article in The Guardian [2], the model is constructed around three linkages:

(1) Personality traits (collected with the app) —> data on user behaviour in Facebook platform, mainly ‘likes’ given by each user (possibly additional background information was collected via the app and from the users’ profiles);

(2) Personality traits —> behaviour in the target area of interest — in the case of Trump’s campaign, past voting behaviour (CA associated geographical data on users with statistics from the US electoral registry).

Since model calibration was based on data from a subset of users who responded to the personality questionnaire, the final stage of prediction applied a linkage:

(3) Data on Facebook user behaviour ( —> predicted personality ) —>  predicted voting intention or inclination (applied to the greater dataset of Facebook users-voters)

The Guardian [2] suggests that ‘just’ 32,000 American users responded to the personality-political questionnaire for Trump’s campaign (while at least two million users from 11 states were initially cross-referenced with voting behaviour). The BBC gives an estimate of as many as 265,000 users who responded to the questionnaire in the app, which corresponds to the larger pool of 87 million users-friends whose data was harvested.

A key advantage credited to the model is that it requires only data on ‘likes’ by users and does not have to use other detailed data from posts, personal messages, status updates, photos etc. (The Guardian [2]). However, the modelling concept raises some critical questions: (1) How many repeated ‘likes’ of a particular theme are required to infer a personality trait? (i.e., it should account for a stable pattern of behaviour in response to a theme or condition in different situations or contexts); (2) ‘Liking’ is frequently spurious and casual — ‘likes’ do not necessarily reflect thought-out agreement or strong identification with content or another person or group (e.g., ‘liking’ content on a page may not imply it personally applies to the user who likes it); (3) Since the app was allowed to collect only limited information on a user’s ‘friends’, how much of it could be truly relevant and sufficient for inferring the personality traits? On the other hand, for whatever traits that could be deduced, data analyst and whistleblower Christopher Wylie, who brought the affair out to the public, suggested that the project for Trump had picked-up on various sensitivities and weaknesses (‘demons’ in his words). Personalised messages were respectively devised to persuade or lure voters-users likely to favour Trump to vote for him. This is probably not the way users would want sensitive and private information about them to be utilised.

  • Consider users in need for help who follow and ‘like’ content of pages of support groups for bereaved families (e.g., of soldiers killed in service), combatting illnesses, or facing other types of hardship (e.g., economic or social distress): making use of such behaviour for commercial or political gain would be unethical and disrespectful.

Although the app of GSR may have properly received the consent of users to draw information about them from Facebook, it is argued that deception was committed on three counts: (a) The consent was awarded for academic use of data — users were not giving consent to participate in a political or commercial advertising campaign; (b) Data on associated ‘friends’, according to Facebook, has been allowed at the time only for the purpose of learning how to improve users’ experiences on the platform; and (c) GSR was not permitted at any time to sell and transfer such data to third-party partners. We are in the midst of a ‘blame game’ among Facebook, GSR and CA on the transfer of data between the parties and how it has been used in practice (e.g., to what extent the model of Kogan was actually used in the Trump’s campaign). It is a magnificent mess, but this is not the space to delve into its small details. The greater question is what lessons will be learned and what corrections will be made following the revelations.

Mark Zuckerberg, founder and CEO of Facebook, gave testimony at the US Congress in two sessions: a joint session of the Senate Commerce and Judiciary Committees (10 April 2018) and before the House of Representatives Commerce and Energy Committee (11 April 2018). [Zuckerberg declined a call to appear in person before a parliamentary committee of the British House of Commons.] Key issues about the use of personal data on Facebook are reviewed henceforth in light of the opening statements and replies given by Zuckerberg to explain the policy and conduct of the company.

Most pointedly, Facebook is charged that despite receiving reports concerning GSR’s app and CA’s use of data in 2015, it failed to ensure in time that personal data in the hands of CA is deleted from their repositories and that users are warned about the infringement (before the 2016 US elections), and that it took at least two years for the social media company to confront GSR and CA more decisively. Zuckerberg answered in his defence that Cambridge Analytica had told them “they were not using the data and deleted it, we considered it a closed case”; he immediately added: “In retrospect, that was clearly a mistake. We shouldn’t have taken their word for it”. This line of defence is acceptable when coming from an individual person acting privately. But Zuckerberg is not in that position: he is the head of a network of two billion users. Despite his candid admission of a mistake, this conduct is not becoming a company the size and influence of Facebook.

At the start of both hearing sessions Zuckerberg voluntarily and clearly took personal responsibility and apologized for mistakes made by Facebook while committing to take measures (some already done) to avoid such mistakes from being repeated. A very significant realization made by Zuckerberg in the House is him conceding: “We didn’t take a broad view of our responsibility, and that was a big mistake” — it goes right to the heart of the problem in the approach of Facebook to personal data of its users-members. Privacy of personal data may not seem to be worth money to the company (i.e., vis-à-vis revenue coming from business clients or partners) but the whole network business apparatus of the company depends on its user base. Zuckerberg committed that Facebook under his leadership will never give priority to advertisers and developers over the protection of personal information of users. He will surely be followed on these words.

Zuckerberg argued that the advertising model of Facebook is misunderstood: “We do not sell data to advertisers”. According to his explanation, advertisers are asked to describe to Facebook the target groups they want to reach, Facebook traces them and then does the placement of advertising items. It is less clear who composes and designs the advertising items, which also needs to be based on knowledge of the target consumers-users. However, there seems to be even greater ambiguity and confusion in distinguishing between use of personal data in advertising by Facebook itself and access and use of such data by third-party apps hosted on Facebook, as well as distinguishing between types of data about users (e.g., profile, content posted, response to others’ content) that may be used for marketing actions.

Zuckerberg noted that the ideal of Facebook is to offer people around the world free access to the social network, which means it has to feature targeted advertising. He suggested in Senate there will always be a pay-free version of Facebook, yet refrained from saying when if ever there will be a paid advertising-clear version. It remained unclear from his testimony what information is exchanged with advertisers and how. Zuckerberg insisted that users have full control over their own information and how it is being used. He added that Facebook will not pass personal information to advertisers or other business partners, to avoid obvious breach of trust, but it will continue to use such information to the benefit of advertisers because that is how its business model works (NYTimes,com, 10 April 2018). It should be noted that whereas users can choose who is allowed to see information like posts and photos they upload for display, that does not seem to cover other types of information about their activity on the platform (e.g., ‘likes’, ‘shares’, ‘follow’ and ‘friend’ relations) and how it is used behind the scenes.

Many users would probably want to continue to benefit from being exempt of paying a monetary membership fee, but they can still be entitled to have some control over what adverts they value and which they reject. The smart systems used for targeted advertising could be less intelligent than they purport to be. Hence more feedback from users may help to assign them well-selected adverts that are of real interest, relevance and use to them, and thereof increase efficiency for advertisers.

At the same time, while Facebook may not sell information directly, the greater problem appears to be with the information it allows apps of third-party developers to collect about users without their awareness (or rather their attention). In a late wake-up call at the Senate, Zuckerberg said that the company is reviewing app owners who obtain a large amount of user data or use it improperly, and will act against them. Following Zuckerberg’s effort to go into details of the terms of service and to explain how advertising and apps work on Facebook, and especially how they differ, Issie Lapowsky reflects in the ‘Wired’: “As the Cambridge Analytica scandal shows, the public seems never to have realized just how much information they gave up to Facebook”. Zuckerberg emphasised that an app can get access to raw user data from Facebook only by permission, yet this standard, according to Lapowsky, is “potentially revelatory for most Facebook users” (“If Congress Doesn’t Understand Facebook, What Hope Do Its Users Have”, Wired, 10 April 2018).

There can be great importance to how an app asks for permission or consent of users to pull their personal data from Facebook, how clear and explicit it is presented so that users understand what they agree to. The new General Data Protection Regulation (GDPR) of the European Union, coming into effect within a month (May 2018), is specific on this matter: it requires explicit ‘opt-in’ consent for sensitive data and unambiguous consent for other data types. The request must be clear and intelligible, in plain language, separated from other matters, and include a statement of the purpose of data processing attached to consent. It is yet to be seen how well this ideal standard is implemented, and extended beyond the EU. Users are of course advised to read carefully such requests for permission to use their data in whatever platform or app they encounter them before they proceed. However, even if no information is concealed from users, they may not be adequately attentive to comprehend the request correctly. Consumers engaged in shopping often attend to only some prices, remember them inaccurately, and rely on a more general ‘feeling’ about the acceptable price range or its distribution. If applying the data of users for personalised marketing is a form of price expected from them to pay, a company taking this route should approach the data fairly just as with setting monetary prices, regardless of how well its customers are aware of the price.

  • The GDPR specifies personal data related to an individual to be protected if “that can be used to directly or indirectly identify the person”. This leaves room for interpretation of what types of data about a Facebook user are ‘personal’. If data is used and even transferred at an aggregate level of segments there is little risk of identifying individuals, but for personally targeted advertising or marketing one needs data at the individual level.

Zuckerberg agreed that some form of regulation over social media will be “inevitable ” but conditioned that “We need to be careful about the regulation we put in place” (Fortune.com, 11 April 2018). Democrat House Representative Gene Green posed a question about the GDPR which “gives EU citizens the right to opt out of the processing of their personal data for marketing purposes”. When Zuckerberg was asked “Will the same right be available to Facebook users in the United States?”, he replied “Let me follow-up with you on that” (The Guardian, 13 April 2018).

The willingness of Mark Zuckerberg to take responsibility for mistakes and apologise for them is commendable. It is regrettable, nevertheless, that Facebook under his leadership has not acted a few years earlier to correct those mistakes in its approach and conduct. Facebook should be ready to act in time on its responsibility to protect its users from harmful use of data personally related to them. It can be optimistic and trusting yet realistic and vigilant. Facebook will need to care more for the rights and interests of its users as it does for its other stakeholders in order to gain the continued trust of all.

Ron Ventura, Ph.D. (Marketing)

 

 

 

 

 

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

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

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

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

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

Two more issues deserve special attention: 

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

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

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

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

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

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

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

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

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

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

Ron Ventura, Ph.D. (Marketing)

Notes:

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

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

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Not many people would resist a nice meal of a 200g burger sandwich, whole and rich with supplements, ketchup on top, and a side dish of French fries or fried onion flakes. But the venue of dining also counts in shaping the diner’s experience — it is likely for a diner to expect a more tasty and enjoyable burger meal at a full-service grill restaurant compared with a fast food restaurant. A number of factors affect the attraction of a restaurant to diners in addition to food quality, like atmospherics of the venue, service and attitude towards customers. “Moses”, a small-medium chain (8 branches) of grill bar-diners in Israel, has created a brand theme aimed at making patrons-diners feel more welcome and wanted at their restaurants. At the core of the theme are anthropomorphization of Moses as a cat wearing a wide smile and his style of language that is meant to let customers feel more at ease, like they belong in the restaurant as personal guests of Moses.

  • See epilogue with update at the bottom (June 2018)

The language Moses uses to tell patrons-diners about special offers, activities and events is personal, direct and very informal, often a non “going around the bush” kind of talk. It appears on table covers, postcards, signage, its website and other materials. This style also characterises its advertising. It may sound a little blunt sometimes but careful not to be offensive. The approach Moses takes to bring up any matter is intended in a humourous way. It seems that Moses is just trying to be frank, clever yet witty.

There is not much company-official text in English to give as an example since Moses addresses substantially Hebrew-speaking Israelis as in a casual discourse. And indeed Moses’s rhetoric employs expressions in Hebrew that have significance to Israelis but whose semantics may be partially lost in translation to English or other languages. Still, the tone and intention of the rhetorical style of Moses is preserved and can be sensed in the following examples. Moses typically takes a rather plain information or message and twists its presentation by inserting: (a) some doubt or skepticism, (b) adventurism or suspense, (c) irony.

The limited content in English on the Israel-native website of Moses appears (reasonably) to be translated from content originally composed in Hebrew. Consider the following phrases, extracted from the English version of the About page (note: information here is not updated as in Hebrew), to get a feel of how Moses talks to clients. Thus, when telling readers of the chain’s background Moses says:

“Here’s something you’ll find on every website, and here too. Do you really care if Moses Tel Aviv was established on November 2003, and it is part of a group of restaurants…” (Note: the group referred to includes other restaurants of different types of cuisine and brand names; since then Moses expanded as a distinct chain within the group).

Cutting short on the chain’s evolution, Moses comments:

“What’s really important is that they are open now. If you wanted to learn some history you’d probably log into Wikipedia or somewhere like that.”

Some consumers may not like to be sent-off like that to find more information, but another, and the correct way to read this is “Moses doesn’t want to waste your time; just come and eat”. In an age when people are shorter in time and can easily search and find information on the Web, Moses shows as understanding. (Moses also seems to understand the tendency of Israelis to be not very patient.)

In another example, a print ad from a few years ago for a new burger of Moses, Artburger, posed in large-bulk letters (‘loudly’) at the center of the copy: “How Many Times Do I Have to Explain to You That This Is Not a Hamburger?!”  Artburger is made of a mix of lamb, beef and veal meat. Text in small font at the bottom of the ad explained:

“In a competition conducted by TimeOut magazine, which is like what you are holding now but another, readers chose the Artburger of Moses, which is exactly what you will be holding soon, as the best hamburger. So this is the time to admit failure. If after all we had done, we couldn’t make you understand that Artburger isn’t really a hamburger, then we probably deserve this.”  (Translated, RV)

This is a clear attempt by Moses, if a little sarcastic, at differentiating its 250g Artburger with a superior-quality meticulous blend of meat from standard beef hamburger. Importantly, this is not a gimmick of one-off ad but an integral part of the language Moses consistently uses in its communication to consumers, part of his character. (An image of the original ad in Hebrew can be found in the Gallery; also see photos from restaurants in the chain and the Artburger Olympic Contest).

As a final example, Moses made an intriguing invitation or call for customers to participate in a satisfaction survey distributed on postcards at his restaurants. This is how the invitation went:

“Psss… Psss… Act normally. Continue reading as if this is just any other text on a postcard. Don’t let the waiters feel that something suspicious is going on here. Smile like what is written here is something funny. Now, in your most nonchalant way, throw a look at the bottom left corner of the postcard…did you get the (QR) code? It can turn you from regular Moses customers to … “mystery customers”, Hush… Yes, exactly as you’ve heard. Scan the code now and not at home, answer our discreet satisfaction questionnaire, show when finished to the waiter and get a scratching card, and maybe you will win a bonus to spoil yourself. Nice work, Agent. See you on the next mission.” (Translated, RV)

It is an attention-grabbing and engaging way of asking customers to participate in such a survey. In a ‘gamified’ kind of invitation, the task is put into a story of a secret mission — properly applied and difficult to ignore. The invitation has additional important elements like encouragement to reply immediately and a reward, both aimed at increasing the response rate (a link is further provided in addition to the code), yet embedded in a whole story that signals suspense and thrill (and also humour). Then finally comes this footnote:

” (!) This postcard will destroy itself instantly when finished reading if you spill a little ketchup on it, a bit of mayonnaise, wrinkle it into a little ball, and then throw to the garbage can…” — A nice touch of irony in mockery of espionage work…

Moses the cat is a cartoon character — he is known to consumers only by face, with his wide smile, his tongue hanging out as a signal of his mischievous nature, round eyes, red nose, and sharpened ears on top. The icon that identifies Moses visually fits well with his verbal language, and together they help build the brand personality: Moses is sociable, extrovert or approaching to others, light, direct but sometimes more subtle and sophisticated, looking for adventures, and he likes to make jokes but with the sting of irony. Over time some versions of the looks of Moses have appeared (e.g., in different colour, ears pointed to the sides or raised upwards) but they all have the same distinctive elements that are indicative of his character. Other visual elements like the design of the website (e.g., colours and shapes of “windows”) or the menu (recently re-designed in a graphic style similar to infographs) are consistent with the less-orderly conduct of Moses .

  • The face icon of Moses is reminiscent of Felix the Cat, a hero comic and cartoon character from the 1920s-1940s. The personality characteristics (e.g., adventurous, playing tricks on others) also match quite well. The chain has reportedly acquired the creative rights to use the icon-logo of the cat Moses from an American company that owns rights since the 1960s for an original animated figure (1), although the article does not mention the name of the original figure.

However, language can more than tell of the brand personality of Moses; it also speaks of the culture of Moses chain of restaurants as an organisation. When the language used in written and electronic communications is considered together with oral communication, conduct and other actions of the chain’s staff members in the restaurants, they indicate a culture that approaches customers, wants to get close to them and cares for them. Staff members on-site do not really talk as described above but they are courteous and waiters would usually ask diners how they were doing before taking order and return to ask how is the meal after serving. They also tend to fix problems and give away bonuses as compensation to conciliate with customers and keep them happy. Members of the customer club are called Moses Friends; the language used by Moses the cat seems to be directed especially to them and to encourage new ones to join as his friends. Moses Friends regularly get a bonus starter or dessert and accumulate stars for price discount. They also get priority seating.

Yuval Sela, founding partner (with the Yarsin Group) and CEO, defines Moses as “a restaurant that talks to everyone, at noon to business people, in the evening to families, and at night to the young ones after entertainment” (2). In fact, Moses restaurants have turned out most popular among families on weekends. The chain that considers itself a place for “Modern American Kitchen” runs a well-controlled number of restaurants, self-managed without franchising. Sela sees children as the anchors that bring families to their restaurants and therefore most important to satisfy — they give them game and drawing booklets with coloured pencils, and at least one restaurant added in the past year a play room for little children (“Gymboree”). For the young ones who come late at night they offer a night burger meal for a special price treat (42 NIS=€8.75). Beyond that they offer as expected a business lunch deal of a salad, 200g burger, side dish and soft drink/juice at a very fair price (competitive even against McDonald’s meals — 58 NIS to 50 NIS) and other attractions like “international burgers” in culinary styles of different countries. All together, it is evident of a culture of a business that cares for its varied customers.

The language of Moses in the chain’s communications will not appeal to everyone. Some may consider it impolite and intruding (e.g., senior citizens). Others may find this genre of language simply strange to them. It is essential to study and confirm to what segments that kind of language is appealling or at least can feel comfortable with it. Notably, five of the restaurants are located in the Tel-Aviv area in or near business districts that host professionals and managers in banking and finance, Hi-Tech and other business services and socio-economically privileged neighbourhoods. The recently added branch in the vacation resort city of Eilat is rather the exception and probably targets primarily consumers as families.

More frequently, the restaurants are in vicinity to patrons-diners that are likely to appreciate and welcome the spiked humorous and sometimes more sophisticated approach of Moses’s language. It is furthermore likely that consumers from those same circles are those that come outside working hours with friends and family to dine at Moses. It can be hoped that diners who come along with “devotees”, even if they do not truly welcome that style of language, will at least find it amusing.

Epilogue (June 2018):  In early 2017 Moses restaurant chain was acquired by BBB Group which already owned at that time two hamburger restaurant chains. Following this acquisition, BBB Group operates three chains with different positions of quality and value proposition: Burgerim — basic, fast-food; BBB (Burgus Burger Bar) — medium, good value; and Moses as its premium brand. However, within a year BBB dropped or abolished much of the symbols and elements of the brand personality of Moses, including the culture and language attached to it. Five of its current 11 branches are already operated by franchisers. The previous founding owners lamented that differentiation of the brand has eroded and revenues did not justify keeping up the chain. Yet the personality and culture of Moses did make the restaurant chain stand out from its competitors, including BBB itself. Moses is not the same as before; even its menu and how burger sandwiches are served have changed. The BBB Group has not made so far an attempt to revitalise the brand theme of Moses or replace it with something new and different. Without it, the task could become more difficult to maintain differentiation of Moses from other chains at least similar in position of quality and value, and it is losing its brand distinction and uniqueness.

Ron Ventura, Ph.D. (Marketing)

Notes:

(1) “How Did We Turn Into an Overeat People: 20 Hamburgers a Day and a Line to Restaurant at 3AM”, TheMarker Online (Hebrew), 23 Sept. 2010 http://www.themarker.com/misc/1.581423

(2) Ibid. 1 (Citation translated from Hebrew, RV)

 

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