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Category: neuromarketing

  • Difference between neuroscience and neuromarketing

    Difference between neuroscience and neuromarketing

    The importance of practice (with context) for the understanding of theoretical results

    Even for people who already work in the field, the differences between the scope, scope and meaning of neuroscience and neuromarketing are not always very clear.

    I would like to comment on a presentation made at the last neuromarketing congress, held in March 2017 in London and organized by NMSBA – Neuromarketing Science and Business Association.

    Although the specific contributions of each area (‘neuroscience’ and ‘neuromarketing’) can be complementary, it is essential that the limitations to their respective applications are previously known and considered as resources to support business decision-making.

    Without intending to deepen a technical or theoretical discussion, I allow myself to exemplify the difference, in a very practical way, with a real case that demonstrates how different the two areas are.

    Real case

    The case was about a German tea maker who wanted to change and also rejuvenate its already very traditional packaging, since it is a company with more than 80 years of experience in the market.

    Two new packaging proposals were initially developed by a specialized design agency and previously approved by the tea maker’s own marketing team.

    In order to support the choice of the most suitable packaging and minimize possible risks, the board would like this decision, due to its importance, to be based also on the most modern techniques available on the market.

    Therefore, a company specialized in neuroscience was hired, with access to the most appropriate equipment and resources for this evaluation, including comparing the results with the actual packaging itself.

    The manufacturer’s expectation was that, with neuroscience, it would be possible to choose the most appropriate packaging alternative and capable of adding different attributes of the new positioning sought, supported by what was most scientifically pertinent.

    Among the different attributes sought in the packaging were the rejuvenation of the brand, modernity, innovation, but without giving up the other associations already existing and incorporated into the product and the brand over time by consumers.

    The results

    The different packages were evaluated and compared explicitly and implicitly, including the use of magnetic resonance imaging (fMRI), with the results being quite clear that one of the new options has a greater emphasis, coinciding with the choice of the marketing team itself.

    This situation, consequently, generated considerable confidence as to the most appropriate choice to be made, as the results also point scientifically and technically to the same solution.

    It is important to keep in mind that, often in ‘conventional’ techniques, such as in qualitative and quantitative research, situations where the results are somewhat conflicting are not uncommon, demanding a more subjective interpretation, which adds uncertainty to borrowers decision-making and the research agency.

    In this case, decision made, new packaging approved, investments made, products displayed on supermarket shelves and a great expectation for results.

    The surprise

    To general surprise and perplexity, what was observed were unexpected and unexplained declines in sales, something to be repeated month after month, even after all the investment made and the initial certainty regarding the choice made.

    Even more desperation from managers, not sure what to do now, but in any case aware of the need to better understand what would have caused the failure in sales.

    Thus, it was decided to hire a new company, in this case an agency specialized in neuromarketing, initially to review the entire packaging evaluation process already carried out.

    The new evaluation

    There being no doubts about the process, an assessment of the context and the process of acquiring the tea was then put into practice, with the observation of how the product purchases normally occur in supermarkets, one of the most relevant distribution channels.

    The filming and recording of a woman, young – less than 35 years old, full-time worker, mother of 2 young children, shopping in a supermarket with her young children, was particularly decisive in understanding the problem.

    The image of children irritated by the unattractive situation, the consumer with very little time to choose the products, without the ‘desired’ or ‘idealized’ reflection in front of the gondolas for a rational choice of products were very familiar elements to most who helped understand the reason for low sales.

    It was clear that the consumer’s decision regarding the choice of brands for the different products on the shopping list was almost always taken in a matter of milliseconds, apparently bearing in mind the objective of accomplishing this task in the shortest possible time.

    Familiarity

    One of the crucial aspects observed in the purchasing process was the importance of the consumer’s ‘familiarity’ with the product, more specifically in this case when analyzing its packaging.

    It was observed that this ‘familiarity’ was due to the recognition of the manufacturer’s brand, its typical colors, the logo, that is, the visual aspect of the packaging itself, which is already well known by consumers.

    It turns out that the new packaging of the product had almost no trace of familiarity with the old packaging, either in terms of colors or its graphic elements, in spite of the favorable results obtained with neuroscience.

    In other words, despite all the positive aspects of the new packaging verified with the tests carried out, there was no longer an association of the product already known by its consumers to the new packaging now presented on the shelves.

    Most consumers left the supermarkets with the impression that the product was not available on the shelves, without bothering to carry out a more detailed search, perhaps due to the lack of time, the pressure of the children, the rush to complete the activity, etc.

    Consequently, by not finding what they ‘were looking for’, consumers ended up choosing a ‘similar’ product, from another competitor, also positioned on the shelves, like all other players in the category.

    The solution

    With the identification of the problem at the point of sale, the manufacturer reevaluated the existing packaging options and opted for one that, although it did not deserve the best evaluations in neuroscience tests, still maintained greater traits that enabled the consumer to associate with the previous mark.

    That done, tea sales returned to expected levels and recovered the share that had been lost to the competition.

    The message that remains, in no way constitutes a condemnation of neuroscience or its techniques, but about the need to also consider neuromarketing and the resulting implications.

    The complementarity that conventional techniques of market research and opinion, such as ‘ethnography’, ‘in-depth interviews’ or even ‘product clinics’ should not be overlooked and still play an important role in these analyzes.

    More information:          Kochstrasse – Agentur fuer Marken

    NMSBA – Neuromarketing Science & Business Association

    World Forum – Londres – março 2017

  • Like & Dislike in Advertising

    Like & Dislike in Advertising

    Likability, Advertising and Neuromarketing

    It has always seemed like a considerable exaggeration to expect advertising campaigns to make people fall in love with brands, products or services.

    Even with admired, inspiring companies like Apple, Coca-Cola, Google or Microsoft, or products like Nespresso or the iPhone, talking about consumers’ “love” for a brand or product may be a stretch.

    In my view, getting an advertisement to make someone simply “like” a brand, product or service is already a considerable challenge — even more so for categories like toilet paper, toothpaste, banks, insurance or cell phone plans.

    That’s why the “like and dislike” evaluation — likability — is a more realistic, plausible and logical way to think about how advertising wins over its target audience.

    Different studies address this in the advertising market, including some from the ARF (Advertising Research Foundation), which highlight the predictive potential of likability, while others are less conclusive, or even skeptical.

    How It’s Traditionally Measured

    Conventional research measures “like and dislike” mainly through two classic questions: “Did you like the ad you watched?” and “Would you like to watch it again?”

    It’s worth noting that, whether the approach is qualitative or quantitative, both of these likability findings rely on people’s stated, rationalized responses.

    Far from claiming that results from this format are invalid, the point worth discussing is how accurate or adequate this kind of evaluation really is for assessing an ad.

    One risk of this “traditional” criterion is that respondents’ answers can be skewed by social desirability bias — the tendency to give a “politically correct” answer. The format also doesn’t allow for a more refined metric, since it tends to polarize between two extremes (“like” and “dislike”), making it harder to pinpoint the adjustments needed or draw finer comparisons with competitors.

    What Neuromarketing Adds

    When we look at the alternatives for measuring that same “like and dislike” using neuromarketing tools, the options multiply considerably.

    It’s worth highlighting, first, the wide range of measurement techniques available — techniques fully capable of meeting these expectations, generally with stronger results.

    These range from facial expression analysis to skin conductance (galvanic skin response), pupil dilation, and EEG (electroencephalography), among others.

    Each technique delivers more precise results and, above all, is far more sensitive to participants’ reactions, with scales and measurement frequencies that allow for a more accurate read on impact.

    Unlike conventional research, the data collection pattern in these techniques allows advertising to be evaluated second by second, making it easier to pinpoint exactly where intervention or correction is needed.

    In addition, pairing the analysis with eye tracking reveals the extent to which every element of the commercial was — or wasn’t — actually perceived by participants. This is a valuable finding, since it shows which elements are driving likability and which still need more emphasis, whether in the message, the brand itself, or the context.

    Why These Results Are More Reliable

    The main strength here is the high reliability of the results, simply because they’re entirely spontaneous biometric measurements — not filtered through interpretation or rationalization.

    The numerical format of these results is another key advantage: it’s accessible and understandable to everyone, regardless of technical background.

    Unlike conventional research — where a “likability” diagnosis might be read as a straight “approval” or “death sentence” — neuromarketing makes it possible to improve and refine a solution instead.

    A New Way of Working Together

    Once the initial hesitation around this newer approach fades, and the usual distrust between the agency (creative side) and the research firm (analysis side) is overcome, a new kind of working relationship becomes possible.

    That partnership — using these research techniques far more intensively, not just on the finished campaign but from its inception — allows each step to be tested from day one.

    It’s worth being clear: this kind of collaboration between the advertising agency and the research firm would never mean interfering with the creative process itself. Research specialists simply don’t have that expertise — but working closely together is very likely to result in more effective campaigns.

    —

    *Reference: Faris Yakob, “Being Well Liked” [confirm full title, publisher/year, and link to the original source if available].*

  • Brand loyalty and neuromarketing

    Brand loyalty and neuromarketing

    Brand Loyalty and Neuromarketing

    The meaning and scope of “loyalty” have undergone considerable change, much like most of the ideas and assumptions we grew used to before the digital age.

    Several voices even argue for abandoning the pursuit of brand “loyalty” altogether, for reasons ranging from heavy investments that never delivered the expected return, to loyalty programs that simply failed to drive sales.

    From Repeat Purchases to Experience

    Until recently, “loyalty” was understood — and largely limited to — repeat purchases: as constant and frequent as possible, and that was the whole story.

    The idea centered almost entirely on the transactional: loyalty programs where every ninth purchase earned a free tenth item, or simple discount coupons. In principle, both sides — brands and consumers — walked away satisfied, ready to start a new cycle on the same basis, in the same format, repeating with little real differentiation.

    But the concept of “loyalty” in the digital age has taken on very different connotations from those it had when the brand-consumer relationship was fundamentally built on physical presence — and that shift now demands a different response from brands.

    There are growing signs that consumers are no longer fully satisfied with the old model’s solutions, and that they expect something more than a purely transactional relationship. Increasingly, consumers link “loyalty” to brands that deliver a remarkable experience — consistently, over time, and above all, one that adds real value to the relationship.

    So how do you “deliver” a better experience to the consumer? What should brands pay attention to so that this delivery meets these new expectations and translates into the loyalty they’re after?

    From Consumers to Brand Advocates

    The idea is to move beyond transactions and cultivate active attitudes and behaviors among consumers — turning them into brand “advocates,” “enthusiasts” and “promoters.”

    These are consumers who defend, publicize and recommend the brand to acquaintances, coworkers, family — and, above all, on social media. Consumers who, in return for the experience they received and in appreciation for the product or service, spontaneously start praising, sharing and commenting positively about the brand.

    In other words, this still-emerging kind of “loyalty” happens when consumers go beyond the simple purchase and naturally take on an active role, with concrete, spontaneous actions directed at the brand.

    Unlike the conventional “one-to-one” effect, what emerges here is “one-to-hundreds,” “-thousands,” perhaps even “-millions,” given the exponential reach of social media.

    Three Pillars: Relevance, Utility and Purpose

    Brands essentially need to work on three fronts to give consumers a better, more memorable experience: **relevance**, **utility** and **purpose**.

    **Relevance** comes from a brand’s understanding of the customer journey — making decisions easier for consumers and offering them what’s already known to interest them, using big data as the underlying platform. Think of Amazon or Netflix suggesting new products based on past preferences, or on what large numbers of other people are choosing right now. The examples don’t stop there — they extend to Booking.com, Airbnb, iFood, Uber, international publications, and countless other active brands already operating under this model.

    Delivering simple experiences that align with each consumer’s own history — making the choice easier for someone “lost” among countless options — is a powerful driver of sales growth and a key part of consolidating loyalty.

    **Utility** means using the resources the digital medium offers so the consumer experience isn’t just interesting, but also easier, more pleasant, and genuinely solves problems or removes friction. Experiences that achieve this add value, retain customers, and can even be fun — like the ASOS app, which identifies similar clothing items from photos, or lets customers try on clothes at home for free. Or like certain hotels, where guests can review their bill online from their room, authorize the charge, and skip the checkout line entirely — combining simplicity with convenience. The examples keep multiplying: mobile boarding passes, hotel rooms that need no physical key or check-in, one-tap buttons that reorder your last pizza — all speeding up the process.

    **Purpose** is about how brands reveal what they are, what they think, and what they value. While many of these initiatives predate the digital age, today’s tools have given them far greater visibility and reach. The goal is to strengthen the relationship, reinforce values, and build consumer identification with those ideals — enough to justify a purchase because it makes people feel like better versions of themselves, contributing to causes worth supporting.

    A few examples: Patagonia and responsible consumption, or recycling used gear; Airbnb’s special program supporting victims of natural disasters, like the Florida hurricane; Adidas’ “Team Messi” campaign (across Twitter, Facebook and Instagram), where 94% of participants were new to the brand and now spend an average of €10 in e-commerce.

    But like almost everything, it’s a double-edged sword. Success in this strategy can take a brand to new heights, with far deeper loyalty — but a misstep can mean losing consumers, eroding the brand, and sliding right back into purely transactional territory.

    The Research Challenge

    That leaves research with a real challenge: how do you measure the type, quality and intensity of the experience delivered to the consumer? How do you assess whether that experience actually had an impact — and whether it translates into future purchases?

    Some answers can come from conventional market research techniques, but it’s clear there are limitations, and a need for deeper answers. Simple scales like “yes/no” or “good/average/very poor” aren’t the most adequate metrics — they don’t allow for much progress in evaluating experience, even if they’re a relevant starting point.

    Neuromarketing, paired with conventional research, already offers techniques and tools to dig deeper into most of these questions. In the end, the answers being sought come down to evaluating the reactions these experiences trigger: at what point they were impactful, how they stood apart from the competition, and to what extent they produced lasting effects.

    Neuromarketing-based responses tend to be more accurate precisely because they’re not based on rational or self-reported answers, but on spontaneous, instinctive emotional reactions to these stimuli and experiences.

    That’s why these metrics are far more sensitive and credible — both because of the precision of the technical tools involved, and because of most people’s well-documented difficulty in accurately describing their own feelings or emotions.

    The truth is, many of us don’t even know how to properly interpret our own emotions — let alone describe them or put a number on them. That’s exactly why neuromarketing can, and should, be used more and more often.

    —

    *Reference: Amy Brown, “Rethinking ‘Loyalty’ in the Age of Digital,” Admap, November 2017.*

  • Perspectives for the use of facial expressions

    Perspectives for the use of facial expressions

    Facial Expressions

    The human face (facial expressions) consists of a vast panorama in constant movement of what is happening in our most intimate state of mind, with a considerable diversity of nuances and great complexity.

    Humanity has always been developing, in a natural way, the ability to understand the facial expressions of others, initially as a survival strategy (friend / enemy), and currently aiming at relationships of all kinds.

    Based only on sensitivity and intuition, we all spend a considerable amount of time interpreting, analyzing and reacting to the perceptible signs of facial expressions of bosses, spouses, teachers, partners, co-workers, strangers, relatives. , etc.

    With the technology and the capacity of data processing increasing, the face of each one of us and the information that is transmitted spontaneously for some time has ceased to be just the way we present, relate or behave in public.

    Far from merely signaling our momentary state of mind or our reaction to situations, people or facts, this whole set of data has been increasingly treated as something strategic and object of intense studies.

    The use of facial expression analysis continues to grow, whether with Apple using it to unlock the i-phone, in churches in the United States trying to attract believers, in England identifying those responsible for shoplifting, with the police in Wales arresting suspects at football games in China identifying undisciplined drivers, allowing tourists access to certain attractions, among others.

    In the medical field, some applications are very promising, such as the early diagnosis of genetic diseases such as Hajdu-Cheney syndrome, in hopeful attempts to treat autism, in determining whether a person is depressed or whether the pain is real or psychological.

    All these new features have sparked heated discussions regarding the invasion (or not) of privacy, since, for example, the identification of sexual preferences reached 81% of correctness by the algorithm, while people (without the resource) 61% of the time they made that identification correct.

    There would therefore be a potential risk of discrimination on the part of companies, for example, in the recruitment of employees, so much so that legislators in some countries in Europe are already moving towards considering biometric data as information belonging to the people themselves and not something. in the public domain.

    But, going back to the types of applications that would interest us, the fact is that facial expressions, most of the time, communicate more and better than words, either because they are spontaneous, sincere, natural, because they reflect the real feeling or emotion , and above all because they are not rational.

    It is thus an important resource to be used in a complementary way to the other existing techniques in neuroscience and market research, in order to understand what people do not know, cannot or may not want to verbalize.

    Paul Ekman was the pioneer in the analysis of facial expressions with his research even in the 60s. Among his greatest contributions, there is evidence of the existence of at least 6 human emotions, which can be identified regardless of gender, age or even of culture.

    This study resulted in the decoding of these emotions in different combinations of 46 types of facial movements that allowed different applications from animations to lie detector.

    With the advancement of technology and the greater capacity for processing information, the uses of this knowledge have expanded considerably. Basically the algorithm consists of measuring the movements of a series of points virtually created on the participant’s face in relation to other fixed points.

    Thus, the position of the mouth, lips, cheeks, eyebrows, eyelids, wrinkles etc. they are constantly compared with other points (like the tip of the nose, the chin), with the pattern of the facial expression of each one and also with a reference table, allowing the identification of emotions such as joy, confusion, frustration, surprise, fear, anger, disgust, etc.

    In studies that Checon has already carried out, it is possible to assess how much a particular commercial is pleasing (or not), to what extent this involvement is positive (or not), in which excerpts from the commercial are necessary adjustments or reinforcements, all without even asking the participants , always in a clear, objective way, which can be understood even by those who are not even in the area of ​​neuro or research.

    The same types of conclusions are possible in the evaluation of people’s reactions to a political discourse, in order to understand if there is understanding or engagement, which are the passages that need more clarity, if there is approval, acceptance, always in a non-invasive way, without even not even interact directly with the participants.

    In works on website usability, the difficulties in performing certain tasks are evident with negative facial expressions, or with expressions of anger, doubt, dissatisfaction or frustration, even if not admitted in the participants’ ‘rational’ testimony.

    Another very interesting use of facial expressions is the analysis of consumers’ reactions to store windows, making it possible to identify the impact caused, the strengths and weaknesses of each option, even the attractiveness as an ‘invitation’ to people for the inside the establishment.

    Not to mention the food industry analyzing facial expressions in tasting tests or preferably between products in blind tests, or in banks evaluating reactions to ATMs, or automakers evaluating the behavior of drivers driving or identifying signs of drowsiness behind the wheel.

    Micro expressions offer a valuable contribution in the evaluation of decision making, being able to predict whether a certain purchase will be made (something that a flash of disgust can deny), or if a certain price is appropriate (something that an expression of joy can confirm and one of anger may disprove).

    Since, in most cases, these micro expressions are not even perceived by the participants themselves, because they are spontaneous reactions, they are more reliable predictors than the (often) politically correct answers (not infrequently) that compromise many of the predictions of sales.

    The choice of a candidate and the intention to vote also fit perfectly into this assessment of decision-making in a seemingly more reliable way than the mere rational statement by voters.

    There is impressive data as to the correctness of the voting intentions of American voters in the 2010 presidential election, based only on the facial expressions collected in the Obama & Romney debate that reached 73% confirmation, without asking any questions.

    More information:       The Economist – What machines can tell from your face

    The New Yorker – We know how you feel

    Paul Eckman – Facial Action Coding System