Chapter 18
Picking the Right Approach for Your Research Needs
In This Chapter
Summarizing the range of consumer brain responses measured by neuromarketing
Classifying which technologies are best for measuring responses in key marketing areas
Seeing how some companies are combining neuromarketing and other research approaches
In Part II, we fill you in on the new view of the consumer emerging from brain science. In Part III, we look into how nonconscious processes play a role in six marketing areas. And in Part IV, we review a wide variety of neuromarketing methods and technologies that can be used to measure consumer responses and behavior. In this chapter, we pull these threads together into a unified viewpoint of what goes with what. Our goal is to give you a quick-reference guide for pinpointing where neuromarketing can help you address your research needs.
We begin with a fresh classification of the kinds of brain processes and outcomes neuromarketing can measure. Then we look at the intersection of each technology area and each marketing area. For each intersection, we provide a list of those processes and outcomes we believe are best suited for measurement by that technology in that marketing area.
It’s a high-level matchup, a snapshot at a moment in time for a field that is rapidly evolving, but it’s a good starting point for navigating through the neuromarketing field and deciding where and how neuromarketing can be a useful market-research approach for you.
We conclude with a short section on integrating neuromarketing into larger research programs. We describe how some leading-edge companies are building next-generation research organizations that combine neuromarketing with other research approaches — some traditional and some as new as neuromarketing — for a more comprehensive picture of their consumers, products, and brands.
Summarizing What You Can Measure with Neuromarketing
To create a high-level overview of what goes with what, we first need to do a little classifying of the many brain processes we discuss in this book. Here are a dozen consumer responses that can be measured by neuromarketing techniques and technologies:
Implicit associations (introduced in Chapter 5) are connections in long-term memory. They’re key to understanding impressions of novelty, familiarity, and processing fluency.
Priming (introduced in Chapter 5) is the basic mechanism by which objects and situations in our environment nonconsciously influence our attitudes, goals, and behaviors.
Attention (introduced in Chapter 6) is the brain mechanism by which nonconscious inputs get elevated to conscious awareness. Levels of attention influence emotions, memory, and expectations.
Discrete emotions (introduced in Chapter 6), such as happiness, sadness, surprise, disgust, fear, anger, and contempt, are our universal emotional reactions to the world around us.
Emotional arousal and valence (introduced in Chapter 6) are dimensions (as opposed to discrete types) of emotion. Arousal refers to level of stimulation, intensity, and agitation. Valence refers to direction of liking or disliking, positive or negative reaction.
Approach and avoidance (introduced in Chapter 6) are the two nonconscious dimensions of motivation that drive action. They’re motivational sources of attraction and aversion, and they’re heavily influenced by nonconscious, emotional conditioning (somatic markers).
Memory activation (introduced in Chapter 5) is the extent to which memory encoding or retrieval is triggered by an experience.
Value (introduced in Chapter 8) is the mental calculation of expected value, experienced value, and remembered value. It’s derived from balancing loss aversion (cost, pain, inconvenience) with reward seeking (pleasure, benefit, payoff).
Usability (introduced in Chapter 13) is the degree to which an online task is experienced as easy to do, efficient, and enjoyable. It’s an attribute of web pages and websites.
Preference (introduced in Chapter 8) is the judgment of value among alternative choice options.
Choice (introduced in Chapter 8) is a key marketing outcome variable. It can be a result of implicit or explicit decision making and is measured directly by choice experiments.
Behavior and performance (introduced in Chapter 2) are additional important marketing outcome variables. A behavior is an observable action. Behaviors are outcomes of conscious and nonconscious mental processes, encompassing what people say and do. Performance is determined by measuring behavior against a goal or expectation, resulting in a judgment of relative success or failure.
Matching Neuromarketing Approaches to Research Questions
The consumer responses we list in the preceding section can be matched up to the neuromarketing methods and technologies we cover in Chapters 16 and 17, as well as to the marketing application areas we cover in Part III. We provide our estimates as to what goes with what in Table 18-1. As you can see by glancing at the table, some cells are blank; that’s because some methods and technologies can’t be used, or aren’t optimal, for measuring consumer responses in some application areas. Other cells contain the consumer responses that can best be measured using a particular method or technology in each application area.
To make this task of matching consumer response measures to methods and technologies more manageable, we group the technologies covered in Chapters 16 and 17 into six broad categories: behavioral response-time studies, eye-tracking, behavioral experiments, biometrics, electroencephalography (EEG), and functional magnetic resonance imaging (fMRI).
Behavioral response-time studies
Behavioral response-time studies (discussed in Chapter 17) are simple, scalable, inexpensive, and easy-to-interpret tools for measuring implicit associations, semantic and affective priming, preferences, and choices. Because they depend on rapid responses to discrete choice or classification tasks, they work best with words and static images as stimuli. They’re a good choice for studying brands and products, but they’re less appropriate for studying advertising (except for print or other static ads), shopping, online tasks, or entertainment.
Behavioral response-time studies can be quickly set up using online services that take care of all the underlying coding required to ensure accurate timing of the selection tasks. Experimental templates are also available that are easy to customize to work with your own stimuli. Experiments can be run using existing online panels of consumers, allowing you to get hundreds of completed trials from qualified participants in very short time frames.
Eye tracking
Eye tracking (discussed in Chapters 16 and 17) includes measuring eye movements and fixations, eye blinks and the startle reflex, and pupil dilation. It’s a very popular stand-alone technique in neuromarketing studies. It’s also regularly combined with other approaches when the stimuli being studied are visual. It’s less useful for branding and new product concept studies because these studies often don’t involve visual stimuli. The availability of well-established metrics, which are often built into the eye-tracking software, makes eye tracking an excellent solution for measuring attention, cognitive processes underlying choice (used in combination with forced-choice testing), implicit preferences, and online usability. Eye tracking leaves some questions unanswered — such as whether a fixation is a function of interest or confusion — but eye-tracking metrics are intuitive and direct measures of behavior that most people find easy to understand and interpret.
Eye tracking comes in two flavors: online eye tracking through the webcam and lab-based eye tracking using specialized equipment. A neuromarketing vendor should be able to help you decide which approach is the best balance of precision and scalability for your needs.
Behavioral experiments
Behavioral experiments (discussed in Chapter 17) are the primary technique for testing principles and insights from behavioral economics and social psychology. The experimental approach (see Chapter 19 for a review of the basics) is flexible, relatively inexpensive, easy to set up, and easy to understand and interpret the results. With heuristics (judgment and decision-making shortcuts) as a guide, behavioral experiments can be an excellent technique for testing hypotheses about priming, choice, and behavior in different consumer scenarios.
Behavioral experiments are especially useful for studying the effects of priming on choice and behavior in shopping situations, in both physical and online stores. They’re also beginning to be used more for testing the impacts of brands, products, packages, and advertising as primes of choice and behavior. Behavioral experiments can also be used to test choices and behaviors triggered by entertainment experiences, such as responses to new movie trailers.
The chief advantage of behavioral experiments is that they measure behavior directly, so there is no intermediate step of translating raw signal measures into interpretable metrics.
Biometrics
Biometrics (discussed in Chapter 16) measure a wide range of physiological (body) responses — facial expressions, facial muscle movement (facial electromyography [EMG]), skin conductance due to perspiration (electrodermal activity [EDA]), heart rate, blood pressure, respiration — that can be used across most marketing areas. The only area where biometric measures are not extensively used is in shopping and in-store studies, because physical movement in shopping environments often creates interference with body signals.
Biometrics are best suited for measuring nonconscious and conscious emotional responses to stimuli. Autonomic nervous system measures like EDA and heart rate are most useful for measuring emotional arousal, facial EMG is a reliable measure of emotional valence, and facial expression analysis (both automated and expert-based) is primarily used to measure discrete emotions (joy, surprise, and so on). Facial expression, facial EMG, and arousal measures are also useful for testing online usability, because these measures are good for gauging longer-term emotional responses to online tasks, such as confusion, frustration, or boredom.
One neuromarketing vendor (Innerscope, Inc.) has reported using biometric measures successfully to predict marketplace behavior for new product designs, so we include behavior as a response that can be measured by biometrics for that application area.
Biometric methods are less complex than EEG and fMRI methods, but they still represent a significant step up in complexity compared to behavioral response-time studies, eye tracking, and behavioral experiments. Unlike those approaches, biometric studies require expert knowledge and experience to correctly apply sensors, control data collection conditions, and convert raw signal results into interpretable metrics.
Electroencephalography
As discussed in Chapter 16, EEG measures electrical brain waves. EEG studies represent another step up in complexity compared to biometric studies. They require PhD-level training in neuroscience to oversee the study from start to finish — from experimental design to study preparation to data collection to data analysis. For this reason, EEG studies are almost always conducted in partnership with an EEG technology specialist.
EEG has been used with good results in branding, product innovation, product and packaging design, and advertising studies. It has been less commonly used in shopping studies, although one neuromarketing firm (Sands Research, Inc.) has reported interesting results using mobile EEG equipment and eye-tracking glasses to study choice and behavior in real-store shopping scenarios (see Chapter 7).
Fewer EEG studies have been reported in online experience testing. This may be because the free-ranging nature of goal pursuit in online tasks is hard to reconcile with the high degree of experimental control required for reliable measurement of EEG signals, which need to be averaged over multiple individuals. When engaged in online tasks, people will pursue their goals in different ways, producing different sequences of mental states and emotional reactions, which are hard to integrate and interpret with EEG.
EEG has been most effective for measuring nonconscious approach-avoidance motivational reactions to stimuli, using the hemispheric asymmetry approach described in Chapter 16. EEG is also well established as a method for measuring moment-to-moment changes in attention using frequency band fluctuations, and it’s the only measurement technology able to identify memory activation in real time. Finally, event-related potentials (ERPs) have been used extensively to explore many aspects of implicit associations, including emotional valence, personal relevance, and expectancy violation.
Functional magnetic resonance imaging
fMRI (discussed in Chapter 16) measures blood flow to different regions of the brain associated with mental tasks and states. fMRI is the most complex technology used in neuromarketing. It’s considered the gold standard for brain imaging by academic neuroscientists, but the same features that make it the most precise imaging technology also make it the least practical. fMRI machinery is huge and expensive, and it’s found only in hospitals and the best-funded neuroscience research facilities. But it’s also the only technology that can pinpoint activity at any location within the brain, as long as that activity can be sustained for the three to five seconds it takes to produce a full brain scan.
In consumer neuroscience (the academic sister discipline to neuromarketing), fMRI has been used to study branding, advertising, shopping, and entertainment. Major studies in branding have identified implicit associations and reactions to brands that impact the process of assigning value to a product or outcome. Studies have found that powerful brand associations have the capacity to influence basic sensory experiences like taste and smell, as well as product choices.
fMRI is the only technology able to reveal the dynamics of value creation in the human brain, allowing neuroscientists to identify how reward expectations and loss aversion (resistance to spending) are activated in different parts of the brain and reconciled in the process of product or brand choice and purchase. fMRI has been used to predict both individual and marketplace behavioral outcomes following exposure to TV advertising. (These studies by Falk, Lieberman, and colleagues are discussed in Chapter 22.)
Integrating Neuromarketing and Traditional Research Approaches
In this book, our focus is on neuromarketing, but for businesses that regularly use market-research services, a broader perspective is required. For both large and small consumers of research, neuromarketing is only one tool in a larger toolkit of approaches and methodologies. To integrate effectively into broader research programs, neuromarketing needs to fit in as well as stand out.
Taking a big-picture view of market-research requirements
Figure 18-1 depicts three fundamental ways consumers interact with a brand or product: being exposed to its marketing messages, shopping and buying a brand or product, and consuming or using a product.
Illustration by Wiley, Composition Services Graphics
Figure 18-1: The consumer cycle: marketing, shopping, consuming.
These three modes of interaction make up three stages in a cyclical relationship between the consumer and the product or brand. Each stage produces outputs — expectations, associations, or choices — that then become inputs into the next stage:
Marketing: Consumers’ responses to marketing begin with expectations based on prior product experiences. The purpose of marketing is to change or reinforce those expectations by strengthening mental associations with the brand or product. Updated associations are the output of successful marketing messages.
Shopping: When consumers enter a shopping environment (in-store or online) they bring their mental associations with them. Through the process of shopping (searching, choosing, and paying), some associations are activated and others are not, and the outcome is a choice, which results in a purchase.
Consuming: The output from shopping is the input for consuming. Purchased products are consumed in product experiences, which further update associations and expectations. These expectations then become inputs into consumers’ responses to later marketing messages.
A perfect market-research program would be one that covers this complete consumer cycle and generates key performance indicators for each stage of the cycle and each transition point. In other words, it would connect marketing to shopping, shopping to consuming, and consuming to marketing, all with a unified set of metrics and measures.
Some leading companies are beginning to think about market-research programs in this comprehensive way. They’re frustrated with discrete research approaches that don’t add up (neuromarketing included). They want integration and synthesis across their research data, with results combined into a holistic framework that provides a comprehensive view of their consumers at every point in the consumer cycle.
Thinking about capacity and capabilities for integrated studies
The first step in building a comprehensive market-research program is determining what methodologies and technologies need to be included. In large marketing-focused companies today, four major research streams are likely to be active in one part of the marketing organization or another:
Observational research: These studies use anthropological or ethnographic approaches, or traditional interviews and focus groups, to observe consumers with minimal intervention. They’re qualitative rather than quantitative, and they’re aimed at discovering new facts and insights about consumers.
Online and mobile research: Today, online and mobile research is mostly devoted to online panel studies of various kinds and social media (or “buzz”) content analysis. With neuromarketing, online and mobile can expand to include behavioral response-time studies, rapid forced-choice studies, and webcam-based implicit response studies.
In-store, point-of-sale (POS) research: These studies are conducted in real or mock stores to examine shopping and buying behavior. Main subjects of research are signage and display testing, shelf-display studies, and traffic-pattern studies. Neuromarketing adds in-store behavioral experiments and nonconscious priming studies to the mix.
Performance and return-on-investment (ROI) research: These studies use consumer panels, media exposure data, and POS purchasing data to assess the performance and ROI of marketing expenditures. For the most part, these studies require massive amounts of data that can only be provided by the largest research companies. Performance and ROI data are critical to developing normative databases, a topic discussed in more detail in Chapter 19.
To this list, neuromarketing adds a fifth research stream:
Lab-based studies: These are experimental studies that are conducted in controlled laboratory conditions, using biometrics, EEG, or fMRI technologies. Lab studies also include simulations and virtual-reality experiments.
The second step in integrating all these data streams is to develop and deploy a comprehensive knowledge repository of findings and lessons learned from all five research streams, organized around a holistic framework like the consumer cycle model (see Figure 18-1). This knowledge repository can then be used to bring together findings, identify new insights, and most important, provide a performance-based foundation for calculating the ongoing ROI of a company’s full investment in marketing and market research.
Building an organizational structure for integrated studies
Leading companies are just beginning to think about their research efforts in this holistic way. Some are asking large market-research firms to outsource the functionality and management of such an organization; others are building the capability in-house using internal resources and outside consulting help.
The ultimate vision is a kind of “mission control” for research — bringing together the latest technologies from neuromarketing, other new research methodologies, and traditional techniques — within a single organization devoted to planning and oversight of a company’s complete research program.