Innerscope Research, LLC © 2009 1 WHITE PAPER A REVIEW OF STUDIES USING BIOMETRIC MEASURES OF EMOTION TO PREDICT BEHAVIORS By
Dr. Carl Marci Dr. Caleb Siefert Dr. Ravi Kothuri General Inquiries: 617‐904‐0555 www.innerscope.com Confidential: Not to be Distributed Without Permission from Innerscope Research Version Date 08.17.09 Innerscope Research, LLC © 2009 2 About the Authors: Dr. Carl Marci is Director of Social Neuroscience for the Psychotherapy Research Program at the Massachusetts General Hospital and a Staff Psychiatrist at MGH. He is also the CEO of Innerscope Research, LLC. Dr. Marci received his B.A. with honors from Columbia University and his M.A. in psychology and philosophy from Oxford University as a Rhodes Scholar. Dr. Marci completed his M.D. with honors at Harvard Medical School. Dr. Marci has extensive training in the use of biomeasures and the neuroscience of emotion through two National Institutes of Health fellowships. He has published numerous articles in peer‐reviewed science journals, gives lectures nationally and internationally, and is a leader in the new field of social neuroscience. He has recently presented at the Advertising Research Foundation and the World Advertising Research Conference, and is the guest editor of the International Journal of Advertising special issue on neuromarketing. Dr. Caleb Siefert is a Senior Scientist at Innerscope Research, LLC. He was previously the co‐chief psychologist for the psychiatric inpatient unit at Massachusetts General Hospital, senior research and statistical consultant for the inpatient research and development group, senior investigator for the Psychological Evaluation and Research Laboratory (PEaRL) at MGH, and Instructor at Harvard Medical School. In addition to being an active practicing clinician who conducts psychotherapy as well as personality and neuropsychological assessments, Dr. Siefert was also a Principal Investigator for multiple research studies at MGH and a co‐investigator and statistical/research design consultant for multiple research labs at several academic institutions. Dr. Siefert received his B.A. in with high honors from Michigan State University, his M.A. in Clinical Psychology from Adelphi University and his Ph.D. in Clinical Psychology from Adelphi University. Dr. Ravi Kothuri, Vice Presient of Research and Development at Innerscope Research, LLC, has been an active researcher and innovator in the database industry (esp. spatial and multimedia) for the past 15 years. Over his ten year tenure with Oracle, he architected various software products. He also holds over twenty‐five patents on specific Oracle technology and has authored numerous articles for database conferences and journals. His depth and breadth of knowledge has led to him delivering keynote addresses at conferences, and presenting at DARPA and NSF review panels. Dr. Kothuri has also authored a book on Oracle Spatial Technology and has taught part‐
time at Boston University. He received his Ph.D. in Computer Science from the University of California Santa Barbara, and was in the Executive Program at MIT Sloan. He is a professional member of the IEEE and the ACM, and is an active member in the database research community. Deborah Fair, a researcher at Innerscope Research, LLC, also contributed to this paper. About Innerscope Research, LLC: Innerscope Research® is dedicated to solving difficult market research questions by measuring and analyzing subconscious emotional responses to media. With its breakthrough Biometric Monitoring System™, Innerscope accurately predicts consumer behaviors, providing Fortune 100 companies with an unprecedented level of consumer insight. Founded by Harvard and MIT scientists, Innerscope leverages the latest advances in biometrics, neuroscience and eye tracking to measure moment‐to‐moment emotional engagement, the primary driver of behavior and choice. For more information, visit www.innerscope.com. Some sample comments from Innerscope clients include: •
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“This is the most valuable research we have ever conducted.” President, Major Packaged Food Company “I have never seen a response like this to research in my nine years here.” SVP Ad Sales Research, Major TV Network “We should be using this type of research in everything we produce.” President of Ad Sales, Major TV Network “This should replace dial testing.” Director of Research, Cable TV Network “Brilliant. This was incredibly helpful.” Chief Strategy Officer, Major Toy Manufacturer “Finally, research results that lead to actual decisions. Terrific.” Director of Research, Consumer Package Goods Company “These results are fantastic ‐‐ you guys rock!” Director of Research, Cable TV Network Innerscope Research, LLC © 2009 3 A REVIEW OF STUDIES USING BIOMETRIC MEASURES OF EMOTION TO PREDICT BEHAVIORS 1.0 Introduction: Why Measuring Unconscious Emotional Response Matters Human emotions are a mixture of complex neurobiological, physiological and psychological phenomena. Decades of research have significantly advanced our understanding of the mechanisms of emotion in general and their unconscious influences in particular. This research has revealed that understanding unconscious emotional response is critical to understanding and predicting many if not all human behaviors. Using a variety of research methodologies, a convergence of key findings has emerged across social psychology, psychophysiology, neuroscience, and cognitive science. Advances in these fields have demonstrated five key points regarding emotional response: • Emotional responses are the primary drivers of a wide variety of behaviors • The vast majority of brain processing related to emotions, occurs below conscious awareness, with limited or no direct connectivity to language centers of the brain, significantly limiting the accuracy of self‐reporting of unconscious emotional experiences • Traditional models suggesting that people “think” first and then rationally decide how they will “feel” and behave while following a “rational” thought process are highly inaccurate • Emotion systems in the deep structures of the brain initially generate changes in bodily responses below and beyond the control of conscious awareness prior to “rational” thought • Biometric measures of emotion systems reflect information processing in the deep structures of the brain, below conscious awareness, and are manifest through peripheral organ systems in the body that are readily accessible with modern sensors. By leveraging scientific and technological advances and using proprietary methodologies grounded in neuroscience, Innerscope Research measures unconscious and preconscious emotional responses to better understand how consumers respond to media in order to explain behaviors that are not amenable to rational models (e.g., why consumers say one thing and do another). The following introduction to the scientific literature discusses the relationship between emotions and cognitions, their powerful effect on our thoughts and actions, and the science behind Innerscope’s methodology of measuring the emotions that are predictive of human behavior. 2.0 Literature Review 2.1 The Power of Unconscious Emotional Responses and their Effect on Behavior Multidisciplinary research over the past twenty years has proven the power of emotions in our lives including their direct influence on learning, memory, decision‐making, and behavior. Some examples with references in the academic literature include: Innerscope Research, LLC © 2009 4 • Unconscious and preconscious processing regulate and influence virtually all of our higher order processing including learning, memory, and decision making (Bubier & Drabick, 2008; Bargh, 2007; Zajonc, 2000; Carter & Smith‐Pasqualinin, 2004) • Memories are organized around emotions, affecting what we remember and what we forget (e.g. Marci et al., 2007; Neidenthal et al., 1999; Bradley & Baddeley, 1990; Schacter, 2001) • Emotional experiences at the time we recognize or recall an experience confounds and interacts with the accuracy of conscious reporting and recall of our memories (e.g., Schacter, 2001; Monahan, 1998; Zajonc, 2000) • Stimuli that engage us emotionally draw our attention and focus (e.g., Tomaka & Palacios‐Esquivel, 2007; Lang et al., 1997), have a powerful impact on the formation of attitudes (Zajonc, 2008), and even influence response to medical treatments (Fraguas et al., 2007). Thus, a greater understanding of unconscious and preconscious emotional responses provides a clearer understanding of what will be learned and what decision‐making behavior can be expected. 2.2 “Feeling” before “Thinking”: The Unconscious Nature of Emotional Responses The notion that we experience emotions before we consciously are aware and process them is now widely accepted within the scientific community (Davis & Lang, 2001; Damasio, 1994; Greenwald, 1992; LeDoux, 2002; Lieberman, 2007; Murphy & Zajonc, 1993; Schacter, 2001). Emotional responses are complex combinations of unconsciously generated deep brain responses that produce reactions in the peripheral nervous system such as accelerations in heart rate, fluctuations in sweat activity, and changes in breathing (Damasio, 1994; Marci et al., 2007; Panksepp, 1998). These reactions are a result of the direct link between the deep structures of the brain involved in the immediate evaluation of perceptual information and the peripheral nervous system – connections that evolved long before human language and consciousness emerged (Dywan et al., 2008; LeDoux, 1996, 2002; Morris et al., 1998). For example, consider what happens if someone walking along in the forest suddenly sees a bear or hears a humorous joke. Their heart rate increases, breathing quickens, sweat glands become activated and the individual prepares for one of two very different but important behavioral responses: fight‐or‐
flight or the uniquely human breathy exhalation and chortle of laughter. These responses are regulated by the autonomic nervous system and the resultant behavioral expressions are initiated independently and outside of consciousness. The neural system prepares the body well before the person has time to think. Within moments, the unconscious deep brain structures send information to the conscious brain that informs conscious thinking (e.g., why focusing on the stimulus is important, and identifying the goals and needs in that situation). Only at the point of conscious processing does the feeling of “fear” or “humor” emerge. While the conscious brain can only consider a few things at once, the unconscious and preconscious parts of the brain processes thousands of pieces of information simultaneously and conveys them to higher brain structures and the body through the peripheral nervous system within milliseconds via an emotional response. Emotional responses in deep structures of the brain, reflected in the body, direct higher order brain regions to dedicate resources and process relevant information for immediate and future use. Innerscope Research, LLC © 2009 5 Once looked upon as “troublesome” interlopers that disrupted “rational” thoughts, modern views of emotional response evolved considerably. We now understand the importance of emotional responses: they allow us to organize and respond in a more efficient manner to the cluttered world around us. Emotional responses in deep structures of the brain(that are reflected in the body) direct higher order brain regions to dedicate resources and process relevant information for future use. Unconscious and preconscious emotional responses provide vital information that: • Orients attention to the most relevant environmental stimuli (the bear, the closest tree, the person telling the joke) • Activates motivating goal states (the need to get to safety, the need to relax and build non‐
threatening social relationships) • Results in important behavioral responses (freeze, head for the tree, reward joke teller with compliments). In summary, reactions of the emotional unconsciousness occurring prior to and very often well beyond conscious awareness are important for our survival and for the formation of social relationships. In dramatic circumstances such as seeing a bear or hearing a joke, it is easy to demonstrate the role of the bodily responses to such stimuli in threat or extreme social situations. What is much more difficult to observe (without the aid of sophisticated technology) is the essential emotional responses that are part of our daily lives, moment‐to‐moment, minute‐by‐minute, and how they influence our behaviors and decisions. The fact that we are unaware of how our emotions are affecting us on an unconscious level actually makes it harder for us to counteract their effects. The old models of “top‐down” processing and conscious “rational” dominance over emotions are tumbling to new models that emphasize the importance of “bottom‐up” emotional influence on cognition. The new models clearly show how emotions influence what we think about, pay attention to, and seek to learn as we organize goals, mobilize for action, orient our attention, and facilitate social communication (Critchley, 2005; Lang et al., 1997; Davis, 2000; Davis & Lang, 2001; Bradley et al., 2000). 2.3 The Biology of Emotional Responses & the Autonomic Nervous System The peripheral nervous system (PNS) connects the deep structures of the brain via the spinal cord to the body and its many end organs. The PNS consists of two separate branches: the somatic nervous system associated with voluntary control of various systems (e.g., muscle movement, touch, hearing, etc.) and the autonomic nervous system (ANS) associated with unconscious control of support functions (e.g., heart rate, perspiration, and breathing). Transmitted information from the primary senses goes to the deep brain structures involved in emotion generation and travels through the PNS to a variety of organs. These organs include: (1) the heart to regulate rate and contractile force; (2) blood vessels in muscles to regulate constriction and dilation and prepare for movement; (3) specialized sweat glands in the skin to regulate hand sweat and grip strength; (4) the lungs to regulate depth and rate of oxygen intake; and (5) the pupils to regulate light intake and optimize vision acuity. This transmission of information occurs below conscious awareness. The ANS responds very quickly and efficiently as the parts of the deep structures of the brain that first evaluate Innerscope Research, LLC © 2009 6 external stimuli are also capable of rapidly influencing and changing key processes in the body to prepare the individual for behaviors or to help organize and attend to what is most important or relevant in the external world. Thus, the ANS provides a link between the information processing centers of the brain, mediated by emotional response, and the functional systems in the body that reflect that response. Scientists have measured activity in the ANS to study a wide range of emotional responses including amusement, depression, anger, relaxation, anxiety, fear, laughter, sadness and pleasure for many years (e.g., Marci et al., 2004; Marci et al., 2007; Fraguas et al., 2007; Ray et al., 2008; Sokhadze, 2007; Hajcak et al., 2003; Min et al., 2005; LeDoux, 1996). 2.4 Measuring Emotional Responses Using Biometrics While the bear and laughter examples demonstrate extreme instances of how preconscious emotions are expressed via the ANS, the same processes occurs during the most subtle emotional responses to moment‐to‐moment, minute‐by‐minute daily life events – including and especially during emotional responses to media. Using state‐of‐the‐art medical grade technologies, Innerscope measures these subtle, unconscious and preconscious responses as they occur through four channels of biometric data related to the ANS: (1) Hand sweat and micro‐perspirations via 32‐bit skin conductivity (2) Heart rate and heart rate variability via medical grade electrocardiography (3) Breathing rates and fluctuations via respiratory transducers (4) Movement via multi‐axial accelerometers. Visual attention and pupil dilation are often used as a fifth channel of biologically based information. Changes caused by ANS activity measured with these multiple channels have been consistently linked to the unconscious processing of emotional stimuli (e.g., Boiten et al., 1994; Boucsein, 1992; Hubert & deJong‐Meyer, 1990; Levenson, 1992, 1994; Lang, 1995; Ohman et al., 2000; Nyklicek et al., 1997; Marci et al, 2004). A number of similar studies have also demonstrated the importance of the ANS in measuring emotions: • ANS reactivity to even a mild stimulus/experience produces measurable responses • Continuous, moment‐to‐moment changes in ANS channels are meaningful and reflective of emotional reactions to stimuli • The ANS is sensitive to all forms of sensory information (e.g., auditory, visual, smell, etc.). ANS changes are also caused by exposure to positive and negative still images, pleasant and unpleasant film clips, even various forms of noise. (Hamm et al., 2003; Lang et al., 2001; Palomba et al., 2000; Sokhadze, 2007; Gomez & Danuser, 2004; Nyklicek et al., 1997). Innerscope Research, LLC © 2009 7 3.0 A Model for Using Emotions to Understand and Predict Consumer Behaviors Innerscope has developed a model to predict complex consumer behaviors based on a measure of emotional engagement that captures more than just positive or negative emotional responses. Innerscope calculates the magnitude of engagement at an unconscious level by assessing the degree to which multiple study participants in an audience are having an emotional response and the timing of that emotional response (Marci, 2006). The formula for biometric emotional engagement is as follows: Intensity
(impact)
Synchrony
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Engagement
Thus, a television advertisement (or any media stimulus) that generates higher levels of emotional involvement (Intensity) and sustained attention in the audience (Synchrony) results in higher engagement scores. When audiences respond emotionally, engagement levels increase suggesting that people are “in‐tune” with the media content. It is important to note that biometric emotional engagement is an aggregated measure. For example, if only one audience member leans forward or has a jump in heart rate in response to a particular creative element or moment, the impact on engagement will not be significant. However, if large portions of the audience lean forward or increase heart rate at the same time it indicates that all members are responding to the same creative element and engagement scores increase. Innerscope has conducted a series of validation studies to show that advertisements and media content that produce higher engagement scores are more effective at “breaking through the clutter” and are more likely to drive desired consumer behaviors. This is true for advertisements, magazine covers, websites, video games, shopping, and packaging. Innerscope’s validation studies show that engagement levels relate to behavioral outcomes like channel changing, fast‐forwarding, purchase behavior, and online buzz (i.e., number of views and comments an advertisement receives online). The sections below describe a variety of studies that demonstrate Innerscope’s emotional engagement can be used to predict consumer behaviors. 3.1 Reliability of Emotional Engagement In order to assess reliability of measurements obtained using Innerscope’s equipment and study procedures for measuring audience engagement, a sample of 40 participants viewed the same television show while being biometrically monitored. Participants were prescreened and matched for age, gender distribution, frequency of television watching, and ratings for the frequency with which they watched the specific test show. Sampling inclusion criteria for participation was restricted to create cohesive and highly similar groups that also reflected the intended target audience for the program (based on data provided to Innerscope by the show’s creators). Groups differed with regard to their reported viewing habits of the program: twenty of the participants were “core viewers” (i.e. meaning they rated Innerscope Research, LLC © 2009 8 themselves as making effort to watch the show regularly and reported that they enjoyed it very much) and twenty of the participants were “occasional viewers” (who reported that they enjoyed the show but only watched it on occasion when they got the chance and also rated the show as enjoyable). Figure 1. Comparison of Mean Engagement Scores for Core Viewers and Occasional Viewers for Target Show 1 with Commercial Pods. 80
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Engagement scores were calculated for both groups and compared. Biometric data was then collected as participants viewed the program. For each show segment and each ad pod, mean engagement scores were calculated by averaging bin level engagement scores across the show segment or ad pod. As can be seen in Figure 1, and as would be expected, core viewers’ scores were consistently higher than occasional viewers (a consistent Innerscope finding) for both the show content and the ad content. Interestingly, and again as would be expected from two groups of reporting familiarity and affinity for the show, the engagement patterns were almost identical differing only by level. The mean engagement scores were significantly correlated (r = 0.76). This data suggests that, as expected, level of engagement is likely to reflect emotional involvement with the show on a moment‐to‐moment basis and the pattern of engagement (i.e. increases and decreases in engagement) was highly reliable across groups. 3.2 The Super Bowl Study: Predicting Online “Buzz” Innerscope’s Super Bowl study involved an audience of 30 participants (15 Giants Fans and 15 Patriots Fans) who agreed to watch the Super Bowl XLII while being biometrically monitored. Groups were matched for age and the frequency with which they watched football games (i.e. they were required to have watched more than 6 games, but fewer than 10 during the season). Giants’ fans and Patriots’ fans watched the game and ads in separate rooms and watched in real time (i.e. as the game was broadcast and played live). Scores based on Emotional Engagement® for each of the ads shown during the Super Bowl were calculated using the entire sample (i.e. N = 30). Additional data for Super Bowl ads included in this study (i.e. dial and self‐report) was obtained from on‐line reports published by independent groups. Of note, Innerscope Research, LLC © 2009 these other methods made use of substantially larger sample sizes. A well known internet video site, MySpace.com, ran a televised in‐game promotion during the Super Bowl informing viewers that they would post all Super Bowl ads immediately after the game concluded. MySpace.com then tracked the number of views and the number of comments each ad received over the six months following the Super Bowl. Thus, outcome variables were the number of views and number of comments each ad received. 9 Figure 2. Threshold of High Engagement Levels During Super Bowl XLII Show Patriots Fans Were More Engaged During the First Half of the Game While Giants Fans Became More Engaged in the End. 120%
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Correlations between outcome variables and self‐report/dial/biometric data are displayed in Table 1. In addition to producing the strongest bivariate correlation (0.62, p <0.01), regression analysis (for predicting views) indicated that, after inclusion of self‐report data and dial data on blocks 1 and 2, respectively, inclusion of Innerscope’s biometric data into the model resulted in a substantial increase in predicted variance (R‐Square change = 0.10; F = 6.29, p < .05). An even stronger effect was obtained for comments, where the inclusion of Innerscope’s biometrics into the model produced a substantial increase in predicted variance (R‐Square change = 0.29; F = 19.48, p < .001). Not only do these results speak to the predictive power of biometrics and emotional engagement metrics, they support the hypothesis that the underlying construct tapped by Innerscope’s biometric measures (unconscious emotional engagement) is unique and adds incremental predictive power to research models which attempt to predict actual real‐world behaviors. The fact that Innerscope’s emotional engagement metrics are more predictive than methods which require substantially more participants to give conscious responses illustrates the tremendous potential of assessing the ANS at on unconscious level. Innerscope Research, LLC © 2009 Table 1. Correlations Between Ad Data and Number of Comments and Number of Views. Comments Views Innerscope Biometrics 0.62** 0.49** Dial Testing 0.31* 0.43* Self‐Report Ratings 0.19 0.29* 10 Note. ** = p < .01; * = p < .05 Additional analyses looked at published results from an EEG based methodology (Sands Research) to compare the top ads in levels of performance with online views and comments. As shown in Figure 3, the top Innerscope ad (Amp Energy Drink, Jumper Cables) showed significantly more views (horizontal axis) and comments (vertical axis) than the top dial test reported by USA Today (Budweiser, Clydesdale) and the top EEG ad reported by Sands Research (Pepsi, Bob’s House). The results from Super Bowl XLII demonstrate an important component of predictive validation. While the Super Bowl is a unique environment for advertising, it also offers a uniquea opportunity for demonstrating the utility of new metrics compared with existing standards. The public nature of the game and the goal of many advertisers to achieve some level of “buzz” for their multi‐million dollar investment suggest that online “word‐of‐mouth” as reflected in the number of views and comments online are a critical and available benchmark to use for comparison and validation. Figure 3. Number of Views and Comments by Methodology for the Top Ads for Super Bowl XLII. A visual display of the results for the top ads by methodology using MySpace data showing number of views and comments emphasizes the differences between methodologies. Measuring unconscious emotional engagement is a better predictor of the deep connection with the audience that drives behavioral responses.
Comparison of MySpace Results for the Top Ad Measured Using Different Methodologies
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Innerscope Research, LLC © 2009 11 3.3 Predicting Sales with Emotional Engagement Two ads with radically different creative and conceptual framework and execution for marketing the same quick service restaurant company were tested using Innerscope biometrics. Results compared with published in market sales results (independently verified by the agency of record) showed that the version with the steadily increasing emotional engagement scores (Execution A, 30 seconds) outperformed the version with the drop in engagement scores in the second half (Execution B, 45 seconds). The results are despite the fact that execution B was 15 seconds longer (Figure 4). The results support other unpublished data that higher levels of emotional engagement result in increased sales for advertisers. Figure 4. Different Patterns of Engagement for TV Ads Lead to Different In Market Sales. B
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3.4 Predicting Television Program Success A series of Innerscope studies showed that engagement levels of TV programming of similar genres in comparable audience segments corresponded with in market success of the show. Thus, shows with higher levels of engagement were more likely to be successful than shows with lower levels of engagement. In addition, low engagement corresponded with shows that were subsequently cancelled. Figure 5. Differences in Engagement Levels for TV Programs Relate to in Market Success.
TEST 1 TEST 2 TEST 3 TEST 4 TEST 5
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Innerscope Research, LLC © 2009 12 3.5 Relationship with Self­Report The program experience for two media reels featuring different content produced a significant difference in engagement. This difference closely mirrored the top two scores of reported intent to view results, which were significantly higher in the group with the higher emotional engagement scores (Figure 6). The results are consistent with findings that allow Innerscope’s unconscious biometric responses to complement conscious, self‐report measures. Figure 6. Relationship Between Engagement Levels and Self‐Report Intent to View Engagement
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3.6 Predicting Fast­Forward Behavior Using Biometrics In addition to the validation studies presented above, Innerscope recently reported findings with TiVo, Inc. The two companies shared data on two cable programs of one hour duration each. Innerscope tested 40 participants reporting to be fans of the show live in two different major metropolitan cities. Results showed that levels of engagement were highly correlated with the probability of watching an ad in its entirety. Figure 16 shows the Innerscope levels of engagement and TiVo moment‐by‐moment Stop‐Watch data for the five ad pods during the first hour of programming normalized to compare the two scores (z‐score transformation). Levels of emotional engagement in many cases lead the fast‐
forwarding behavior, suggesting that immediately following decreases or increases in emotional engagement, the probability of viewing an ad decreases or increases, respectively. Figure 7. Relationship Between Engagement Levels and Probability of Fast‐Forwarding an Ad.
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Innerscope Research, LLC © 2009 13 3.7 Building a Biometric Knowledge Base and Database With the establishment of a reliable and well‐validated metric, the opportunity to build a biometric database of advertisements presents itself. Innerscope now has over 800 television ads (30‐second advertisements from national advertisers) tested in a wide variety of contexts ranging from scripted, network, prime‐time drama to niche cable network reality shows in a comparative database. The database complements the Innerscope knowledge base that comes from testing thousands of ads in scores of programs. Innerscope tests all of its advertising in a context, and the level of show engagement is carefully controlled for each test. The database shows a normal distribution (Figure 8) across categories. Innerscope is able to make comparisons within the major categories as well, including consumer package goods, telecommunications, financial, automobile, and pharmaceuticals. Each 30‐
scond ad tested gets a performance rating on one of three measures: (1) mean engagement, (2) maximum engagement, and (3) biometric build. The scores allow easy comparison to other ads in the study as well as to the universe of emotional responses measured by Innerscope. Figure 8. The Distribution of Ads in the Innerscope Biometric Database of over 800 Ads. A visual display of the Innerscope Biometric Database consisting of over 800 television advertisements shown in a wide variety of programming contexts including prime‐time network drama and cable reality shows. Each 30‐scond ad tested gets a performance rating on one of three measures: (1) mean engagement, (2) maximum engagement, and (3) biometric build. The scores allow easy comparison to other ads in the study as well as to the universe of emotional responses measured by Innerscope.
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Innerscope Research, LLC © 2009 14 4.0 Summary & Conclusions Findings from neuroscience research over the past decade clearly show that unconscious emotions drive behavior. Building on this body of work, Innerscope’s methodology leverages these findings and advances in sensing technology and analysis to measure consumers’ emotional responses to media stimuli in order to better understand and predict behavior. By using a biologically based measure of emotional engagement that combines unconscious attention with emotional intensity, Innerscope’s results enable companies to better understand their customers – what they will pass over, what they will attend to, and what they will resonate with, ultimately influencing the final purchase. Technological advances and measurement applications pioneered by Innerscope Research have created an unobtrusive, medical grade, portable system used to passively monitor individuals and audiences in any environment. This allows Innerscope to measure emotions when they happen (moment‐to‐moment measurement), where they happen (in the ANS), in the real situations in which they happen (in real‐
world context). Taking advantage of Innerscope’s patent pending measures of emotional engagement and technological advances in medical sciences helps businesses derive deeper insights into the consumer’s experience to understand what they say, what they do, and their willingness to become more engaged in the product. Harnessing the power of these methods to understand how consumers think about, experience, and engage emotionally with brands, products, and advertising content is essential for businesses that wish to stay successful (Zaltman, 2003). Innerscope Research, LLC © 2009 15 References Bargh, J. A. (2007). Social Psychology and the unconscious: The automaticity of higher mental processes. New York: Psychology Press. Boiten, F. A., Frijda, N. H., & Wientjes, C. J. E. (1994). Emotions and respiratory patterns: Review and critical analysis. International Journal of Psychophysiology, 17, 103–128. Boucsein, W. (1992). Electrodermal activity. New York: Plenum Press. Bradley, M. M., Codispoti, M., Cuthbert, B. N., & Lang, P. J. (2000). Emotion and motivation I: Defensive and appetitive reactions in picture processing. Emotion, 3, 276‐298. Bradley, B. P., & Baddeley, A. D. (1990). Emotional factors in forgetting. Psychological Medicine, 20, 351‐
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