Slides from an upcoming webinar in the McGill University Brain to Society Decision and Behavioral Seminar Series

1. Brain To Society Decision and Behavior Seminar Series
Sylvain Sénécal
Tech3Lab, HEC Montréal
June 6, 2018

2. Over the next hour…
• Consumer neuroscience
• Measurement
• Tech3Lab
• Triangulation
• Research project
• Q&A

3. Consumer neuroscience

4. Consumer neuroscience (Vs. Neuromarketing)
• Consumer neuroscience research
• uses quantitative empirical research methods
• to measure nonconscious preferences and executive cognitive processes
• such as decision making (Harris et al. 2018).
• Consumer neuroscience includes
• a range of neuroscientific and physiological research techniques
• to measure changes in neural electrical or metabolic activity
• to study cognitive and affective processes (Ahlert, Kenning, & Plassmann, 2006; Ciorciari, 2012).

5. Consumer neuroscience research
• Most research uses a single neuroscientific method/measure (Harris et al. 2018)
• Eyetracking, fMRI, or EEG.
• Neuroscientific data triangulation is complex
• Technical issues related to data synchronization and signal latency need to be addressed.
• Some labs can now triangulate neuroscientific data
• Such as the Tech3Lab

6. Measurement

7. Body Measures Brain Measures
Somatic Measures
(SNS)
Facial Expressions
Facial muscle
movements
Eye movements and
fixations
Eye blinks and the
startle reflex
Automatic
Measures (ANS)
Electrodermal
activity (EDA)
Heart rate
Blood Pressure
Respiration
Behavioral response
times
Pupil dilation
Blood flow
measures
Electrical fields
(EEG)
Blood oxygenation
Positron emissions
(PET)
Electrical fields
(EEG)
Magnetic fields
(MEG)
Genco, Pohlmann, and Steidl (2013)
Some Neuroscience Measures

9. Tech3Lab

10. Tech3Lab

18. Data triangulation infrastructure

25. Negative emotion
Positive emotion
Negative emotion
Cognitive load

26. A recent research project

27. The tone of voice of tourism brands
on social media: Does it matter?
Barcelos, R. H., Dantas, D. C., & Sénécal, S
R&R, Tourism Management

28. Corporate voice
“Hello Ms. [customer]. Please
let us know when you are
planning to visit so we may
further assist you. Thank you.
Best regards, Social Media Team
at the [hotel name].”
Human voice
“Hello beautiful people! Happy
Monday!! Welcome back from
the weekend. Hope it was a
great one for you all. We wish
you yet another wonderful
week. ☺”

29. Corporate vs. Human voice
• Corporate voice
• A more distant and formal style traditionally used by companies.
• Human voice
• A more natural, close, and human style of online communication.

30. Research Question and Objective
• Given that social media enables more direct contact with customers,
• Should a brand present itself in a more personal and human way in these contexts?
• Alternatively, should a brand keep its distance and adopt a less intimate approach?
• Investigate how the tone of voice used by a tourism brand on social media impacts
customers’ attitudes and information processing.

31. Background literature
• Social media is changing the decision-making processes of tourism
consumers (Hudson & Thal, 2013).
• The concept of a conversational human voice is still a relatively unexplored
concept
• However, research shows that it increases customer engagement and brand evaluations
(Barcelos, Dantas & Sénécal, 2018; Schamari & Schaefers, 2015; van Noort & Willemsen,
2012).

32. Background literature
• Dual-process models for online consumer behavior
• content (systematic/central) and non-content cues (heuristic/peripheral)
• significantly influence information processing by users in various online contexts (Wirth et al.,
2007).
• Both systematic and heuristic cues in online communities are important
determinants of
• customers’ behavioral intention in online review sites (Zhang et al. 2014).
• Relevance and completeness of tourism information (content cues) as well
as web page design (a non-content cue) are positively related to
• users’ destination image formation on social media (Kim et al. 2017).

33. Background literature
• Tone of voice as a peripheral cue
• A brand using a human voice is expected to transmit more emotions than one using a
corporate voice
• Peripheral cues associated with the tone of voice should have a stronger influence on a
consumer’s information processing when the brand is using a human voice.
• According to some studies about affect-cognition models and attribute framing,
• People exposed to positively framed messages that evoke positive emotional states or moods
would engage in a more heuristic processing (Eagly & Chaiken, 1993; Gonzalez et al., 2005;
Kuvaas & Selart, 2004).
• Yang (2015) identified different patterns of information search due to the consumers’
elaboration mode (central or peripheral) using measures of ocular fixation duration.

34. Hypothesis
• Consumer should engage in more heuristic patterns of processing and information search
when exposed to messages using human voice than when exposed to messages using
corporate voice.
• The more human (vs. corporate) the voice used by a tourism brand on social media, the
more heuristic (vs. systematic) are consumers’ patterns of information search.

35. Method
• 30 participants (16 female, 14 male)
• Task
• Look at a hotel brand page on Facebook for as long as they wished and then decide if they wanted
to make a reservation.
• Design
• Each participant was randomly assigned to one of the two versions of the hotel brand page (human
or corporate voice).
• Participants’ eye fixations, pupil diameter, and saccades were recorded with a Tobii X-60
eye-tracker (Tobii Technology AB).
• All participants had normal or corrected-to-normal vision and were pre-screened for
glasses, laser eye surgery, astigmatism, epilepsy, and neurological and psychiatric
diagnoses.

36. Method
Measure Definition Expectations according to Hypothesis
Total fixation
duration
Time (in milliseconds) spent on a
stimulus (page or AOI within the
page)
Longer fixation durations and ratios on
AOIs containing content cues (text) in
the corporate voice scenario. Longer
fixation durations and ratios on AOIs
containing non-content cues (pictures) in
the human voice scenario.
Fixation ratio Time of total fixation duration on a
stimulus (page or AOI within the
page) divided by the total time at the
brand page
Number of
saccades
Number of eye movements between
one fixation and another on the page
More saccades and saccades per second
in the human voice scenario, since the
information search is expected to be
more heuristic and less systematic.Saccade ratio Total number of saccades divided by
the total time (in seconds) spent on a
page
Time to first
fixation
Time (in milliseconds) spent on a
page before looking at the stimulus
(page or AOI within the page)
Different times for first fixation at
different AOIs on the brand page.
Pupil size Pupil diameter (in mm) for each eye
fixation on a stimulus (page or AOI
within the page). Pupil size is an
estimation of cognitive load.
Increased pupil size on AOIs containing
content cues (text) in the corporate voice
scenario. Increased pupil size on AOIs
containing non-content cues (pictures) in
the human voice scenario.

37. Results (Main Study)
Brand page using corporate voice Brand page using human voice
Fixation duration (green to red)
Cognitive load (blue)

38. Fixation duration and areas of interest (AOI)
Table 2. T-tests for means of total fixation duration.
Area of Interest (AOI)
Means (in seconds)
F(df = 29) p
corporate voice human voice
Header: hotel information 2.943 1.762 3.461 .073
Post 1: main text from the hotel 7.311 4.579 3.230 .083
Post 2: profile pictures of the hotel 0 .050 3.291 .080
Post 4 (whole post) 5.836 .826 3.483 .073
Post 4: main text from customer 2.007 .551 3.674 .066
Post 5 (whole post) 3.088 .682 3.551 .070
Post 5: replies from the hotel to customers 1.909 .358 3.264 .082
Post 5: main text from customer 1.179 .324 3.200 .084
Post 23 (whole post) .060 0 2.973 .096
Only AOIs with means significantly different at p < .10 are shown. n = 30.

39. Cognitive load and AOI
Table 4. T-tests for means of cognitive load.
Area of Interest (AOI)
Means (sums of standardized
pupil sizes)
F(df = 29) p
corporate voice human voice
Cover photo 95.368 154.339 3.627 .067
Post 3: profile pictures of customers 7.244 0.117 6.767 .015
Post 4: main text from customer 101.274 44.774 4.987 .034
Post 7 (whole post) 38.444 11.445 5.280 .029
Post 7: main text from customer 31.476 7.017 5.213 .030
Post 13: main text from customer 32.729 13.106 3.576 .069
Post 22 (whole post) 12.828 1.186 5.595 .025
Post 22: main text from customer 12.127 1.072 5.313 .029
Post 23: profile pictures of customers 0.466 0.000 3.650 .066
Post 25: main text from the hotel 15.116 4.988 3.867 .059
Post 25: profile pictures of customers 1.950 0.000 4.958 .034
Only AOIs with means significantly different at p < .10 are shown. n = 30.

40. Discussion
• Taken together, the results of these tests support our hypothesis,
• The more human (vs. corporate) the voice used by the hotel on social
media, the more heuristic (vs. systematic) should be the consumers’
patterns of information search.
• Participants looking at the hotel brand page using corporate voice exhibited an increased
attention to the information about the hotel and the contents of the posts (both text and
pictures).
• Participants looking at the hotel brand page using human voice, on the other hand,
fixated in more diverse regions of the page, and were more interested than the
participants in the condition of corporate voice in a few AOIs such as the cover photo and
some profile pictures.

41. Triangulation and implications
for managers

42. Customer experience
assessment

46. Benchmarking and
segmentation

52. Thank you!
ss@hec.ca
tech3lab.hec.ca

53. Q&A

54. Some consumer neuroscience references
• Ariely, D., & Berns, G. S. (2010). Neuromarketing: The hope and hype of neuroimaging in business. Nature Reviews Neuroscience, 11(4),
284–292
• Smidts, Ale, Ming Hsu, Alan G. Sanfey, Maarten AS Boksem, Richard B. Ebstein, Scott A. Huettel, Joe W. Kable et al. "Advancing consumer
neuroscience." Marketing Letters 25, no. 3(2014): 257-267.
• Karmarkar, U. R., & Plassmann, H. (2017). Consumer Neuroscience: Past, Present, and Future. Organizational Research Methods,
1094428117730598.
• Plassmann, H., Venkatraman, V., Huettel, S., & Yoon, C. (2015). Consumer neuroscience: applications, challenges, and possible
solutions. Journal of Marketing Research, 52(4), 427-435.
• Harris, J. M., Ciorciari, J., & Gountas, J. (2018). Consumer neuroscience for marketing researchers. Journal of Consumer Behaviour.
• Wang, Y. J., & Minor, M. S. (2008). Validity, reliability, and applicability of psychophysiological techniques in marketing
research. Psychology & Marketing, 25(2), 197-232.
• Shaw, S. D., & Bagozzi, R. P. (2018). The neuropsychology of consumer behavior and marketing. Consumer Psychology Review, 1(1), 22-
40.
• Pozharliev, R., Verbeke, W. J., & Bagozzi, R. P. (2017). Social Consumer Neuroscience: Neurophysiological Measures of Advertising
Effectiveness in a Social Context. Journal of Advertising, 46(3), 351-362.