HON3Y is a mobile-based research platform at the intersection of emotional, contextual, and behavioral data. Participants experience the platform as any life-logging app, tagging and/or inputing behaviors as part of the research study. Researchers access an intimate view into the relationship between emotion states such as stress and happiness and consumer behaviors such as visiting a store or buying a specific product.
HON3Y is powered by emozia’s new “always on” method to map human emotion, context and behavioral patterns over time.
3. Participants experience the platform as any life-
logging app, tagging and/or inputing behaviors as
part of the research study.
Researchers access an intimate view into the
relationship between emotion states such as
stress and happiness and consumer behaviors
such as visiting a store or buying a specific
product.
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scan barcode
tag action
4. // MAKE EMOTION VISIBLE
What are the emotions that prevail before, during, and after key moments of behavior?
// UNDERSTAND CONTEXT
How other drivers like weather, transportation, physical activity, or sleep, play a role?
PLATFORM GOALS:
5. The Trend Behind the Platform
MOOD GEISTING
Technologies that read emotion for
management, visualization and manipulation.
a. Moodcasting
b. Customization
c. Choice
d. Visualization
9. CONTEXTUAL + BEHAVIORAL DATA VIA
EMOTION RECOGNITION TECHNOLOGY
Always on.
Includes multiple sources of “always on” data, can also
include facial and voice recognition.
Used to understand mood changes continuously over time
and/or around specific event.
10. HON3Y is powered by emozia’s new “always on”
method to map human emotion, context and
behavioral patterns over time.
The platform exists at the intersection of
emotive recognition technology and self-
reported or passive behavioral data (e.g.
visiting a store, drinking coffee, etc.).
Example: Coffee Pilot Study // Participants tag all coffee
consumption over 90 days, the platform analyzes emotion states,
activity, and contextual data prior and after consumption.
12. THE ENERGY DRINK PILOT STUDY
Emotive States:
- Energy (Physical + Mental)
- Stress
- Happiness
Research Behaviors:
- Purchase and consumption of any energy drink
- Manual tag or barcode scan
Contextual Data:
- Weather
- Location (Home vs. Work)
- Transportation (Walk vs. Drive)
Pilot Design:
- 25 Participants
- 90 Days
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participant number
13. 0.75%
0.76%
0.77%
0.78%
0.79%
0.8%
0.81%
0.82%
+% 2%4% +%1% 2% +%6% 0% +%6% +% 1%2% +%2%4%
Average%energy%emo8ve%data%around%consump8on,%%%%%%%%%%+/+24hours%
Energy% Consump8on%
Energy levels of a research participant
over a 24-hour period: 12 hours prior
and after coffee consumption.
This chart shows data for
one participant in the pilot
study. We can see how the
“energy” levels resulting
from ERT’s algorithm match
the expected boost after
consuming coffee.
Source: HON3Y pilot study, 2014
14. 0.7$
0.71$
0.72$
0.73$
0.74$
0.75$
0.76$
0.77$
0.78$
,$ 2$4$ ,$1$ 2$ ,$6$ 0$ +$6$ +$ 1$2$ +$2$4$
Average$emo6ve$data$around$consump6on,$$$$$$$$$$,/+24hours$
Stress$ Consump6on$
0.71%
0.72%
0.73%
0.74%
0.75%
0.76%
0.77%
+% 6% +% 3% 0%
Average%emo4ve%data%around%consump4on,%%%%%%%%%%%%+/+3hours!
Stress%
Consump4on%
We can zoom-in in time and
look at any period of time
prior and after the set
behavior (in this case
logging a cup of coffee).
These charts show “stress”
levels before and after
coffee consumption for
another random participant
in the pilot study.
Source: HON3Y pilot study, 2014
15. The decision tree establishes the main
drivers of the action or behavior in question.
This report is part of the standard reporting
suite.
In this case we are looking at emotive and
contextual factors influencing energy drink
consumption in order of importance.
Source: HON3Y pilot study, 2014, all participants
19. RETAIL VISIT PRODUCT CONSUMPTION PHYSICAL ACTIVITY
HEALTH BEHAVIORS NUTRITION RX ADHERENCE
TRANSPORTATION ENTERTAINMENT SERVICE USAGE
WIDE RANGE OF APPLICATIONS
20. SET-UP LENGTH OF STUDY,
RECRUIT PARTICIPANTS
PARTICIPANTS RECEIVE
INSTRUCTIONS TO ACCESS THE APP
RESEARCHERS RECEIVE
AGGREGATED DATA
STANDARD RESEARCH STUDY SET-UP
21. Research Design Tech Set-Up Deployment Field Final Report
Goals
ERT Data Design
Contextual Data Design
Behavior Identification
Sample Size
Recruiting (client owns)
Invitation
Follow-ups
Behavior tracking
mechanism set-up:
- Barcode scan
- Geofence
- Self-reported
App store set-up
Invitation deployment
Calibration report (2W)
Pulse report (45D)
Data Analysis
Standard Report
Presentation
3 DAYS 7 DAYS 3 DAYS 90 DAYS 2 WEEKS
22. H O N 3 Y
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participant number
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Participant logs in using
her unique code
Home shows activity log
and logging options*
User taps log area
Home screen shows
updated log number
H O N 3 Y
Tuesday, February 17
11:05:36 AM
19 17 31
DAYS
ACTIVE
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REMAINING
H O N 3 Y
Tuesday, February 17
11:05:36 AM
19 17 31
DAYS
ACTIVE
LOGS
DAYS
REMAINING
scan barcode
tag action
scan barcode
tag action
scan barcode
tag action
SIMPLE PARTICIPANT EXPERIENCE
*illustrative