From mobile data to smart life.

Young Sohn – President and CSO Samsung Electronics

“In the end we really want to know how sensors can help us to better understand our body and our health.

Why do we have to wait to see a doctor to understand what happens inside our body?

In the future there will be a lot more home diagnosis and preventive healthcare.

If not, we’ll be marching straight into a financial disaster.”

De Tijd, 3rd June 2015

Devices will need to be cognitiveif we want to create personalized experiences

Sync Me See Me Know Me Be Me

direct maildemographics

1928

connectedexperience

telemarketing+ telephone

1980

CRM+ customer history

1990

behavioralmarketing+ behavioral profiling

2000

socialmarketing+ social circle

2008

+ real-time context

2015

EVOLUTION of customer engagement

Increasingly connected & personalized

connectedexperience

+ real-time context

2015transforming marketinginto 1-to-1 Coaching

Declared

Observed

ContentStructured, explicit, self-declared, and static

ContextUnstructured, time-

series, observed, and dynamic

TWO sides to the data story

ExpectedValue

User Acceptance

Accelerometer

Gyroscope

In-App Usage

Wi-FiGPS/Location

Light Sensor

Browsing History

Calendar

Messages

GSR/HR

Microphone

Camera

USER ACCEPTANCE of sensor data is defined by the expected value

sensor data is the source for context-awareness

Sentiance unlocks contextual mobile experiences by mining sensor data on smartphones, wearables and connected devices to understand and predict the context, behavior

and mood of your mobile audience.

From mobile data to smart life.

sentiancecontext suite

sentianceplatform

night owl

long commute

green commuter

at lunch

shopping

L2 moments

commute home

L3 profile segments

SDK

L1 events

at the gym

parent (has kids)

on a trainnoisy environment

in company

SENSOR DATA

PERSONALIZATION based on sensor data

sense and interpret the contextual cues of a mobile user

uncover habits and predict human behavior

learn about the ever-changing Personalities of a mobile user

L2 moments

L3 profile segments

L1 events

Layer 1

Layer 2

Layer 3

aggressive driver

…

…waking

up

…

pet owner

sleeping

walking running

car subwaytrain

on the bus

boat

sitting standing

airplane*

biking

arriving at home, work, the gym, ...

shopping

lunchinactive

noisy environment*

in a meeting

horse*

home

working

in company*

full-time worker

workaholic

urban

watching tv

motorcycle

agitated*

suddenly stopped

tram

climbing*

*subject to sensor availability/capability and/or user permissions

CONTEXT defines the moment

situationalawareness goes beyondsimple geo-fencing. In thebackground, pervasive sensing, learning and classifying the situation a user is in.

behavioralprofiling is based on real and observed behavior, not on snapshots of declared data, e.g. Likes or Search queries. These personas are the most accurate.

Sleeping Alone Driving

Stress …

Arriving at Home

About to go to Work

…

EVENTS

MOMENTS

Shopaholic

AthletePROFILES Workaholic

Aggressive Driver Unique User

…

…

“Best about an hour after I’ve arrived home from work, so I have had time to eat. Not the days I am picking up

the kids. That makes Mondays, Tuesdays and Fridays between 4pm

and 5:30pm. Unless I’m stuck in traffic on the E313.“

semantic time activity moments

“Morning is when I wake up, whatever time that may be.

Afternoon is when I have eaten something and wander out

shopping or whatever. Night is when the kids are in bed and I

have a horror movie on.”

MORNING ROUTINE

LUNCH TIME

EVENING ROUTINE

NIGHT TIME

SLEEPING

SHOPPING

NIGHT OUT

COMMUTE

WORKING LATE

SPORTS

BIKING

WAITING CITY TRIP

DOG WALK

AT SCHOOL

…

INTERACT / TARGET at the right time

what does this mean in a healthcare context Today?

Become a better coach

Patient Activity monitoring

Patient recovery coaching

Track Activity levels

- walking, biking, moving, …

- detect and monitor patterns

Loyalty to therapy

Alerts – short term deviations

Review – set targets

Fall / Accident detection

Outside activities

Events this month: 10

Physical activity level: LOW

Morning routine: Early Bird

senior citizen, retired

at home, lunch time

alone, inactive

improve patient insights

Improve patient insights

Track patients time line

• Interacting with Patients on Semantic time

• Morning, Lunch, Evening Routines• Medication Alerts, Feedback reminders,

Measurement triggers

• Correlate findings to Profiles?

• Elderly monitoring

• Activity levels, places visited, pattern changes• Driving behavior

1 line

of code is required to integrate our mobile SDK and start building intelligent and personalized user experiences!

1 day

on a single battery chargemeans your mobile userswon’t experience anyinconvenience!

EASY integration of our Software Development Kit into your mobile app

Layer 1

Layer 2

Layer 3

aggressive driver

…

…waking

up

…

pet owner

sleeping

walking running

car subwaytrain

on the bus

boat

sitting standing

airplane*

biking

arriving at home, work, the gym, ...

shopping

lunchinactive

noisy environment*

in a meeting

horse*

home

working

in company*

full-time worker

workaholic

urban

watching tv

motorcycle

agitated*

suddenly stopped

tram

climbing*

*subject to sensor availability/capability and/or user permissions

Thankyou.

© 2015 – info@sentiance .com

profiling

map/reduce sensor and context data

CRM

DMP

context store AP

I

MOBILE APP

insights

analytics

performance

reporting

dashboard

real-time layer

compute layer

training layer

campaign execution

• Ads• segmentation

• push notification• email• SMS• voice

• CRM updates

profile model store

external campaign

context model store

raw data(sensors, events)

profile store

SDK

in app action

moment & context

detection

self service campaign

suite

real time layer

WHAT goes on in the back-end

SENTIANCE CLIENT

Smart city, driver profiling & fleet management

in partnership with Ghent University

USE CASE I

8PM Today

PROFILE recommends transport mode based onbehavior, moment & environment to make the city smarter

WORKAHOLICPROFILE SEGMENT

TAILGATERPROFILE SEGMENT

CITY WORKERPROFILE SEGMENT

DRIVING

LEFT WORK

ON HIS WAY HOME

RECOMMENDED

TRANSPORT

TRAIN + E-BIKE

Predict the best moment to offer a limited promotion offer

USE CASE II

8PM Today

Personal offer: Book now two

tickets and receive € 5 discount

AVOID pushing the (right) message at the wrong time

WORKAHOLICPROFILE SEGMENT

WEEKEND MOVIE LOVERPROFILE SEGMENT

NIGHT OWLPROFILE SEGMENT

SITTING

LEFT WORK

ON HIS FRIDAY LUNCH BREAK

Optimize traditional advertising to achieve better ROI

USE CASE III

DETERMINE where & when your target audience is receptive to your traditional media

Make the most of your travel experience

No waiting linePriority boarding

Earn flight rewardsVisit m.klm.com

WORKAHOLICPROFILE SEGMENT

CITY PERSONPROFILE SEGMENT

FREQUENT AIR TRAVELERPROFILE SEGMENT

COMMUTING

STANDING

ON HER WAY TO WORK

Thankyou.

© 2015 – info@sentiance .com