This document provides an agenda and overview for a presentation on providing a personalized in-store shopping experience using IBM Watson. The presentation covers why personalization is important given changing consumer expectations, challenges with today's in-store shopping experiences, how cognitive personalization can enhance the shopping experience, and a use case demonstrating cognitive personalization in an automotive dealership. It includes demos of IBM Watson cognitive APIs and a "Cognitive Car Recommender" app that provides personalized vehicle recommendations based on a shopper's personality traits.

1. Amplify 2017
Session CSE-1728
Providing a Real-Time,
Personalized, In-Store Shopping
Experience
with IBM Watson
Maria N. Schwenger, IBM
schwenge@us.ibm.com
Sunil Mishra, IBM
sunilmis@us.ibm.com

2. 1. Why Personalization?
2. Challenges of today’s In-store Shopping Experience
3. Cognitive Personalization of Shopping Experience
4. Use Case of Cognitive Personalization in Dealership
5. Experience Personalization – “Cognitive Car Recommender” App
6. Q&A
AGENDA
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3. 1. Why Personalization?
a) New ways of engagement
b) New consumer expectations
c) New way of interactions
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4. Amplify 20174
Addressing changing global
demands and expectations
Transforming Consumer Engagement
Consumers require a new level of
engagement
A “do it yourself”
mentality now prevails
Humans interact with
machines differently
Consistency expected
across an Enterprise
Companies are losing
touch with customers
We expect answers:
§ Quickly
§ Simply
§ On our own
We expect systems to:
§ Know us
§ Engage us
§ Learn & improve over time
We expect seamless
interactions
§ Consistency of service
§ Regardless of channel
Self-service can
distance customers
§ Difficult to build &
deepen relationships

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Understanding
Individuals…
Studies across a wide variety of fields
show that individuals have intrinsic
traits that can be recognized and
used to predict future behavior
[Ford’05, O’Brien ‘96, Neuman ‘99, Gosling ‘03, Wholan ’06]
Surveys exist to measure most traits,
but are often lengthy and rely on self-
reports
Linguistic analysis allows many traits
to be inferred from the written
language of individuals
[Tausczik&Pennebaker ‘10, Yarkoni ’10]
Our work leverages
linguistic analysis to
predict the behaviors of
individuals at scale

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People Analysis is Missing the “Why”
How are
people feeling
about my
brand?
What are people
discussing on
socialmedia or in
their circles?
Who are the
influencers in
this network?
Sentiment
Analysis
Social
Analytics
Influencer
Analysis
Where are
people
discussing my
product?
Geo/weather
Analysis
WHY?

7. Multilevel Digital
Personalization
Example
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Source: https://willgibson19.wordpress.com/2016/11/04/wher e-is-telco-retail-headed-and-what-is-digidexterous/
Example: Digidexterous stores of the future

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A New Point of View in Personalization - Cognitive Computing
360 Degree Purchase DecisionExisting analytics information:
Demographics: 34 yr old, college
educated, busy, working professional
Context: Economically stable,
candidate for home, financial
services
Life event: Recently married
Expressed needs: wants to buy a
car.
New (personality derived)
information
Personality Traits: Agreeable,
achievement striving, open to
experiences, conscientious,
Inherent Values: values self-
enhancement
Inherent Needs: practicality,
structure
Emotions: Mostly Cheerful, Satisfied
Anna
Anna might prefer
Clothing Preferences: Comfortable, business
casualand outdoor travelclothing.
Food Preferences: Organicdairy and
produce, boxed cereals
Coupons: Moderate on coupon redemption
Investments: Moderately riskyinvestments
Health Care preferences: Yoga
Car Preferences: Reliable, safe, and
moderately priced car with low emissions

9. 2. Challenges of today’s
In-store Shopping
Experience
(Dealership example)
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10. Dealership Challenges Todays
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Screenshot
Customers would rather
……. than go to a
dealership
Customers search online
about14 hours before
coming into the dealership;
then when they get there,
they feel like they are
starting over1
The average buyer visits
just 1.6 auto dealerships,
down from an average of
5.2
2 The McKinsey & Company, Innovating Automotive Retail 20141 J.D. Power 2014 New Auto Shopper Study

11. Dealership Challenges Today
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Screenshot
Many customers feel
hassled by commissioned
salespeople trying to push
them into a vehicle
Dealership turnover is high
with declines in new
entrants entering the
profession.
A bad experience with a
sales associate, reflects
poorly on the dealership
and consumers will defect

12. Digital Expectations at Dealership
16
12
18
18
19
20
27
29
29
31
47
0 10 20 30 40 50
None of these
Ability to check in at dealer location via social media (e.g., location check-in via Facebook)
Ability to transfer data from your mobile device (e.g., contact details, previous configurations)
Digital shopping assistant/ avatar helping youwith your questions
Wi-Fi hotspot for your mobile device
Ability to transfer data to your mobile device (e.g., vehicle configuration, price offers)
Tablet for me to use in the showroom to get detailed information, compare vehicles, configure cars, etc.
Cars in showroom have digital info available (e.g., for display on mobile device)
Virtual test drive stations
3D virtual vehicle configurator
Interactive touch screens to view car information with pictures and videos
Source: Capgemini 2015

13. Customer Desires During the Car Buying Experience
Source: BCG Survey n ≈ 2,200, February 2013
%Respondents
43
41
34 34
32
28 28
26
25
23
15 15 14 14
13
10
7
0
5
10
15
20
25
30
35
40
45
50

14. 2. Cognitive Personalization of
Shopping Experience
a) IBM Watson Cognitive APIs
b) IBM Cloud:
– Bluemix Platform
– IBM Bluemix IaaS
c) IBM industry expertise
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15. By applying cognitive capabilities to your data, you will
enhance digital intelligence exponentially.
REASON
They can reason, grasp
underlying concepts,
form hypotheses, and
infer and extract ideas.
UNDERSTAND
Cognitive systems
understand imagery,
language and other
unstructured data
like humans do.
LEARN
With each data
point, interaction
and outcome, they
develop and sharpen
their expertise, so they
never stop learning.
INTERACT
With abilities to see,
talk and hear, cognitive
systems interact with
humans in a natural way.
15

16. IBM built the most complete and integrated
platform for innovation
16
Crawl - Private, public and licensed data
Conversation
Applications
Computation
Cognitive /AI
Content
Data
Cloud
PaaS / IaaS
Watson
Oncology
API
GBS and GTS
industry
solution apps
API
Watson
Cyber-
security
API
Weather
API
Watson
Virtual
Assistant
API
Watson
Explore &
Discover
API
IBM Risk &
Compliance
API
+ Many more
ConversationAP
I
Visual
Recognition
AP
I
Discovery
AP
I
Speech
AP
I
Compare &
Comply
AP
I
Document
Conversion
AP
I
DLaaS
AP
I
Nat Language
Understanding
AP
I
Tone
Analyzer
AP
I
Nat Language
Classifier
AP
I
Personal
Insight
AP
I
Knowledge
Query
AP
I
Cleanse - Data preparation Enrich - w/Ontology and rules + machine learning Store – Knowledge graph: customer and public
Developer services – IAM, billing, logging, monitoring, etc.
Firewall and
reverse proxy
Dedicated machines
(CPU/GPU/power)
Object
storage
DNS Virtual machines
(CPU/GPU/power)
Networking File
storage
Securityandcompliance

17. 17
Retailers reimagines in-
store engagement
Kone gets major lift from
cognitive, data, and analytics
Woodside gives one engineer
the insights of 1,000
Innovators are creating engaging cognitive apps today,
transforming essential experiences
First of a kind mobile shopping
companion learns and interacts in
naturallanguage.
Cognitive elevators interact with
maintenance staff to help improve
safety and quality.
Analyzing data from 80k sensors, 1
million docs, and 30 years of lessons
learned.

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Making Hyper-Personalized Offers (NRF 2014)
Three options for creative marketing campaign
Needs
Personality
Values
Network
Time
Multi-Dimensional Customer Insight
Very motivated for
self enhancement
Efficient, organized,
and conservative.Excitement and
desires self-expression
Network makeup for
receiving similar offers
Timing for making
contact
Content determined by intrinsic preferences: “dress
for success” (self enhancement) “high-quality” (ideals)
- “10% off when bring your friends (social ties)” -
Personality derived
X X

19. 4. Use Case of Cognitive
Personalization in Dealership
a) Augmenting In-store
Experience
b) Introducing Personalized
Content
c) Better understanding of
your clients
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20. eyeQ Kiosk Personalization
- Early start in 2014/2015
- Watson Personality Insights
is used to customized the
presentation layer of in-store
kiosks and improve client
experience and engagement
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Video is available at: https://www.youtube.com/watch?v=ghwh2ewcj6M

21. Extending the Experiment Scope to Dealership
Match Display
Can be placed in the showroom or
service waiting area
Vehicle Display
Outside Display Unit
Unit will assist after-hours
lot shoppers
On-Demand Assistance4

22. System Architecture - Kiosk
Shopper Match
Analytics Processing
Content Management
Personality Insights
Live Customer Dashboard
Internet
Gateway
Match Kiosk with
eyeQ software

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Study Consumers by vehicle type
FordMatch – Personality Character Analysis
Study Consumers by vehicle model

24. FordMatch – Shopper Traffic Analysis
6.12
minutes
Average additional time
shopper spends in dealership if
FordMatch is used
1.67
minutes
Average time highly
engaged shopper spends
at FordMatch

25. FordMatch – Interactive Display Analytics
In-Dealer Engaged Highly
Engaged
Request
Help
Personality
Match
Payoff
147,403 2,994 696 461 179
-- 2% 23% 66% 38%
Customer
Satisfaction
4.5

26. 5. Try Cognitive Car
Recommender App
a) Cars’ “personalities”
b) Live demo
c) Experience yourself!
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Map the Audience’s Input to Our Analysis
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
BMW
Audi
MB
BMW:
dynamic,aggressive,
fast, sporty, adrenaline,
aggressive drivers,
status, younger (at least
feels this way)
AUDI:
Standard,sportive,
serious,modern, creative,
reasonable,latest
technology,younger
families,near to Porsche
Mercedes Benz:
Quality, calm,
conservative,silver
age, safety,
settled/established

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http://watsoncognitivesales.mybluemix.net/WatsonCognitiveSales/

29. 5. Q&A
a) IBM Point of View on
Cognitive
b) Share your experience with
the Cognitive recommender
c) Sessions Q&A
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30. • This is a question many
leaders across industries
have been trying to
answer
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Contact your IBM representative today!
Where Do We Start with Cognitive?
• Cognitive computing is
fundamentally changing
how individuals perform
their jobs, engage, and
interact with others, learn
and make decisions
Your cognitive future
How next-gen
computing changes
the way we live and
work

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35. System Architecture (details)

36. FPO
#watsoncommerce
#watsonmarketing
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