Amplify 2017 Session CSE-1728

Providing a Real-Time, Personalized, In-Store Shopping Experience with IBM Watson

Maria N. Schwenger, IBMschwenge@us.ibm.comSunil Mishra, IBMsunilmis@us.ibm.com

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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1. Why Personalization?

a) New ways of engagement

b) New consumer expectations

c) New way of interactions

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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 withmachines differently

Consistency expectedacross 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

social media or in their circles?

Who are the influencers in this network?

Sentiment Analysis

SocialAnalytics

Influencer Analysis

Where are people

discussing my product?

Geo/weather Analysis

WHY?

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-digidex terous/

Example: Digidexterous stores of the future

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A New Point of View in Personalization - Cognitive Computing

360 Degree Purchase Decision Existing analytics information:Demographics: 34 yr old, college educated, busy, working professionalContext: Economically stable, candidate for home, financial servicesLife event: Recently marriedExpressed needs: wants to buy a car.

New (personality derived) informationPersonality Traits: Agreeable, achievement striving, open to experiences, conscientious, Inherent Values: values self-enhancementInherent Needs: practicality, structureEmotions: Mostly Cheerful, Satisfied

Anna

Anna might preferClothing Preferences: Comfortable, business casual and outdoor travel clothing.Food Preferences: Organic dairy and produce, boxed cerealsCoupons: Moderate on coupon redemptionInvestments: Moderately risky investmentsHealth Care preferences: Yoga

Car Preferences: Reliable, safe, and moderately priced car with low emissions

2. Challenges of today’s In-store Shopping Experience

(Dealership example)

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Dealership Challenges Todays

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Screenshot

Customers would rather ……. than go to a

dealership

Customers search online about 14 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

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

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 you with 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

Customer Desires During the Car Buying Experience

Source: BCG Survey n ≈ 2,200, February 2013

% R

espo

nden

ts

4341

34 34 32

28 28 2625

23

15 15 14 14 1310

7

0

5

10

15

20

25

30

35

40

45

50

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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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 datapoint, interactionand 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

IBM built the most complete and integrated platform for innovation

16

Crawl - Private, public and licensed data

Conversation Applications

Computation Cognitive / AI

ContentData

CloudPaaS / IaaS

Watson Oncology

API

GBS and GTS industrysolution 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 RecognitionAP I

DiscoveryAP I

SpeechAP I

Compare & ComplyAP I

Document ConversionAP I

DLaaSAP I

Nat Language UnderstandingAP I

ToneAnalyzerAP I

Nat Language ClassifierAP I

PersonalInsightAP I

Knowledge QueryAP 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)

Objectstorage DNS Virtual machines

(CPU/GPU/power) Networking File storage

Secu

rity

and

com

plia

nce

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 natural language.

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)Threeoptionsforcreativemarketingcampaign

NeedsPersonality

Values

Network

Time

Multi-DimensionalCustomerInsight

Verymotivatedforselfenhancement

Efficient, organized,andconservative.Excitementand

desiresself-expression

Networkmakeup forreceivingsimilaroffers

Timingformakingcontact

Contentdeterminedby intrinsicpreferences:“dressforsuccess”(selfenhancement)“high-quality”(ideals)- “10%offwhenbringyour friends(socialties)”-

Personalityderived

X X

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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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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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

System Architecture - Kiosk

Shopper MatchAnalytics ProcessingContent Management

Personality Insights Live Customer Dashboard

InternetGateway

Match Kiosk witheyeQ software

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Study Consumers by vehicle type

FordMatch – Personality Character Analysis

Study Consumers by vehicle model

FordMatch – Shopper Traffic Analysis

6.12 minutes

Average additional time shopper spends in dealership if

FordMatch is used

1.67minutes

Average time highly engaged shopper spends

at FordMatch

FordMatch – Interactive Display Analytics

In-Dealer Engaged Highly Engaged

RequestHelp

PersonalityMatch

Payoff

147,403 2,994 696 461 179

-- 2% 23% 66% 38%

Customer Satisfaction

4.5

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 BMWAudiMB

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/

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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• 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 futureHow next-gen

computing changes the way we live and

work

Please Note: IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal without notice at IBM’s sole discretion.

Information regarding potential future products is intended to outline our general product direction and it should not be relied on in making a purchasing decision.

The information mentioned regarding potential future products is not a commitment, promise, or legal obligation to deliver any material, code or functionality. Information about potential future products may not be incorporated into any contract.

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Notices and Disclaimers

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Information in these presentations (including information relating to products that have not yet been announced by IBM) has been reviewed for accuracy as of the date of initial publication and could include unintentional technical or typographical errors. IBM shall have no responsibility to update this information. THIS DOCUMENT IS DISTRIBUTED "AS IS" WITHOUT ANY WARRANTY, EITHER EXPRESS OR IMPLIED. IN NO EVENT SHALL IBM BE LIABLE FOR ANY DAMAGE ARISING FROM THE USE OF THIS INFORMATION, INCLUDING BUT NOT LIMITED TO, LOSS OF DATA, BUSINESS INTERRUPTION, LOSS OF PROFIT OR LOSS OF OPPORTUNITY. IBM products and services are warranted according to the terms and conditions of the agreements under which they are provided.

Any statements regarding IBM's future direction, intent or product plans are subject to change or withdrawal without notice.

Performance data contained herein was generally obtained in a controlled, isolated environments. Customer examples are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual performance, cost, savings or other results in other operating environments may vary.

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Workshops, sessions and associated materials may have been prepared by independent session speakers, and do not necessarily reflect the views of IBM. All materials and discussions are provided for informational purposes only, and are neither intended to, nor shall constitute legal or other guidance or advice to any individual participant or their specific situation. Amplify 201732

Notices and Disclaimers Con’t.

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facebook.com/ibmwatson

@ibmwatson

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System Architecture (details)

FPO#watsoncommerce#watsonmarketing

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