Rtp webinar-fujitsu-cisco-08-9-2016-final deck-opt (1)

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Panelists
MODERATOR:
Debbie Hauss
Editor-in-Chief, Retail TouchPoints
Ashees Sinha
Practice Architect, Digital Transformation
Cisco Systems
ashees@cisco.com
Joe Hnilo
Vice President, Software Business
Fujitsu America, Inc.
joe.hnilo@us.fujitsu.com

Ashees Sinha
Practice Architect,
Cisco Systems
August 9, 2016
Digitization of Customer
Experience
through
Cisco Connected Mobile Experiences
(CMX)

6© 2016 Cisco and/or its affiliates. All rights reserved.
A Mobile World
1
Cisco®
Visual Networking Index (VNI) Report
Mobile Devices Increase to
Over 10 billion by 20181
Organizations Looking to
Monetize Wi-Fi
Wi-Fi as a Platform to
Deliver Services

What if You Could…?
§ Send location and
dwell-time
notifications?
§ Offer personalized
promotions?
§ Access customer
analytics?
§ Show maps with
featured attractions?
§ Deliver personalized
third-party
advertising?
§ List nearby
amenities?
§ Reduce wait times,
improve traffic flow?
§ Provide gate
directions?
§ Deliver third-party
advertising ?
§ Offer way-finding
patient apps?
§ Simplify
onboarding?
§ List nearby
services?
§ Improve safety and
security?
§ Provide intuitive
campus maps?
§ Enhance tours and
stadium
experiences?
Retail EducationHealthcareTravelHospitality
Consumers StudentsPatientsPassengersGuests

90%
Of shoppers use their
phones while in store**
96%
of shoppers prefer to shop in
locations with free Wi-Fi*
71%
Of shoppers say their device has
become more important in their
instore experience
Shoppers Rely on Mobile Devices While Shopping
“Shoppers want to stay connected while
they’re here, which makes mobile access
the key.”

What it Brings to Your Business
Customer Engagement and Insights
25% of Customers Buy on
Their Mobile Device While in Store
Lift in conversion
Extends digital investments into the store
New source of shopping insights
Test store layouts and fixtures with more precision
Cater to preferences of various demographics
Increase effectiveness of associates
Increase customer loyalty
“Knowing our customers is key to being able
to engage and inspire them...Understanding
their behaviour in the store is key to our
multichannel leadership strategy.”

Companies that make
extensive use of customer
analytics
• 126% profit improvement
• 23X more likely to outperform
competitors in new customer
acquisitions
• 21X more likely to migrate
customers to profitable
segments
Customer Insight drives Customer Experience
86% of Consumers Will Pay More
For a Better Customer Experience
CashierCashier
Dressing Rooms
Jewelry
Junior's
FormalWearShoes
EmployeeOnly
Men's Boy’s Girl’s
Women's
Suites
Belts
Cosmetics
Sleepwear
Swim Wear
BeddingKitchenSeasonal
Low Traffic
Low Product
Demand
Overcrowding
No Shoppers,
change
display?
Shoppers not
reaching interior
High Traffic,
Need more
Associates

Capabilities: Traffic Quantification
Hyper
Awareness
Informed
Decision
Making
▪ Understand shopper behaviors
▪ Connecting silo’d customer data
sources
▪ Insight into who did and did not
make a purchase during visit
▪ Identify highest value customers
Business Challenge
▪ Traffic Quantification
▪ Tailored Brand-Specific Guest Wi-Fi Experiences
▪ Comprehensive Conversion Capture
▪ Labor Optimization
▪ Loss Prevention
Business Capability Enabled
▪ Greater understanding of
shoppers desires and needs
▪ Deliver differentiated and relevant
engagements
▪ Provide relevant and world class
experiences each visit
▪ Personalized attention for high
value customers
Business Outcome
Fast
Execution

Use Case: Way Finder
▪ Create more compelling
shopping experiences
▪ Differentiate between regular
shoppers and loyal/preferred
▪ Deliver relevant ads based on
known customer preferences
▪ Avoid lines for check-out
Business Challenge
▪ Enable customers to navigate within the mall
▪ Integrate location and big data analytics
▪ Drive loyalty with location-based capabilities
▪ Insert targeted ads onto guest’s mobile app
▪ Convert regular shoppers to
preferred loyal shoppers
▪ increase revenue with relevant
promotions
Business Outcome

Use Case: Location Based
Pushed Notifications
Connect Welcome Promotion Analytics
▪ Understand shopper needs
and likes
▪ Reward loyal shoppers without
overwhelming them
▪ Deliver real time promotions
▪ Stock stores to customer
preferences
Business Challenge
▪ Deliver personalized in-store shopping experiences
▪ Provide relevant information that helps make the
purchase decision
▪ Insert targeted ads onto retail app (where the shopper
is using one)
▪ Increase revenue through
real-time deal notifications and
brand promotions
▪ Adapt to drive customer loyalty
▪ Build strong customer
relationships with differentiated,
valuable engagement
Business Outcome

Enhancing the Customer Experience
Through Analytics
Phase 1: Wi-Fi Only Phase 2: Wi-Fi, POS Phase 3: Wi-Fi, POS, CRM, Social
Presence
Detection
Aisle
Traffic Flow
Department
Traffic FlowPresence
Detection
Fixture
Dwell Time
Department
Dwell Time
Dept Path
Analysis
Associated
Device Traffic
Associate
Engagement
Queue
Management
Customer
Demographics
Social
Engagement
Store Layout
Heat Maps
Zone Analysis
Loss Prevention
Dwell Conversion
Department
Conversion
OmniChannel
Experience
Customer LoyaltyShowrooming
Customer Intimacy/Personalization
BusinessImpact
HIGH
LOW
Detailed Traffic
Conversion
E-commerce

31 © 2015 FUJITSU
Connect. Challenge. Inspire.
FUJITSU
Retail Solution
Engagement
Analytics
Joe Hnilo
VP, Software Business
Fujitsu America
August 9, 2016

32 © 2015 FUJITSU
Fujitsu in Retail – at a glance
Revenue
$1.6b
Solutions
Retail R&D/Innovation
>$20m
Years
50
Global Retail Strategic
Team Partnerships
8,000
Countries
53
Analytics
Omni-channel Self Service
ICT Services
Customers
>500
Copyright Fujitsu 2016

33 © 2015 FUJITSU
Who we work with
EMEA Japan & Asia Americas
Oceania

34 © 2015 FUJITSU
Retail Engagement Analytics
Transforming Retail Operations and Shopping Experience in the Store

35 © 2015 FUJITSU
Online shopping analytics is
very mature…

36 © 2015 FUJITSU
…in-store analytics is far
behind

37 © 2015 FUJITSU
Stores account for
90% of transactions.

38 © 2015 FUJITSU
Fujitsu Retail Engagement Analytics
q Fujitsu Retail Engagement Analytics provides retailers with an
effective solution for understanding and analyzing shopper behavior
while they are present in the store:
§ Collect and aggregate live customer location data
§ Combine location data with sales data to provide actionable
insights
§ In-store traffic monitoring and alerting for better store
operations
§ Patented Automated Flow Discovery to visualize traffic flows
§ Visualized analytics insights - dashboard/heat maps/flow
maps
§ Secure cloud hosting with global reach
§ Strategic partnership with Cisco

39 © 2015 FUJITSU
Core Benefits for Retailers
We can track key customer behavior in the store…
Number of people by store & zones
Peak time in store/zone
New compared to repeat visitors
Common traffic patterns
Where people spend time
So retailers can…
Optimize floor layouts vs hot spots
Optimize # checkouts & location
Understand visit patterns
Manage in-store congestion proactively
Optimize staff allocation and scheduling

40 © 2015 FUJITSU
Turn Analytical Insights Into Action via BPM
Time of day
Threshold
CustomerCount
n Real time monitoring of customer traffic and staff allocation
n Alert store manager and staff to initiate pre-emptive action
Visualization: Location of
Store Staff, customers and
behaviors
Predicted customer
arrival rate
Pre-emptive Alert to Shift Supervisor
Reactive Alert to Store Manager
Actual customer
arrivals
Store Traffic Map
Call out
Stocking Break
Cashier
Supervisor

41 © 2015 FUJITSU
Key Differentiators
q Turn analytics insights into actions with Business Process Management
(BPM) capabilities.
q Capture and correlate live customer location data with the PoS data to
deliver actionable insights.
q Visualize traffic flow for detailed shopper path analysis using Fujitsu
patented Automated Flow Discovery technology.
q Superior processing speed and scale leveraging advanced data processing
technology, which is 500x faster than traditional databases.
q Secure cloud hosting with global reach on Fujitsu’s own secure private
cloud S5, delivered via our global network of data centers.
q Complete, end-to-end solution delivered by Fujitsu

42 © 2015 FUJITSU
Passers-by
5,000
Visitors
2,437
Engaged
2,013
Purchases
564
Sales
$14,091
Traditional Approach
REA - Store Performance Impact
Passers-by
5,000
Visitors
2,437
Engaged
2,037
Purchases
591
Actionable Intelligence with REA
1%
5%
Sales
$14,771
5%

44 © 2015 FUJITSU
Leading Fashion Clothing Retailer
q A multinational retail-clothing company, known for
its fashion clothing for men, women, teenagers and
children
q Fujitsu gathered and analyzed location and sales
data including the period of a store-wide promotion

45 © 2015 FUJITSU
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Repeat Customers
New Customer
Customer Visits - New vs. Repeat
Key Finding Potential Action
Loyal customers consist nearly half of the total traffic Loyalty program to reward repeat customers
Traffic drops significantly on March 19-20 Examine the cause of traffic drop
* This data is representative data

46 © 2015 FUJITSU
Customer Traffic by Department by Week
0
5000
10000
15000
20000
25000
Shoes Ladies Home Kids Cosmetics
Week1
Week2
Week3
Week4
Traffic to cosmetic department almost doubled during week 4 Examine and analyse the promotion effectiveness during
week 4 at cosmetics department

47 © 2015 FUJITSU
Sales Conversion/Dwell Time by Zone
Men’s department has the low dwell time but high conversion rate
Ladies department has the long dwell time but low conversion rate
Examine the reason behind this and design corresponding
strategy to boost the conversion rate at Ladies department
Short dwell time &
high conversion rate
Problem Focus:
Long dwell time
& low conversion
rate

48 © 2015 FUJITSU
Traffic Density Across the Store
“Hot spots” across the store layout Allocate more staff resources to the right spot at right time

49 © 2015 FUJITSU
Key Findings
q Identified most prominent routes taken by customers
§ Majority Visitors to one dept.- Floor plan optimization
§ Signage to encourage department visits
q Quantified the effectiveness of promotions
§ Marketing effectiveness
q Developed actionable intelligence for departments where conversion
rate was low
q Identified relationship between staff allocation and conversion
§ Staffing Optimization
q Identified most effective time periods to run promotions

#AnalyticsInStore
Q&A | Panelists
MODERATOR:
Debbie Hauss
Editor-in-Chief, Retail TouchPoints
Ashees Sinha
Practice Architect, Digital Transformation
Cisco Systems
ashees@cisco.com
Joe Hnilo
Vice President, Software Business
Fujitsu America, Inc.
joe.hnilo@us.fujitsu.com

#AnalyticsInStore
Thank You For Joining Us
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Rtp webinar-fujitsu-cisco-08-9-2016-final deck-opt (1)

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Rtp webinar-fujitsu-cisco-08-9-2016-final deck-opt (1)