Internet of Everything: Retail’s Future

Cisco Public© 2012 Cisco and/or its affiliates. All rights reserved. 1
Internet of Everything
Retail’s Future
Cisco Consulting Services
October 2013

© 2012 Cisco and/or its affiliates. All rights reserved. Cisco Public 2
Does your Loyalty Program differentiate the
brand? Your CRM application?
Commodity.
Loyalty Programs.
Enterprise Applications.
Differentiator.
Data.
Captured. Analyzed.
Turned Into Action.
The New Competitive Frontier

Delivering the right
information to the
right person (or
machine) at the
right time
Process
Connecting people
in more relevant,
valuable ways
People
Leveraging data
into more useful
information for
decision making
Performance
Physical devices
and objects
connected to the
Internet and each
other for intelligent
decision making
Products

Machine-to-Machine (M2M)
21%
Share of Value at Stake
Machine-to-People (M2P)
48%
People-to-People (P2P)
31%
Inventory
Visibility
Flexible
Payment Options
Automated
Ordering Process
Energy Optimization
Understand Shopper
Behavior
Personal-SoLoMo
Content
Endless Aisle
Omni-Channel
On-Demand Expert Advice Collaborative Product
Development
On-Demand Training
Source: Cisco Consulting Primary Research, 2013

Cisco Public 5© 2012 Cisco and/or its affiliates. All rights reserved.
Creating Retail Value from IoE:
5Opportunities
1
2
3
4
5
Light Up and Connect Dark Assets
Connect and Build Customer Trust
Gain More Visibility into Inventory
Drive Higher Levels of Stock Availability
Maximize Staff Productivity

POS CREDIT
MOBILE RFIDVIDEO SENSORS
SOCIAL EMPLOYEEMEDIA
STRUCTURED UNSTRUCTURED
WEATHER
Data is Fuel. Think Quantity and Quality.
SOURCES
TYPE
CRM LOYALTY
1

Customer Data:
Identification
Transaction History
Cohort Data:
Aggregate ID
Transaction History
Loyalty Data:
Identification
Interests-Uses
Transaction Data:
Identification
Interests-Uses
SINGLEVIEWCONSUMER
Availability Data:
Identification
Interests-Uses
SINGLEVIEW
INVENTORY
weathersociallocation time trend behavior
P R E V I O U S “ D A R K “ A S S E T S
mobile-WiFivideo
Etc.
SKU conditioninternet staff
1
2

Real-time pairing of
shopper’s exact location
via mobile device with
Weather Channel report =
push ad for best type of
Pantene product
Source: Wall Street Journal, August 2013; New York Times, July 2013; Frontline Insights, September 2013
Real-time pairing of
In-store shopper flow (via
video) with frequent
shopper data (via mobile
device)=
Quantity and quality of
traffic
2011: Real-time pairing of
employee feedback
textual analysis with POS,
promotion and marketing
ROI data =
Highly accurate leading
indicator of performance
2 2 5 2

MGM Resorts uses wireless to create
immersive, personal experiences using
service, advice, recommendations, prom
otions, and pricing.
Guests use app via Wi-Fi
get directions to
locations, receive
discounts,
MGM developed processes
to coordinate location-
based/personal offers
Data about customer
location used to present
relevant info. through app
Seamless, secure Wi-Fi in
MGM properties powers app
on guests’ devices
Machine People
2

Smart retail operations, proactively
anticipate: 1) checkout traffic to dynamically
staff front-end resources, reducing customer
wait times / increasing associate productivity;
2) potential out-of-stocks to dynamically adjust
labor to increase on-shelf availability
Video sensors help store
managers optimize
checkout and restocking
Early out-of-stock
assessment helps automate
logistics and replenishment
Predictive video analytics
assess in-coming foot traffic
impact on checkout volume
Smartphones, cart sensors
help track customers’
journey through the aisle
Machine People
• Shelf
Sensors -
Inventory
• Video-
Demographics;
Shopping Units
• Video-shelf
Inventory
• Wi-Fi – shopper
traffic
Sensor
fusion
Operational
Systems
FastDataEngine
Alerts,
Dashboards,
Automatic
processes
4 5

Tap QR code to get jeans delivered to dressing
room in 30 seconds through chute via a robotic
arm; card on record auto charged
Customer uses mobile to
engage with merchandise,
try on and purchase
Automated product delivery
& return from changing
room. Automated payment.
RFID links products and
customers. Mobile linked to
encrypted database
Mobile device and recorded
details act as customer
identifier.
People Machine
2 3
4 5

Value at Stake 2013
(Jan. – Dec.)
$1.2T
Value
realized
in 2013
IoE Value Index
$613B
(53%)
$544B
(47%)
Value
“left on table”
in 2013
Global Value at Stake
2013-2022
(10-year total)
$14.4T*
2013
$1.2T
Note: chart is not to scale
* $14.4T is conservative because it is based on a set number (21) of private-sector use cases and discounts future cash
flows due to uncertainty around privacy and regulatory issues.

55.1%
Opportunity
44.9%
Value Realized
N=7,501
N=7,501 respondents
onScaleof 1 to 10,
Retail ITexec. rate theirabilityto capture valuefrom IoE
*10-point scale: 1 = extremely weak ability;
10 = extremely strong ability
Confidence Level
to Capture IoE Value
$99B
$81B

44.9%
45.8%
46.0%
50.7%
50.8%
54.2%
57.4%
60.5%
65.4%
55.1%
54.2%
54.0%
49.3%
49.2%
45.8%
42.6%
39.5%
34.6%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Retail /
Wholesale /…
Energy
Manufacturing
Transportation
Other
Healthcare / Life
sciences
Services
Financial
services
High tech /
Telecoms
IoE value realized IoE opportunity
$118B
N=7,501
Value at Stake
2013 ($B)
$118.3
$115.2
$276.9
$98.7
$65.4
$23.6
$224.4
$55.0
$179.6$99B
$121B

Internet of Everything: Retail’s Future

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