The document discusses how semantic technologies can benefit retailers. Semantic tools can map raw data to systems to provide speedy, high-quality information for business agility. They allow applications to react intelligently to new information from an exponentially increasing amount of available data. The required technologies and standards are already in place. Semantic approaches examine relationships between concepts and facts to power personalized recommendations and decisions.

1. Profi%ng
from
Seman%c
Web
in
Retail
The
new
tool
of
successful
prac%%oners
in
Customer
Experience
and
Opera%ons
Suresh
Nair
(MphasiS)
&
Gam
Dias
(First
Retail)

3. Why
Seman%c?
• Speed
&
quality
of
informa%on
=
business
agility
• Exponen%al
increase
in
available
raw
data
• Seman&c
technologies
map
raw
data
to
your
systems
• Smart
applica%ons
react
to
new
informa%on
• The
technologies
and
data
standards
are
already
available

8. Application Screen from WATCHITOO

9. Application Screen from TOBI

10. Just browsing: vs. shopping:
I want the dress that Daisy is
wearing, and the song in the
background
Let
me
learn
more
about
the
movie
OK. The
cheapest I can
Search
across
get both is $130
merchant
sites
Great,
go
for
it!
Find
the
soundtrack
Done. The song’s on
your MP3 player. The
dress will get here on
Tuesday

11. Internet Studio Details
Customer’s IMDB Movie
Application Database
Character
Dress size Movie Site
Data about the Merchant tie in
Location
customer
Card #
Ratings and Purchases
Movie
Reviews
Context Dress Reviews
Character
Item code Merchant Product code
Deeper Data Price
Soundtrack # Network
Social Graph Likes
Posts

12. What
Cooking
Range?
Research
Things I know…
Key Decisions New Facts
Induction range
WILL IT MEET OUR NEEDS?
CAN WE AFFORD IT?
WILL IT MATCH THE DÉCOR?
HOW WILL WE PAY FOR IT?
Shortlist
New Decisions

13. What
Cooking
Range
What
COOKING
should
I
buy?
RANGE
should
I
BUY?
Public Sources
What the Application
knows about ME
What’s
your
cooking
style?
What
décor
do
you
have?
Privileged Sources
You
should
buy…

14. Customer Aggregator Public information provider
Application Application
SEMANTIC
EXPOSITION
PRIVACY
PRIVACY
DECISIONS
PROMISE
Privileged data provider
CUSTOMER
TRADITIONAL
DATA
&
CONTEXT
AD’
RATES
Merchant
PREFERENCE
RELATIVE
PRICING & ADVERTISING
DECISIONS
RANKING
PLUS MERCHANDISE
PAYMENT
RECOMMEN-­‐
ACTIONS
ACCEPTED
AD
PRICING
DATIONS
PRICING
CHARTS
DECISION PUBLISHED
BEING MADE FACT

18. Vendor Supply Chain Products
Management
What What
Vendor When Why
Details
Where How
Vendor Selection Process
Quality Price
Product Evolution Process
Timing Segments Features
Delivery In Flight Impact on
Capability Shipments Product Lines Floods in
Thailand
Event Propagation

19. Seman%c
Web
Infrastructure
Inference The Magic
Concepts Facts Query tools Federation
Engine Box
“Get the
income (from Search
“If a person the payroll agents, AI
“Person” / “John was “Get all was born in system) of tools,
“Date of born on Jan persons born
1971, their everyone backward
Birth” 15, 1971” in 1971”
age is 41” over 40 (from chaining
the HR rules engines
system)
Semantic Web Use as input
Exectute
Queries
Queries
Concept Query Inference AI
Engine Engine Engines
Model Queries Get results
Conforms Fact
To
Store
Store these
As new facts
Ontology Meta Data Markup

20. What’s
a
‘Customer’
Sales:
“A customer is
ACME Co
anyone who pays for
Works Was Jan 15, a service or product
for Born On 1971
Party
Company Person Vendor
Service:
ACME John My Gadget “A customer is
Co Smith Shop
anyone who John Smith
transacts (uses) a
service or product
Uses Provided by
Pays for Product
My Cool
Tablet Audit / Risk /
Compliance “A
ACME Co
customer is anyone
John Smith
who uses or pays for
a service or product”
Semantically Modeled Data Tailored Semantic Views

21. Conclusions
• Speed
&
quality
of
informa%on
=
business
agility
• Exponen%al
increase
in
available
raw
data
• Seman%c
technologies
map
raw
data
to
your
systems
• Smart
applica%ons
react
to
new
informa%on
• The
technologies
and
data
standards
are
already
available

22. THANK YOU
Profi%ng
from
Seman%c
Web
in
Retail
Suresh
Nair
(MphasiS)
&
Gam
Dias
(First
Retail)