Saurabh Jains Entry for Summer Internship Contest

1. CONCEPTUALIZING A
RETAIL SOLUTION ON
COMPETITIVE
PRICING
Saurabh Jain
Goa Institute Of
Management
SUMMER INTERNSHIP
PROJECT

2. PURPOSE
To design a prototype for a solution in the retail domain that can act as
a model for clients in pricing their own products to gain competitive
advantage in the world of dynamic pricing.
Snapshots of Retail Industry:
• Fifth largest sector in the world, is one of the sunrise sectors with huge
growth potential
• Expected to grow 17% globally with the emergence of the new
economies and opening up of the markets
• In 2013 the grocery market in six Central European countries was worth
nearly €150bn
• Growth in emerging markets like China, India, Brazil is expected around
20-25%

3. WHY COMPETITIVE PRICING?
• Some of our key Secondary Research insights
*KPMG-Retail Outlook 2013
We find that Pricing is Central to
Most of The Answers given by the
Top Management of Retail
Companies

4. REPRESENTATION OF INFORMATION FLOW
Generates POS
Transactional Information.
Data collection &
Aggregation
INTELLO- PRICE
Client
Store Competitor
Store

5. PRICING ANAYTICS
Sales
Volume
Promotions
& Discounts
Price
Points of
Products
Sentiment
Analysis
of social
media
Demogra
phic
details of
consumer
s
Aggregate
Demand,
Supply
GDP
per capita
Margins
MSRP
Price
difference
Discounts
offered

6. MAJOR OFFERINGS FROM COMPETITORS
& BUSINESS BENEFITS
COMPETITORS
Product
Based
Competitor
s
Oracle SAP
Direct
Competitor
s
TCS
Competitiv
e Pricing
Macro
Space
Utilization
Infosys
Pricing
Analytics
Cognizant
Pricing
Optimizatio
n
Procureme
nt and
Spend
Analytics
Other
Competitor
s
Latent
View
Analytics
Pricing
and Mark
Down
Optimizati
on
The Smart
Cube
Pricing
Analytics
Boomeran
g
Commerce
Competitiv
e Price
Optimizati
on
• Niche players like Boomerang Commerce have
rolled out its solution for $ 1 Million
• Direct Competitors like TCS, Infosys have started
rolling out solutions to its retail clients to capture
the need in the market.
• Wipro can leverage upon its previous statistical
models of Trade Promotion Optimization(TPO) and
Market Mix Modeling(MMM) to develop this
solution.

7. KEY LEARNINGS
Dynamics Of
Retail
Industry
Solution
Design
Pricing
Analytics
Key Features
Design
Screen
Visualization
Target End User
Scope &
Assumptions
TPO Model
Marketing Mix
Model
Pricing Manager
Competitor
Offering
Data
Representation
Key KPI’s
In House Product
Development
Marketing Strategy