The client is a leading supermarket chain in India with hundreds of stores. They wanted to optimize their marketing strategies to increase sales and customer experience. Global IT Solutions analyzed customer data from stores using various techniques like predictive modeling. This helped reduce marketing costs by 27.25% and increase monthly sales by 14%. Regular feedback allowed tracking of customer sentiments and satisfaction levels. The solution provided customized and real-time insights to outlet managers.

1. Global IT Solutions
An ISO 9001:2015 & ISO/IEC 27001:2013
The client is India’s leading super market with over hundreds of stores throughout the country.
Business Problem
Over the past few years, the client has launched numerous retail outlets and implemented some inflated
marketing strategies to increase sales and revenue. The client wanted to analyse whether the said strate-
gies have resulted in expected outcomes and also planned to optimise the marketing strategies.
About The Client
Evaluating Customer Lifetime Value and
Optimising Target Marketing using
Retail Analytics

2. Key Challenges
To obtain end customer data from different retail stores. The stores are based on franchise model
with varied data capturing patterns
Creating large number of assumptions/hypotheses and validating those assumptions through data
was cumbersome as sometimes enough data was not available to validate or deny those hypotheses
/assumptions
Understanding various kinds of client constraints (both economical and non-economical) and
creating a solution around those constraints was tough
In the past, client captured little information about the customer most of it being transactional
information. Although now the client has initiated loyalty cards for customers, through which more
information about customers buying behavior is available. Combining the different types of data
was another challenge
We discussed with the client the business problem to be resolved. The client wanted us to optimize
target marketing, figure out ways to increase sales and improve overall customer experience. For
each of these requirements we defined separate specific, measurable and action oriented relevant
business problems
Solution Approach & Methodology
Identify Business Problem
Create Problem Statement Worksheet
We had multiple discussions with the client to figure out major components to create our target
Problem Statement Worksheet with following structure:
Basic Questions to be Resolved
The questions should be based on SMART Principle
1. Background
a. What is the current situation?
b. What has happened so far?
c. Why the problem is being addressed now?
a. What are the potential barriers to the study?
b. What are the infeasible solutions for the
situation?
4. Constraints
The following steps were followed in developing the solution:
1
2

3. 2. Desired Outcome
a. What will be the impact on business?
b. What will be the components of final solution?
c. What will be delivered in the end?
a. What are the hypotheses?
b. What all to be included in the final solution?
3. Scope
a. Who all are decision makers?
5. Stakeholders
a. What are the information sources?
6. Resources
b. Who all are the major stakeholders?
b. What technology will be used?
c. What is the required team size?
Create Solution Tree
We confronted the problem and tried to figure out all the possible causes of the same. Next, we
defined all the potential solutions and strategies to solve the problem. A problem can have multiple
solutions. So for each type of solution we followed a separate but similar process. In this step, we
also utilized the end-customer centric the data acquired from the client. For retail analytics we used
different data types be it transaction data, product data, customer behavior data, store sales data
and company’s internal data
Next we clean, transform and pre-process the acquired data. Then we created assumptions and
hypotheses for all possible scenarios. This was followed by descriptive, predictive and prescriptive
analytics which included Exploratory Data Analysis, Machine Learning and Time Series
Forecasting
Analysis Pyramid
Extract Findings
Once all the analysis is done, we consolidated the results, analyzed their feasibility and implemen-
tation and designed actionable solutions through use of BI
We combined and integrated all the results together and presented them to the client as a
single broad solution. The team mentioned the potential problems, causes and solutions; and
helped the client implement the recommendations
Design the Deliverable Solution
We provide regular analytics support to client for implementing the solution and its architecture
and regularly optimize the machine learning algorithms as more data becomes available
Provide Support
3
4
5
6
7

4. Identify The
Business Problem
Analysis
Pyramid
1
Create Solution
Tree 1
Create Solution
Tree 2
Build Compact
Solution
Create Solution
Tree 3
Create Solution
Tree N
Design The Problem
Statement Worksheet
Demonstrate
Solution to Client
Extract Relevant
Findings
Extract Relevant
Findings
Extract Relevant
Findings
Extract Relevant
Findings
Implement Solution At Client
Site And Track Results
Key Highlights of the Approach
The analysis approach undertaken helped us uncover other hidden aspects of customer
behavior having an indirect impact on the client’s revenue
Comprehending store specific insights allowed us to create solutions highly specific to different
franchises
The usage of open source technology tools reduced the development cost of the application
The application is an end to end analytics solution with an easy to use UI
As a part of the project, the team also did some customer surveys to understand complex
customer behavior and create strategies based on the same
Achievements
The client’s target was to reduce marketing costs by 20 percent. The solution reduced the marketing
costs by 27.25 percent
The monthly sales of the client increased by 14 percent within a year of installing the application of
Target marketing and market basket analysis
Analysis
Pyramid
1
Analysis
Pyramid
2
Analysis
Pyramid
3
Analysis
Pyramid
N

5. The regular feedback from client allowed us to track customer sentiments. Also the satisfaction level
(based on sentiment analysis) had increased
The real time tool allowed outlet managers to perform analysis on the go. This feature allowed them
to provide customized services to every customer
Technology Deployed
RDBMS Systems
MySQL
Application Servers
RStudio, Anaconda
Operating Systems
RedHat Enterprise
Level Servers
Cloud Infrastructure
AWS
NoSQL/Graph DB Systems
Hadoop and Hive
Client : Retail Store
Chain
Location : Mumbai, India
Industry : Retail
Duration : 1 year
Team : 5 People
Project Highlights
About PSI
Pratham Software (PSI) is a global IT services company (with established ISO 9001:2015 & ISO/IEC 27001:2013
practices) providing software product development, consulting and outsourcing solutions to enterprises worldwide.
While providing a wide range of solutions, we focus on Outsourced Product Development (OPD), Business Process
Management (BPM), Application Development and Maintenance (AMD) and Content Engineering. Our extensive
experience in OPD helps us build strong relationships with Independent Software Vendors (ISVs), as we work with
them throughout the product development lifecycle. In terms of technology and platform, we work across all major
technologies such as Microsoft, Java and Open source and have capabilities and experience in developing solutions
for web, mobile, Cloud and social media. For Enterprise customers, in addition to Process Automation, we also offer
development and support services in BI and DWH.
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