Creating Customer Growth Strategies through Data Insights using Analytics for Retail Solution Overview One of the biggest problems many Retail Stores providing credit through their proprietary cards face is around what needs to be done post customer acquisition To download visit: blog.cequitysolutions.com and www.cequitysolutions.com

1. Creating Customer Growth Strategies
through Data Insights using Analytics
for Retail
Solution Overview
One of the biggest problems many Retail Stores providing credit through
their proprietary cards face is around what needs to be done post
customer acquisition. Once the customer has been acquired and has
been transacting, the behavior of the customer needs to be monitored
and on the basis of this behavior differential strategies for customer
growth need to be executed.
Each customer cannot be treated similarly since customer behavior
varies among individuals and hence they need to be treated differentially.
The same can be achieved by utilizing analytics which provides insights in
customer behavior to help distinguish amongst customers.

2. Business Problem- How to leverage Customer Growth through Data Insights
You need to differentiate customers and treat them differently. For which you need to answer the following questions:
Do we understand the drivers of Profit?
How different Marketing Drivers (Response Rate/Sale/Geography) are related to Profit?
Are we maximizing for Marketing Drivers and Profit?
Do we know the Future Demand for our Products?
Do we know how customers behave at various stages of their account lifecycle? Do
we know the Life Time Value of Customers?
L L
Create Customer Lifetime Value
if
and Utilize in Credit Line Increase
Strategies & Offer Timing resulting
in Incremental Sales
Peak
Purchasing
Increasing Decreasing
Purchases Purchases Account Lifecycle:- Long Term,
typically over the lifetime of a customers
association
Purchase Lifecycle:- Short Term, typically
over 1-2 yrs
Acquisition Attrite
How do we stock the right amount for effective customer service?
How do we produce the right quantity to minimize the inventory?
Are we testing the impact of all factors in a marketing program?
Are we doing continuous experiment to understand the customer purchase behavior?
Are we tracking the impact of marketing Programs?
Are we offering the right products to the right segments?
Who should we give a Credit Line Increase?
Design a Test & Learn Offer Type
Framework and streamline
the Impact Tracking & rollout
of Marketing Programs Channel Type
Customer Segments
Seasonality
Geography

3. Utilizing Customer Insight to drive Strategies for the Right Customer at the Right Time
Identifying Profitable Segments
Offer/ Product Design specific to segments
Build Predictive Models for Each Driver
Optimize Across Drivers
Use Secondary data to increase the Prediction Power
Incorporate Market Research Data for fine tuning
Develop robust Experimental Design framework using Fractional Factorial
Build Models to predict customer behavior like sales likelihood, time of buy, life of customer, offer response,
offer incremental sale, revolve behavior, expected sale, attrition probability, etc
Creation of Customer Lifetime Value from these predicted values
Develop Customer Segmentation
using external data for prospecting in
the absence of Internal
Performance Data
Overlay Business Strategy
Robust Program Impact Tracking Mechanism
Feedback Loop for full scale rollout
Create Relationship of Different Business Drivers to Profit
Measurement of Profit Across
Marketing & Risk Drivers
High
Create a Framework for Profit
and other Customer Drivers and
increase Profit with no compromise
on Marketing Objectives
Low Risk High
Low Profit High Profit Medium Profit
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