Final Project - Analyzing a Use Case for Case Study

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Use Analytic Plan to Guide Final Presentation

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Source: EMC^2 Dell DSA Module

Componets of Analytic Plan

Example - Retail Banking

Discovery Business Problem Framed

How do we identify churn/no churn for a customer?

Initial Hypothesis

Transaction volume and type are key predictors of churn rates.

Data & Scope

7 months of customer account history

Model Planning – Analytic Technique

Logistic regression to identify most influential factors predicting churn.

Results & Key Findings

Once customers stop using their accounts for gas and groceries, they will soon

erode their accounts and churn.

If customers use their debit card fewer than 6 times per month, they will leave

the bank within 55 days.

Business Impact

If we can target customers who are high-risk for churn, we can reduce customer

attrition by 22%. This would save $2.3 million in lost customer revenue and avoid

$1.1 million in new customer acquisition costs each year.