GROUP 5 Reducing Customer Churn Through Business Analytics

The case study focuses on reducing customer ______ through Business Analytics.

churn

The business entity in the case study is a leading ______ retail company.

e-commerce

The company analyzed ______ active online customers.

5,630

The company operates across three city tiers: Tier 1, Tier 2, and Tier ______.

3

About ______% of customers shop through mobile phones.

71%

Customer retention became a strategic priority because acquiring a new customer costs ______–______ times more than retaining one.

5–25

The overall customer ______ rate was 16.84%.

churn

A total of ______ out of 5,630 customers had stopped transacting.

948

Customers with four months of tenure or less had a churn rate of ______%.

38.17%

Customers who filed complaints had a churn rate of ______%.

31.67%

Mobile-phone-category shoppers had a churn rate of ______%.

27.40%

Single customers had a churn rate of ______%.

26.73%

The main type of analytics employed in the case study was ______ Analytics.

Descriptive

Descriptive Analytics answers the question, “What is ______ in our customer base?”

happening

The CRM system provided customer ______ such as gender, marital status, city tier, and tenure.

profiles

Sales transaction records included order counts, order category preferences, and days since last ______.

order

Mobile application ______ logs were one of the data sources.

usage

Customer service records included complaint ______.

flags

Marketing and loyalty systems included coupon usage and ______ amounts.

cashback

The company also used payment ______ records as a data source.

gateway

The dataset was classified as ______ data because it had rows and well-defined columns.

structured

The dataset contained 5,630 rows and ______ well-defined columns.

20

The total number of data points was ______.

112,600

The volume of the dataset was classified as ______.

medium

The data required cleaning because it contained missing values and inconsistent category ______.

labels

One descriptive analysis technique used was frequency ______.

distribution

Measures of central tendency were used to compute ______.

averages

Segmentation and ______-tabulation were used to identify where churn concentrates.

cross

The analysis compared ______ customers with retained customers.

churned

The average customer tenure was ______ months.

10.19

The average satisfaction score was ______ out of 5.

3.07

The average number of orders in the last month was ______.

3.01

The average cashback per customer was ₱______.

177.22

The Customer Health Dashboard displayed active customers, tenure distribution, days since last order, and app ______ hours.

engagement

The Churn Monitoring Dashboard provided visibility of the churn rate ______.

KPI

The Customer Churn Rate was ______%.

16.84%

The Customer Retention Rate was ______%.

83.16%

The Complaint Rate was ______%.

28.49%

The average days since the last order was ______ days.

4.54

The most actionable finding was that customers within their first four months churned at ______%.

38.17%

Customers beyond twelve months had a churn rate of only ______%.

5.01%

Complaint resolution was elevated from a customer-service task to a strategic retention ______.

lever

Cash-on-Delivery users had a churn rate of ______%.

24.90%

Tier 3 city customers had a churn rate of ______%.

21.37%

The company could target coupons, cashback, and engagement ______ toward high-risk segments.

campaigns

Dashboards shortened the decision cycle from weeks to ______.

days

The study found that churned customers had slightly ______ satisfaction scores than retained customers.

higher

The company learned that satisfaction surveys alone could not reliably ______ churn.

predict

The conclusion states that Descriptive Analytics can deliver immediate, ______ business value.

quantifiable

The analytics foundation can later support ______ churn models.

predictive