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Question 27 - CBDA discussion

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An insurance company would like to develop a range of insurance products for different types of customers. The analytics team is asked to conduct some research and share their insights with senior management. Which technique would be useful to divide the customer base into groups?

A.
Linear regression
Answers
A.
Linear regression
B.
Survey sampling
Answers
B.
Survey sampling
C.
Factor analysis
Answers
C.
Factor analysis
D.
K-means clustering
Answers
D.
K-means clustering
Suggested answer: D

Explanation:

K-means clustering is a technique that partitions a set of data points into a predefined number of clusters, based on their similarity or distance. This technique can be useful to divide the customer base into groups that have similar characteristics, preferences, or behaviors, and then design insurance products that cater to each group's needs and expectations. K-means clustering can also help identify outliers or anomalies in the customer data that may require further investigation or attention.

asked 18/09/2024
Lal George
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