What steps should be taken to implement a machine learning model to identify potential new customers on social media?

A Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers

Currently, the company has the following data in Amazon Aurora

• Profiles for all past and existing customers

• Profiles for all past and existing insured pets

• Policy-level information

• Premiums received

• Claims paid

What steps should be taken to implement a machine learning model to identify potential new customers on social media?
A . Use regression on customer profile data to understand key characteristics of consumer segments Find similar profiles on social media.
B . Use clustering on customer profile data to understand key characteristics of consumer segments
Find similar profiles on social media.
C . Use a recommendation engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
D . Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media

View Answer

Answer: B

Explanation:

Clustering is a machine learning technique that can group data points into clusters based on their similarity or proximity. Clustering can help discover the underlying structure and patterns in the data, as well as identify outliers or anomalies. Clustering can also be used for customer segmentation, which is the process of dividing customers into groups based on their characteristics, behaviors, preferences, or needs. Customer segmentation can help understand the key features and needs of different customer segments, as well as design and implement targeted marketing campaigns for each segment. In this case, the Marketing Manager at a pet insurance company plans to launch a targeted marketing campaign on social media to acquire new customers. To do this, the Manager can use clustering on customer profile data to understand the key characteristics of consumer segments, such as their demographics, pet types, policy preferences, premiums paid, claims made, etc. The Manager can then find similar profiles on social media, such as Facebook, Twitter, Instagram, etc., by using the cluster features as filters or keywords. The Manager can then target these potential new customers with personalized and relevant ads or offers that match their segment’s needs and interests. This way, the Manager can implement a machine learning model to identify potential new customers on social media.