Topic 1 Question 50
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?
Use regression on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
Use clustering on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media
Use a recommendation engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media.
Use a decision tree classifier engine on customer profile data to understand key characteristics of consumer segments. Find similar profiles on social media.
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All of the questions in the preceding examples rely on having example data that includes answers. There are times that you don't need, or can't get, example data with answers. This is true for problems whose answers identify groups. For example:
"I want to group current and prospective customers into 10 groups based on their attributes. How should I group them? " You might choose to send the mailing to customers in the group that has the highest percentage of current customers. That is, prospective customers that most resemble current customers based on the same set of attributes. For this type of question, Amazon SageMaker provides the K-Means Algorithm.
https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
Clustering algorithms are unsupervised. In unsupervised learning, labels that might be associated with the objects in the training dataset aren't used. https://docs.aws.amazon.com/sagemaker/latest/dg/algo-kmeans-tech-notes.html
THE ANSWER COULD BE B.clustering on customer profile data to understand key characteristic
👍 34DonaldCMLIN2021/09/20Option C. This is not purely unsupervised, as clustering would be, because we have current and past customer profiles to go on. We want to find new customers by finding similar profiles on social media. So it is supervised to some extent. It's not a cluster problem; it is user-user collaborative filtering. The key is to recognize that this is not clustering. You're not blindly trying to group people. You have existing profiles that you are comparing them to.
👍 6cloud_trail2021/10/31- 正解だと思う選択肢: B
Clustering is basically the modelling method for customer segmentation.
👍 5ovokpus2022/06/28
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