Predict Customer Lifetime Value for Non Techies/Beginners (Using Machine Learning, Code in Python)

IIM Community presents it's latest video on how to predict the Lifetime value of a customer using machine learning with codes in python. This video is especially designed for non-technical people/beginners who have a very faint idea of machine learning and predictive analytics.

If you are new to ML, I would highly suggest you to go through the below video to get an idea of the basics about it:

Link for the entire code mentioned in video:

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[VajkTuri]

Why do you have an ML model for prediction ? You kind of already have the target in the features: "OverallScore". An ML model could be applied if you would like to segment the customers without the cluster data only based on the features. But again, if you already have the "OverallScore" from the cluster scores, you should have a rule based """model""" which is 100% accurate.

[jaan-]

The dataset is 2010-11 can i get the latest data

[AkshayKumar-xosk]

Hi Mam, useful. But how to predict the cltv amount instead of segment name. How do I do if I want to predict cltv for next 3, 6 and 12 months?

[ARJUNSINGH-edpj]

Great session mam there is alot to learn from this video.

[vaidyulagsroy]

Very nice and well delivered. Able to get some idea on Machine Learning. Thank you!

[rozum.mariia]

Great explanation, thanks for the provided notebook!!!

[shalinirai]

Amazing video Ma'am.This was really helpful.