Skip to content

Analytics and data science business case studies to identify opportunities and inform decisions about products and features. Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).

Notifications You must be signed in to change notification settings

byukan/Marketing-Data-Science

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

39 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

CUSTOMER-SEGMENTATION

Creating customer segments for a financial services firm using K-means Algorithm.

A variety of products, including mutual funds and exchange traded funds, are available for investors in the equities and bond markets from ABC, a relatively young provider of financial services. The financial services sector is predicted to develop significantly, at a compound annual growth rate of 20%, according to market research conducted by the management team. According to their research, challenger banks—new banks that compete with older, more established incumbents—are becoming increasingly popular with consumers. This has been especially true in North America and Western Europe, where millennials have shown a preference for banks like Monzo and Starling. The group has also acknowledged the rise in the significance of AI and machine learning. The ABC team wants to investigate the company's array of services and gain a better grasp of their current clientele with the help of this market study. The team also wants to find out whether there is a sizable prospective consumer base that they could focus on.

About

Analytics and data science business case studies to identify opportunities and inform decisions about products and features. Topics include Markov chains, A/B testing, customer segmentation, and machine learning models (logistic regression, support vector machines, and quadratic discriminant analysis).

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published