I’m a Master’s student in Data Science and last semester I did a project on customer churn analysis. I’m interested in researching data mining for customer clustering. Are there any requirements for this research?

hello

Thank you for the reply you sent.

Be careful, in this research, there is no attempt to control the research variables.

The type of customers with the RFM model is determined by customer analysis in order to determine the best category of customers with the best performance, and finally, the stage of decision tree rules and classification of decision rules using the C5.0 decision tree algorithm is created.

What affiliation can you use?

I am very happy that you expressed your desire because your valuable information and ability can be used in this research.

If you agree, let's continue the conversation by email.

My email address is [email protected]

Here is the last point:

What was the output of your project about customer churn analysis? Has it been published as an article in a journal?

I would be honored if I could use your research on customer churn analysis for this collaboration. Let me also ask that your research was a case study?

I would be glad if you could send more details.

Yours affectionately.

Sorry, I’ve run into some issues. I explained the details in my email. Really sorry for the inconvenience.

Hello! If you're interested in researching the use of data mining in customer clustering, you're in a field that holds significant potential for improving business insights and decision-making. Customer clustering uses data mining techniques like k-means, hierarchical clustering, and DBSCAN to group customers based on behaviors, demographics, or purchasing patterns. By collaborating with experts in data science, marketing analytics, or machine learning, you can explore how clustering can enhance targeted marketing, personalized recommendations, and customer retention strategies. Many universities and research institutions have professors or research groups focused on data mining, so reaching out to them or joining relevant research forums and conferences could help you find collaborators. Platforms like ResearchGate, LinkedIn, or academic conferences in data mining, business intelligence, or machine learning can be valuable resources for finding like-minded individuals who can guide or collaborate with you in this research.