Alteryx How To Do Customer Segmentation Through KMeans Clustering скачать в хорошем качестве

Alteryx How To Do Customer Segmentation Through KMeans Clustering

In this video I show you how to quickly do an accurate KMeans cluster analysis in Alteryx. I do add in the beginning RStudio and Rattle because they are just so much faster than the K-Centroids diagnostics tool in Alteryx. The diagnostics tool takes hours to do what I show you takes literally a fraction of a second in Rattle. Get a free stock like Apple, Exxon Mobil, GM, Ford, Tesla or Facebook worth up to $500 just by signing up and joining Robinhood using my link: https://join.robinhood.com/davidm16707 Once we've determined the appropriate for optimal cluster size we then take this information back into Alteryx and set up the cluster analysis and append tool. I walk you through every piece of this so that you can do this yourself in minutes or less. I show you each piece of it, the graph and the K means data. I also show you how to set it up so it appends a new cluster column to your data set for further analysis. Also explain you why we do this in data science and data and analysis and why it's so important. K means cluster analysis is used primarily for customer segmentation and it is very valuable and that it helps us to differentiate among different groups of customers and also if there's a time series data component we can look at the movement or change between these clustering groups over time. In data science one of the primary parts of any data science project is a good and thorough customer segmentation which almost always involves a KMeans cluster analysis. Equipped with what I teach you in this video you are all set to do a complete and thorough KMeans analysis. Yes there are other clustering algorithms and cluster analyses, but, as you will find, K means is the most popular and authoritative clustering method. Every good data science project has clustering and customer segmentation at its heart and beginning. In later videos I will show you how we can show movement of these customers in these clusters and how important this is why a marketing executive or sales executive would want to know this. KMeans clustering is a great tool to have on your data science resume and for general use and data science or data analysis. Every large data science project I do involves clustering and usually KMeans clustering. I utilize this all the time and you will to want to learn how clustering can help you to develop amazing insights into your customers data and how these clusters behave. I hope you found this video interesting and informational! Please take a moment to subscribe and like see can see all of my other great videos I have coming out! Also be sure and check out my channel and all the a great videos I have already out there on data science, data analysis, Alteryx, customer segmentation, cluster analysis, Rattle, RStudio, coding, prediction and forecasting, and so much more! Thanks again and God bless!