Learn about how to perform a cluster analysis using R and how to interpret the results.
- [Instructor] Our customer has millions of email records,…and has been contextualizing that data…with customer preference and customer activity.…So we want to establish as set of segmentations…and use that information to create campaigns…that are personalized to different groups.…We're going to do that using cluster analysis using R.…So we have our R environment up…and let's go ahead and connect to our data.…So we have that line in there already.…Let's just select that line and click Run.…And let's have a look at what we're working with.…
So I'll type in the head command…and then I'm going to pass that our variable name.…So we'll do that right here.…And then our variable name, myClusterData.…And run that so we can see the printout…of that in our console here.…So we can see that we have five columns,…or what are known as five vectors, to work with…and I want to point out that these email addresses…that we have in the data have been encrypted.…So these are not actual email addresses of customers…that can be used for any purpose…
In this course, discover how to gain valuable insights from large data sets using specific languages and tools. Follow Chris DallaVilla as he walks through how to use R, Python, and Tableau to perform data modeling and assess performance. As Chris dives into these concepts, he shares specific case studies that come directly from his own work with clients. Plus, he shares three essential—and practical—best practices for data-driven marketing that you can use to bolster your organization's marketing performance.
- Installing R, Python, and Tableau
- Navigating the UI for R, Python, and Tableau
- Using R, Python, and Tableau
- Exploratory analysis
- Performing regression analysis
- Performing a cluster analysis
- Performing a conjoint assessment
- Stakeholder alignment
Skill Level Intermediate
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1. Software Installation
2. Data, Exploratory Analysis, and Performance Analysis
3. Inference and Regression Analysis
5. Cluster Analysis
6. Conjoint Analysis
7. Best Practices
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