In this section, we are going to discuss how we can use R to compute and visualize the KPIs we have discussed in the previous sections. We will primarily focus on analyzing conversion rates using bank marketing data. For those readers, who would like to use Python for this exercise, you can find the Python exercise in the previous section. We will be using the dplyr and ggplot2 libraries in R to manipulate and analyze data and build various charts to accurately report the progress and performances of marketing efforts. The dplyr library provides various functionalities for data manipulation for data science and machine learning tasks.
For the exercise in this section, we are going to use the UCI's Bank Marketing Data Set, which can be found at this link: https://archive.ics.uci.edu/ml/datasets/bank+marketing. You can follow this link...
