Price Sensitivity Analysis Project

Overview

This project aims to analyze and visualize price sensitivity across different product categories. Utilizing R and the ggplot2 library, the script processes four categories of price sensitivity data and generates a comprehensive plot that illustrates the cumulative percentage of respondents' price sensitivity.

Installation

Before running the script, ensure you have R installed on your system. You will also need the here and ggplot2 packages. If these are not already installed, the script will attempt to install here automatically.

Usage

1. Setting Up Your Environment: The script utilizes the here package to set the working directory relative to the project root. This means you should have your project structured with the R script and the data files (too_inexpensive_data.csv, inexpensive_data.csv, expensive_data.csv, too_expensive_data.csv) in the same directory or a known structure that here() can recognize.

2. Data Preparation: The script reads in four CSV files representing different categories of price sensitivity:

   • Too Inexpensive
   • Inexpensive
   • Expensive
   • Too Expensive

   Each dataset should have at least two columns: Price and Percent, representing the price point and the percentage of respondents who rated it as such.

3. Running the Script: Execute the script in RStudio or your preferred R environment. The script will combine the data from the four categories, calculate cumulative sums for each, and plot the results.

4. Viewing the Output: The final output is a plot titled "Price Sensitivity Meter", which shows the cumulative percentage of respondents' sensitivity to different price points, categorized into four levels and color-coded for clarity.

Plot Explanation

• X-Axis (Price $): Represents different price points.
• Y-Axis (% Respondents): Represents the cumulative percentage of respondents who have indicated a level of sensitivity (too inexpensive, inexpensive, expensive, too expensive) at or below each price point.
• Colors: Each category is represented by a different color for easy distinction.

Requirements

• R
• here package
• ggplot2 package

Data Files

Place your data files in the project root or ensure they are accessible through the here() function. The expected files are:

• too_inexpensive_data.csv
• inexpensive_data.csv
• expensive_data.csv
• too_expensive_data.csv

Each file should follow the format of having at least Price and Percent columns.