Week $1$ Case Study: Optimizing Retail Sales with RStudio

Sunshine Retail is a medium$-$sized chain of department stores. With the rise of ecommerce, the company has noticed a decline in in$-$store sales over the past year. However, they believe there's potential to optimize in$-$store sales by analyzing customer purchase data and store visit patterns.

Objective: Use RStudio to structure and analyze the store's data to derive insights that can help Sunshine Retail make data$-$driven decisions to enhance in$-$store sales.

Data Available:

CustomerData.csv: Contains customer demographics like age, gender, and location.

PurchaseData.csv: Contains records of each purchase, including product ID$,$ purchase amount, and timestamp.

StoreVisits.csv: Contains data on when customers visited the store, how long they stayed, and which sections they visited.

Steps for the Project:

Steps for the Project:

Setting Up RStudio:

Install necessary packages: dplyr$,$ ggplot$2,$ and lubridate for data manipulation and visualization.

Copy code: install.packages$($c$("$dplyr$",$ "ggplot$2",$ "lubridate"$))$

Data Import and Initial Exploration:

Load the datasets into RStudio.

Copy code: customer$\_$data read.csv$("$CustomerData$.$csv$")$ purchase$\_$data $\%>\%$