Can I segment the data and understand the typical customer?

library(tidyverse)
library(readxl)
library(scales)
library(lubridate)

load("C:/Users/riaku/Downloads/webshop.RData") 

library(readxl)
income_statement <- read_excel("C:/Users/riaku/Downloads/Income_statement.xlsx")

library(readxl)
promotions <- read_excel("C:/Users/riaku/Downloads/promotions.xlsx")

library(readxl)
prices <- read_excel("C:/Users/riaku/Downloads/Prices.xlsx")


# Basket analysis

basket_analysis <- shopping_basket %>%
  left_join(purchases, by = "transactionID") %>%
  mutate(
    total_items = Tshirt + Mug + Hoodie + Poster,
    item_variety = (Tshirt > 0) + (Mug > 0) + (Hoodie > 0) + (Poster > 0),
    basket_type = case_when(
      item_variety == 1 ~ "Single Item Type",
      item_variety == 2 ~ "Two Item Types",
      item_variety >= 3 ~ "Multi-Item"))


basket_type_summary <- basket_analysis %>%
  group_by(basket_type) %>%
  summarise(
    n_transactions = n(),
    avg_payment = mean(Payment),
    avg_discount = mean(Discount) * 100,
    avg_items = mean(total_items),
    total_revenue = sum(Payment),
    .groups = 'drop') %>%
  mutate(
    transaction_pct = (n_transactions / sum(n_transactions)) * 100,
    revenue_pct = (total_revenue / sum(total_revenue)) * 100) %>%
  arrange(desc(n_transactions))

##graphing this data 

p3 <- ggplot(basket_type_summary, aes(x = basket_type, y = transaction_pct)) +
  geom_col(fill = "pink") +
  geom_text(aes(label = round(transaction_pct, 1)), 
            vjust = -0.5, size = 4) +
  labs(title = "How Do Customers Shop?",
       subtitle = "Single item vs multiple items",
       x = "Basket Type",
       y = "% of Transactions") +
  scale_y_continuous(labels = function(x) paste0(x, "%"),
                     expand = expansion(mult = c(0, .15))) +
  theme_minimal() 

p3