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")


# joining visits with geographical data to understand the customer locations;

customer_geography <- visits %>%
  left_join(geo, by = "VisitID") %>%
  left_join(purchases, by = "VisitID") %>%
  filter(!is.na(transactionID))  # Only customers who purchased


# countries analysis 

country_summary <- customer_geography %>%
  group_by(Country) %>%
  summarise(
    customers = n_distinct(VisitID),
    transactions = n_distinct(transactionID),
    total_revenue = sum(Payment),
    avg_order_value = mean(Payment),
    .groups = 'drop') %>%
  arrange(desc(total_revenue)) %>%
  mutate(
    revenue_dt = (total_revenue / sum(total_revenue)) * 100,
    customer_dt = (customers / sum(customers)) * 100)


# city analysis (top cities);

city_summary <- customer_geography %>%
  group_by(City, Country) %>%
  summarise(
    customers = n_distinct(VisitID),
    transactions = n_distinct(transactionID),
    total_revenue = sum(Payment),
    avg_order_value = mean(Payment),
    .groups = 'drop') %>%
  arrange(desc(total_revenue)) %>%
  head(15)

##graphing this data 

p1 <- country_summary %>%
  head(10) %>%
  ggplot(aes(x = reorder(Country, total_revenue), y = total_revenue)) +
  geom_col(fill = "steelblue") +
  geom_text(aes(label = dollar(total_revenue, accuracy = 1)), 
            hjust = -0.1, size = 3.5) +
  coord_flip() +
  scale_y_continuous(labels = dollar_format(),
                     expand = expansion(mult = c(0, 0.12))) +
  labs(title = "Top 10 Countries by Revenue",
       subtitle = "Where is Rita's webshop making money?",
       x = NULL,
       y = "Total Revenue") +
  theme_minimal(base_size = 12) +
  theme(panel.grid.major.y = element_blank())

p1

p1