Cluster Ensemble - Data Visualization

cluster_ensemble_data_visualization.R

# Group customer by their customer segment
rfm_level_agg = rfm %>%
  group_by(`Customer Segment`) %>%
  summarize(
    Recency = mean(Recency),
    Frequency = mean(Frequency),
    `Monetary Mean` = mean(Monetary),
    `Monetary Count` = n(),
    `Marketing Action` = unique(`Marketing Action`)
  )

# Visualize the RFM
ggplot(data = rfm)+
  geom_density(aes(x = Recency),
               fill = '#c22d6d',
               col = 'white')+
  labs(title = "Distribution of Customer's Recency",
       subtitle = 'Olist Customer Data')+
  xlab('Recency')+
  ylab('Density')+
  theme_bw()

ggplot(data = rfm)+
  geom_density(aes(x = Frequency),
               fill = '#c22d6d',
               col = 'white')+
  labs(title = "Distribution of Customer's Frequency",
       subtitle = 'Olist Customer Data')+
  xlab('Frequency')+
  ylab('Density')+
  theme_bw()

ggplot(data = rfm)+
  geom_density(aes(x = Monetary),
               fill = '#c22d6d',
               col = 'white')+
  labs(title = "Distribution of Customer's Monetary",
       subtitle = 'Olist Customer Data')+
  xlab('Monetary')+
  ylab('Density')+
  theme_bw()

# Visualize RFM Segment
ggplot(rfm_level_agg,
       aes(area = Frequency,
           fill = `Customer Segment`,
           label = `Customer Segment`))+
  geom_treemap(show.legend = FALSE)+
  geom_treemap_text(fontface = 'italic',
                    colour = 'white',
                    place = 'centre',
                    grow = TRUE)+
  scale_fill_brewer(palette = 'Dark2')