An overview of customer segments.
rfm_segment_summary(segments)
Output from rfm_segment
.
analysis_date <- as.Date('2006-12-31')
rfm_result <- rfm_table_order(rfm_data_orders, customer_id, order_date,
revenue, analysis_date)
segment_names <- c("Champions", "Loyal Customers", "Potential Loyalist",
"New Customers", "Promising", "Need Attention", "About To Sleep",
"At Risk", "Can't Lose Them", "Lost")
recency_lower <- c(4, 2, 3, 4, 3, 2, 2, 1, 1, 1)
recency_upper <- c(5, 5, 5, 5, 4, 3, 3, 2, 1, 2)
frequency_lower <- c(4, 3, 1, 1, 1, 2, 1, 2, 4, 1)
frequency_upper <- c(5, 5, 3, 1, 1, 3, 2, 5, 5, 2)
monetary_lower <- c(4, 3, 1, 1, 1, 2, 1, 2, 4, 1)
monetary_upper <- c(5, 5, 3, 1, 1, 3, 2, 5, 5, 2)
segments <- rfm_segment(rfm_result, segment_names, recency_lower,
recency_upper, frequency_lower, frequency_upper, monetary_lower,
monetary_upper)
rfm_segment_summary(segments)
#> segment customers orders revenue aov
#> 1 Loyal Customers 278 1708 166712 97.60656
#> 2 At Risk 86 438 44178 100.86301
#> 3 Champions 158 1234 120178 97.38898
#> 4 Need Attention 35 144 13287 92.27083
#> 5 Lost 111 244 20955 85.88115
#> 6 Potential Loyalist 229 801 65873 82.23845
#> 7 About To Sleep 50 127 10914 85.93701
#> 8 Others 48 210 22061 105.05238