rfm_plot_median_recency: Median plots
In rsquaredacademy/segmentr: Recency, Frequency and Monetary Value Analysis

rfm_plot_median_recency

R Documentation

Median plots

Description

Segment wise median recency, frequency & monetary value plot.

Usage

rfm_plot_median_recency(
  rfm_segment_table,
  sort = FALSE,
  ascending = FALSE,
  flip = FALSE,
  bar_color = NULL,
  plot_title = NULL,
  xaxis_label = NULL,
  yaxis_label = NULL,
  axis_label_size = 8,
  axis_label_angle = 315,
  bar_labels = TRUE,
  interactive = FALSE,
  animate = FALSE,
  print_plot = TRUE
)

rfm_plot_median_frequency(
  rfm_segment_table,
  sort = FALSE,
  ascending = FALSE,
  flip = FALSE,
  bar_color = NULL,
  plot_title = NULL,
  xaxis_label = NULL,
  yaxis_label = NULL,
  axis_label_size = 8,
  axis_label_angle = 315,
  bar_labels = TRUE,
  interactive = FALSE,
  animate = FALSE,
  print_plot = TRUE
)

rfm_plot_median_monetary(
  rfm_segment_table,
  sort = FALSE,
  ascending = FALSE,
  flip = FALSE,
  bar_color = NULL,
  plot_title = NULL,
  xaxis_label = NULL,
  yaxis_label = NULL,
  axis_label_size = 8,
  axis_label_angle = 315,
  bar_labels = TRUE,
  interactive = FALSE,
  animate = FALSE,
  print_plot = TRUE
)

Arguments

`rfm_segment_table`	Output from `rfm_segment`.
`sort`	logical; if `TRUE`, sort metrics.
`ascending`	logical; if `TRUE`, sort metrics in ascending order.
`flip`	logical; if `TRUE`, creates horizontal bar plot.
`bar_color`	Color of the bars.
`plot_title`	Title of the plot.
`xaxis_label`	X axis label.
`yaxis_label`	Y axis label.
`axis_label_size`	Font size of X axis tick labels.
`axis_label_angle`	Angle of X axis tick labels.
`bar_labels`	If `TRUE`, add labels to the bars. Defaults to `TRUE`.
`interactive`	If `TRUE`, uses `plotly` as the visualization engine. If `FALSE`, uses `ggplot2`.
`animate`	If `TRUE`, animates the bars. Defaults to `FALSE`.
`print_plot`	logical; if `TRUE`, prints the plot else returns a plot object.

Examples

# analysis date
analysis_date <- as.Date('2006-12-31')

# generate rfm score
rfm_result <- rfm_table_order(rfm_data_orders, customer_id, order_date,
revenue, analysis_date)

# segment names
segment_names <- c("Champions", "Potential Loyalist", "Loyal Customers",
                   "Promising", "New Customers", "Can't Lose Them",
                   "At Risk", "Need Attention", "About To Sleep", "Lost")

# segment intervals
recency_lower <-   c(5, 3, 2, 3, 4, 1, 1, 1, 2, 1)
recency_upper <-   c(5, 5, 4, 4, 5, 2, 2, 3, 3, 1)
frequency_lower <- c(5, 3, 2, 1, 1, 3, 2, 3, 1, 1)
frequency_upper <- c(5, 5, 4, 3, 3, 4, 5, 5, 3, 5)
monetary_lower <-  c(5, 2, 2, 3, 1, 4, 4, 3, 1, 1)
monetary_upper <-  c(5, 5, 4, 5, 5, 5, 5, 5, 4, 5)

# generate segments
segments <- rfm_segment(rfm_result, segment_names, recency_lower,
recency_upper, frequency_lower, frequency_upper, monetary_lower,
monetary_upper)

# plots
# visualize median recency
rfm_plot_median_recency(segments)

# plotly
rfm_plot_median_recency(segments, interactive = TRUE)

# sort in ascending order
rfm_plot_median_recency(segments, sort = TRUE, ascending = TRUE)

# default sorting is in descending order
rfm_plot_median_recency(segments, sort = TRUE)

# horizontal bars
rfm_plot_median_recency(segments, flip = TRUE)

# median frequency
rfm_plot_median_frequency(segments)

# median monetary value
rfm_plot_median_monetary(segments)

rsquaredacademy/segmentr documentation built on March 16, 2024, 2:07 a.m.