Recency, frequency, monetary and RFM score.

rfm_table_order(data = NULL, customer_id = NULL, order_date = NULL,
  revenue = NULL, analysis_date = NULL, recency_bins = 5,
  frequency_bins = 5, monetary_bins = 5, ...)

Arguments

data

A data.frame or tibble.

customer_id

Unique id of the customer.

order_date

Date of the transaction.

revenue

Revenue from the customer.

analysis_date

Date of analysis.

recency_bins

Number of bins for recency.

frequency_bins

Number of bins for frequency.

monetary_bins

Number of bins for monetary.

...

Other arguments.

Value

rfm_table_order returns a tibble with the following columns:

customer_id

Unique id of the customer.

date_most_recent

Date of the most recent transaction.

recency_days

Number of days since the most recent transaction.

transaction_count

Total number of transactions of the customer.

amount

Revenue from the customer.

recency_score

Recency score of the customer.

frequency_score

Frequency score of the customer.

monetary_score

Monetary score of the customer.

rfm_score

RFM score of the customer.

Examples

analysis_date <- lubridate::as_date('2006-12-31', tz = 'UTC') rfm_table_order(rfm_data_orders, customer_id, order_date, revenue, analysis_date)
#> # A tibble: 995 x 9 #> customer_id date_most_recent recency_days transaction_count amount #> <chr> <date> <dbl> <dbl> <dbl> #> 1 Abbey O'Reilly DVM 2006-06-09 205 6 472 #> 2 Add Senger 2006-08-13 140 3 340 #> 3 Aden Lesch Sr. 2006-06-20 194 4 405 #> 4 Admiral Senger 2006-08-21 132 5 448 #> 5 Agness O'Keefe 2006-10-02 90 9 843 #> 6 Aileen Barton 2006-10-08 84 9 763 #> 7 Ailene Hermann 2006-03-25 281 8 699 #> 8 Aiyanna Bruen PhD 2006-04-29 246 4 157 #> 9 Ala Schmidt DDS 2006-01-16 349 3 363 #> 10 Alannah Borer 2005-04-21 619 4 196 #> # ... with 985 more rows, and 4 more variables: recency_score <int>, #> # frequency_score <int>, monetary_score <int>, rfm_score <dbl>
# access rfm table result <- rfm_table_order(rfm_data_orders, customer_id, order_date, revenue, analysis_date) result$rfm
#> # A tibble: 995 x 9 #> customer_id date_most_recent recency_days transaction_count amount #> <chr> <date> <dbl> <dbl> <dbl> #> 1 Abbey O'Reilly DVM 2006-06-09 205 6 472 #> 2 Add Senger 2006-08-13 140 3 340 #> 3 Aden Lesch Sr. 2006-06-20 194 4 405 #> 4 Admiral Senger 2006-08-21 132 5 448 #> 5 Agness O'Keefe 2006-10-02 90 9 843 #> 6 Aileen Barton 2006-10-08 84 9 763 #> 7 Ailene Hermann 2006-03-25 281 8 699 #> 8 Aiyanna Bruen PhD 2006-04-29 246 4 157 #> 9 Ala Schmidt DDS 2006-01-16 349 3 363 #> 10 Alannah Borer 2005-04-21 619 4 196 #> # ... with 985 more rows, and 4 more variables: recency_score <int>, #> # frequency_score <int>, monetary_score <int>, rfm_score <dbl>