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R

ecency, Frequency, Monetary, or RFM analysis is a technique used to determine which customers are likely to respond to a new offer by examining the following:RFM Analysis is a way of grouping & organizing all your customers into segment-based clusters according to customer behaviors: 

  • Recency - How recently did the customer purchase?
  • Frequency - How often do they purchase?
  • Monetary Value - How much do they spend?
For each customer visible in the CRM grid, RFM analysis calculates and assigns a score from 1 to 5 for each RFM measure.
  • what's the monetary value of their purchases?

The goal of RFM analysis is to understand who is more likely to buy from you again and when they will do it. RFM models provide a bird-eye view of your customer base and better understand customer behaviors and purchasing habits. 

RFM uses purchase history. Advanced Search in PSCUM.CRM calculates RFM scores. RFM values range from 1 to 5.  A score of 5 represents the top 20% of the population, while a score of 1 represents the bottom 20%, scores 2, 3, and 4 the 20% ranges in between.  A score of one (1) means the least recent, least frequent, or lowest spendmonetary value, while a score of five (5) means the most recent, the most frequent, or the highest monetary value. The system concatenates each measure into a three-digit score ranging three measures together range from 111 to 555, a.k.a., the RFM score. The highest score is 555, meaning the customer purchased most recently, most frequently, and at the highest monetary value. The lowest score is 111, meaning the customer has purchased the least recently, least frequently, and at the lowest monetary value. 

The system derives RFM scores based on a selected customer population and how an individual's RFM score plots on a relative scale of 100%. 

  • A score of 5 represents a rank in the top 20% of the population, that is, scores in the 80-100th percentile.
  • A score of 4 represents a rank in the next 20% of the population, that is, scores in the 60-79th percentile. 
  • A score of 3 represents a rank in the next 20% of the population, that is, scores in the 40-59th percentile. 
    • A score of 2 represents a rank in the next 20% of the population, that is, scores in the 20-39th percentile

    . 

    A score of 1 represents a rank in the bottom 20% of the population, that is, scores in the 0-19th percentile.

    The analytical technique entails establishing a benchmark RFM score and saving it in for future reference.  In the CRM record grid, the system identifies that value as the "Last RFM."  You would use the scores to develop segments and outreach strategies. After some timea while, you would regenerate RFM scores and compare the results to their Last RFM score to identify customers whose scores improved or worsened, increased or decreased.  When regenerating RFM scores, and develop strategies accordingly.you must use the same start-stop date range and selection criteria to compare apples to apples.  

    Table of Contents

    Table of Contents
    excludeTable of Contents|Introduction



    Where Is It Found

    Ui expand
    titleWhere to find it

    navigation placeholder replace


    Steps to Calculate RFM

    Step 1: PSCUM.CRM Advanced Search

    Launch the menu option PSCUM.CRM Customer Management and select Advanced Search. 

    ...

    Once returned to the CRM Grid, note the yellow control labeled "Refresh Needed."  Click to refresh the CRM screen and pull up all customers meeting your Advanced Search criteria.


    Step 2: Review

    Immediately following the RFM score calculation, nine additional columns appear in the CRM grid, highlighted below. Calculated RFM scores are temporary and are shown for comparison with a customer's last RFM score if any. Calculated RFM scores are only visible while Advanced Search is active and disappears from the grid when ended. 

    ...

    In the image above, Rows 14 and 15 have no Last RFM score, probably because one was not previously saved or was removed. Rows 1 through 13 contain the Last RFM score, however, and the current RFM calculation indicates changes in behavior compared to the Last RFM calculation. For example, Row 6 shows a current RFM of 114 compared to the Last RFM of 453, indicating that the customer's behavior changed negatively since the last analysis. That is, purchased less recently, purchased less frequently, but spent more than the last analysis.  

    Step 3: Use Mass Change to Save the most recently calculated RFM score.

    To save and make a permanent record of the current RFM calculation, choose Work With Checked to Mass Change selected records.

    ...

    Press Enter then Continue to review and confirm before and after results.



    PSCUM.CRM - RFM Program Logic - Building Buckets

    Method:  Inspect the items being measured. Find the top and bottom values. Take the difference and divide by 5 giving bucket ranges. Assign items to buckets. Done (Tim Smith, 1981- )

    Recency Example (the R-Score of RFM)

    • Scenario:  Order Selection in 24-month date range, from Jan 1, 2020, through Dec 31, 2021 
    • 24 months / 5 = 4.8 months (rounded to 5)
    • Yields five 5-month ranges
    Last Purchase in Month Range...R-Score

    Last Purchase in Date Range (assuming SOLD or SHIP date?)

    21-251January 2020 - April 2020
    16-20

    2

    		May 2020 - September 2020
    11-153October 2020 - February 2021
    6-104March 2021 - July 2021
    1-55August 2021 - December 2021

    Questions for Programming: 

    1. What date does the system use: Batch, Sold, Shipped?  Assumes program uses Batch Date since individual line items can be SOLD and SHIPPED on different dates.  
    2. When rounding, where does the program put the short range?  In the example above, priority was given to R-Score 5, Last Purchase within last 1-5 months. R-Score 1 represents last purchase 21-25 months ago.  Since our date range only encompasses 24 months, the program will not encounter anyone whose last purchase was 25 months ago. 
    3. Is the system selecting negative amount transactions? That would negatively affect a RECENCY score.

    Frequency Example (the F-Score of RFM)

    • Scenario:  N customers, each having completed a different number of purchases within whatever date range. The value of n does not matter. 
    • Tally purchasers per customer
    • Highest individual count is 15
    • Lowest individual count is 1 
    • 15+1 = 16 /5 = 3.2 (rounded to 3)
    • Yield five 5 ranges in increments of 3 
    Frequency ranges...F-Score

    Individual tally/count of purchases ...

    1-3 1Same as frequency range
    4-6

    2

    		"
    7-93"
    10-124"
    13+5"

    Monetary Example (the M-Score of RFM)

    • Scenario:  N customers, each having completed a different number of purchases within whatever date range at whatever monetary value. The value of n does not matter. 
    • Tally net sales amount (question) per order per customer 
    • Highest individual net sale amount is $2,500
    • Lowest individual net sale amount is $20 (assuming CREDIT and negative amount transactions are not being selected 
    • $2,500+$20 = $2,520/5 = $504
    • Yield five 5 ranges in increments of $504
    Monetary ranges...RFM Score

    Individual sum of monetary value ...

    $1 - 5041Same as monetary range
    $505 - 1,009

    2

    		"
    $1,010 - 2,5233"
    $2,524 - 3,0284"
    $3,029+5"


    Questions for Programming:  

    1. Is the program selecting $0 dollar transactions?
    2. Is the program selecting transactions with negative amounts, including CREDIT transactions?
    3. For monetary scores to be accurate, the system should include all transactions.