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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 - 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 monetary value, while a score of five (5) means the most recent, the most frequent, or the highest monetary value. The three measures together range from 111 to 555. 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 analytical technique entails establishing a benchmark RFM score and saving it for future reference.  In the CRM grid, the system identifies that value as the "Last RFM."  You would use the scores to develop segments and outreach strategies. After a 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, you must use the same start-stop date range and selection criteria to compare apples to apples.  

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