Key Features: RFM Analytics
The RFM module provides the following features and benefits:
Tailorable
- Create RFM models and definitions
- Define categories for ranking each definition, such as recency, frequency, monetary, combined (calculated), and total (calculated)
- Define population and transaction queries
- Generate segments that divide the population into categories based on RFM criteria
- Create groups, such as quintiles, that reflect the relative ranking of customers according to all RFM measurements
- Generate lists of potential customers for marketing campaigns
Flexible and Efficient
- Establish multiple RFM analyses
- Define different customer population and transaction queries to include in each analysis
- Record a customer's first, last, and highest transaction amounts and the dates of the first and last contact
- Rank and organize your customer population into specific groups manually or automatically
- Query the list of customers to use for analysis
- Query the set of transactions to consider for analysis
- Store a combined ranking and a total ranking score
- Select one or more criteria for analysis
Measurable
- Generate RFM analysis results
- Query the results of the analyses
- Analyze transaction patterns to accurately predict future behavior
- Rank customer groups according to the relative recency, frequency, and monetary scores of their transactions
- Generate target lists of probable customers for marketing campaigns
- Identify the results you want in an analysis
- Predict a customer's response to a marketing campaign based on the customer's transaction history