Categorizes customers based on their purchasing behavior using the following metrics derived from transactional data.
How recently did the customer make a purchase? Recent customers are more likely to respond to offers.
How often does the customer make purchases? Frequent buyers show higher loyalty and engagement.
How much money does the customer spend? High-value customers contribute most to revenue.
RFM analysis creates distinct customer segments that enable targeted marketing strategies and personalized experiences. Typically, 4 to 12 mutually exclusive segments are identified. The number of segments is driven by distributions in the data and level of granularity desired.
Below is an example series of segments, including descriptions and hypothetical .
Last bought recently AND buy most often AND spend the most. Most valuable customers.
Last bought recently AND buy quite often AND spend above average. Consistent and loyal customers.
Buy regularly, but less frequently or spend less than Loyal / MVP. Customers who have the potential to become Loyal.
Most recent new to file customers, made 1 purchase so far.
Less recent new customers. Haven't returned and are on the verge of becoming At Risk.
Haven't purchased recently and/or reduced spending but used to be Loyal / MVP. High value customers, losing them would have a significant impact.
Haven't purchased recently, reduced order frequency or spending.
Haven't purchased in a long time.
Haven't purchased in a very long time, unlikely to return.
Our systematic approach to implementing RFM analysis and deriving actionable customer insights.
Gather customer transaction data including purchase dates, frequency, and monetary values.
Calculate RFM scores using quintiles or percentiles to rank customers on each dimension.
Combine RFM scores to create meaningful customer segments with distinct characteristics.
Develop targeted marketing strategies and campaigns for each customer segment.
Transform RFM insights into actionable business strategies that drive customer lifetime value and revenue growth.
Create personalized marketing messages and offers based on customer segment characteristics.
Identify at-risk customers early and implement retention strategies to reduce churn.
Optimize product recommendations and pricing strategies for different customer segments.
Focus marketing spend and efforts on high-value customer segments for maximum ROI.
Prioritize customer service efforts based on customer value and loyalty status.
Design tiered loyalty programs that reward and incentivize desired customer behaviors.
Start segmenting your customers and creating targeted strategies that maximize customer lifetime value and drive sustainable growth.