RFV stands for Recency, Frequency, and Value. It is a methodology widely used in marketing and customer analysis to segment and prioritize audiences based on their purchasing behavior. The central idea is to identify a company’s most valuable customers, helping direct personalized strategies to increase engagement, sales, and retention. It also assists in identifying less engaged customers to develop strategies to reactivate these contacts.
Here in Zenvia Customer Cloud, monitoring RFV provides a greater understanding of user behavior and guides customer decision-making based on data.
⚠️ Attention: To generate RFV data properly classified in the Success monitor, you must have integration with the ERP system. Additionally, the RFV is available for Administrator/Operator user profiles.
RFV Components
Recency (R): Measures how recently a customer made their last purchase with the company. Customers who purchased recently are more likely to respond to marketing campaigns. Generally uses the time interval (in days, weeks, or months) since the last purchase.
Frequency (F): Measures how often a customer has purchased with the company within a specific period. Customers who purchase frequently show greater engagement and loyalty. Counts the total number of transactions within a period.
Monetary Value (V): Measures the total amount spent by a customer on transactions. Customers who spend more tend to be more profitable for the company. Calculates the total sum of all purchases made by a customer.
Customer Profiles
Below are the contact groupings and their classifications in Zenvia Customer Cloud.
Champion Customers (R=5, F=5, V=5)
Description: Recently purchased, purchase frequently, and spend a lot.
Characteristics:
Highly loyal.
High revenue contribution.
Most likely to respond positively to campaigns.
Suggested Action:
Reward with loyalty programs or exclusive discounts.
Request feedback for improvement.
Loyal Customers (R=4-5, F=4-5, V=4-5)
Description: Purchase regularly and have a good average spend.
Characteristics:
Strong relationship with the brand.
Less sensitive to promotions.
Suggested Action:
Maintain engagement with personalized campaigns.
Introduce new products/services.
Potential Loyalty (R=5, F=1-3, V=1-3)
Description: Recently purchased but lack a robust frequency or value history.
Characteristics:
Potential to become loyal customers.
Still exploring the brand.
Suggested Action:
Send thank-you messages or welcome offers.
Provide incentives for repeat purchases.
Applications of RFV
Customer Segmentation:
Divide customers into groups such as "high-value," "inactive," or "new."
Example:
Recent + High frequency + High value = Premium customers.
Old + Low frequency + Low value = At-risk customers.
Personalized Campaigns:
Create marketing strategies tailored to customer behavior.
Example:
Recent customers may receive thank-you messages.
Inactive customers can receive re-engagement incentives like discount coupons.
Behavior Forecasting:
Predict which customers are most likely to continue buying based on RFV history.
Priority Service:
Customers with high RFV scores can receive special attention in services or support.
Practical Example of RFV Classification:
Customers can be classified into RFV scores from 1 (low) to 5 (high) for each criterion.
Customer A: Recency 5, Frequency 5, Monetary Value 4 → Highly engaged and profitable.
Customer B: Recency 2, Frequency 3, Monetary Value 2 → Medium interest customer.
Customer C: Recency 1, Frequency 1, Monetary Value 1 → Inactive customer.
This classification can help create matrices to focus efforts on the most relevant customers.
Done! Now you know how to analyze and classify RFV.