RFV Models

Analyse key metrics to identify high value customers

The recent frequency value (RFV) model is an advanced customer segmentation strategy that analyses three key metrics: Recency, Frequency, and Monetary Value. This model helps businesses identify high-value customers based on how recently they’ve interacted with the brand, how often they engage, and how much they spend. One of the primary benefits of the RFV model is that it enables more accurate and data-driven targeting. By analysing these three dimensions, businesses can develop segmented marketing campaigns that speak directly to the most profitable customers, increasing the chances of repeat purchases and improving overall customer lifetime value (CLV).

Prioritises customers by propensity to repeat

A significant advantage of the RFV model is that it helps businesses prioritise customers who are most likely to engage and make repeat purchases. For example, customers who have recently made a purchase, buy frequently, and spend more money are prime candidates for loyalty programmes or high-value offers. By focusing marketing efforts on these high-frequency, high-value segments, businesses can enhance customer retention and increase the return on marketing investments. The RFV model, therefore, allows businesses to direct resources efficiently, ensuring that they are reaching the right customers with the right messaging at the right time.

Tailored programmes

In addition to improving targeting and resource allocation, the RFV model can enhance customer personalisation. By segmenting customers based on their recency,

frequency, and monetary behaviour, businesses can tailor their communications and offers to meet the specific needs of each group. For instance, customers who purchase frequently but haven’t engaged in a while (low recency, high frequency) may benefit from re-engagement campaigns, such as special discounts or exclusive offers, to encourage them to return. Conversely, customers who are frequent and high-value buyers can receive premium offers or exclusive loyalty rewards, creating a more personalised experience that deepens their connection with the brand.

Targets less engaged

The RFV model also helps businesses identify potential at-risk customers and take proactive measures to prevent churn. By tracking the recency and frequency of purchases, businesses can pinpoint customers whose engagement has dropped off. For example, if a previously high-value customer has not made a purchase in a long time, the business can launch targeted campaigns—such as personalised emails, reminders, or special offers—to encourage them to return. Identifying these patterns early allows for timely interventions, helping businesses retain valuable customers before they churn.

Project future revenue from existing customers

Finally, the RFV model provides valuable insights into the overall health of a business’s customer base. By analysing the distribution of customers across recency, frequency, and monetary value categories, businesses can track changes in customer behaviour over time. This helps identify shifts in purchasing patterns, assess the effectiveness of marketing campaigns, and adjust strategies as needed. Additionally, the model supports forecasting by projecting future revenue potential based on the historical data of top-performing customer segments, enabling businesses to make more informed decisions about growth strategies and customer engagement efforts.