The Origin of RFM

Recency, Frequency and Monetary value (RFM) was first cited in an article published in 1995, entitled ‘Optimal Selection for Direct Mail’. In this article, the RFM model is described as a ‘simple method that splits each RFM-variable into categories and assigns probabilities to each category of each characteristic in accordance with its differential response behaviour’. The model scores customer behaviour against three criteria; Recency (how long ago a customer purchased), Frequency (how often they purchase from you), and Monetary value (how much they typically spend).

The Challenges of RFM Analysis

Although RFM isn’t a new concept, its practical application – RFM analysis – is complex. Manually calculating RFM analysis across an ever-growing customer base is enough to dissuade any business from implementing it, especially for businesses wholesaling, distributing, or manufacturing products, taking hundreds of orders every day. With a constant inflow of new customers, and a mix of existing customers with various profiles (loyal, at-risk, lost), the customer base of a typical product business is dynamic. It’s also challenging to maintain mutual independence across the different profiles without automation; every business generates different spend patterns, so it can be arduous to categorise your customers when their criteria are completely different. In turn, it can be challenging to know where, when, and how best to prioritise resources most effectively for optimal results.

All things considered, keeping pace with the daily calculations that the RFM method demands to be effective might sound completely unfeasible alongside the varying other tasks that product businesses fulfil every day. So, to alleviate some of these challenges, investing in software that automates this process can produce fruitful results in the long term that increase your return of investment (ROI) and maximise profitable business growth. 

The #1 Secret in Wholesale & Distribution

With an automated RFM analysis in motion, calculated regularly and powered by customer and product intelligence from a back-office system like Inventory Management, product businesses can get an accurate, up-to-the-second picture of their customer base. 

1. Categorisation – RFM segments act like folders, slotting customers with similar profiles into cohorts, providing clarity and order. 
2. Prioritisation – Once categorised, your team can jump in at the right time to turn one-time transactional customers into long-term customers and save churn risks before it’s too late.
3. Communication – Targeting the right RFM segments with the right message is key to a winning marketing campaign.

CRM with RFM analysis built in gives wholesalers, distributors and manufacturers omniscient visibility of customer categorisation, allowing them to prioritise and communicate effectively with customers that require the most engagement. With CRM that amalgamates all the necessary data to productively contact customers at risk of churn, RFM works in tandem with stock, customer, and sales data that’s already extracted and stored within the system to drive profitable business growth, fast and at scale.

Not yet using RFM analysis to drive business growth? Hear from others who are already benefiting from this automated and proven customer segmentation strategy using CRM for product businesses.

Prospect CRM automatically segments customers by order Recency, Frequency and Monetary value into a simple RFM visualisation for customer-facing teams – take a 14-day, no obligation Free Trial to get your RFM analysis now.