What is RFM analysis?
RFM analysis helps businesses understand and categorise their customers. RFM stands for recency, frequency, and monetary value. These are 3 important metrics used to analyse customer behaviour and identify high-value customers.
Businesses use RFM analysis, for example, to look at how recently a customer made a purchase (recency), how often they buy (frequency), and how much they spend (monetary value). This helps those organisations understand a customer’s loyalty and overall lifetime value based on their own and a similar cohort’s engagement.
The benefits and challenges of RFM analysis
There are several advantages to RFM analysis, which not all businesses have historically been able to use.
That’s because RFM analysis can be quite manual, and not all teams have the resources, time, or tools available to implement strategies around its findings. Larger businesses have been the primary users of RFM analysis, as a result, but as tools like Klaviyo build RFM analysis into the platform, more and more businesses are using this information to create more resilient business strategies and customer lifetime loyalty.
Here are several benefits to RFM analysis for businesses of all sizes:
- Identify high-value customers and foster their loyalty
- Enhance customer retention and reduce churn
- Optimise marketing efforts by targeting the most responsive customer segments
- Personalise marketing messages and offers to boost engagement
- Uncover potential upsell and cross-sell opportunities
- Improve overall customer satisfaction and experience
Even as RFM analysis tools become more widespread, there are still challenges to accurate analysis. Here are two:
- Data quality and accuracy: Ensuring the accuracy and completeness of your data is crucial for reliable RFM analysis. Inaccurate or incomplete data can lead to incorrect insights and ineffective marketing strategies.
- Integration with existing systems: Integrating RFM analysis into your existing marketing platforms, such as your CRM or email marketing platform, may require technical expertise and resources.
Whether you run an ecommerce site, a subscription service, or a physical retail store (or all 3), RFM analysis can help you better understand your customers so you can ultimately grow your business.
How RFM analysis scoring works
Before you can run an RFM analysis, your business will need to fit certain criteria. Here’s what we recommend at Klaviyo:
- You have at least 500 customers who have placed an order.
- You have an ecommerce integration (e.g., Shopify, BigCommerce, Magento, etc.) or use the Klaviyo API to send placed orders.
- You have at least 180 days of order history and have orders within the last 30 days.
- You have at least some customers who have placed 3 or more orders.
Once you’ve reached this baseline, you can begin scoring. Here’s how it works:
- Each customer is assigned a score for recency, frequency, and monetary value on a 1-3 scale.
- A higher score indicates better performance in that metric (e.g., 3 means a very recent purchase or high spending).
- These scores are combined to form a 3-digit number, such as 333 or 123, representing the customer’s RFM profile. A “333” customer is highly engaged and valuable, while a “111” customer might be at risk of churn.
How to create segments with RFM analysis
Once customers are assigned scores, you can group them by common RFM profiles.
For example, customers with a score of 333 could form a VIP segment, as they’re highly engaged, frequent purchasers, and high spenders.
Customers with a score of 111 might fall into a dormant segment, representing those who haven’t purchased recently, buy infrequently, and spend minimally.
From there, you can create segmentation strategies like:
- High-scoring segments: Consider offering exclusive rewards, early access to products, or personalised communication to maintain loyalty.
- Mid-tier segments: Focus on encouraging higher frequency or spend with tailored promotions or loyalty programs.
- Lower-scoring segments: Run win-back campaigns, offering discounts or other incentives to re-engage them.
This segmentation allows you to maximise the effectiveness of your marketing efforts by addressing the specific needs and behaviours of each customer group, ultimately driving higher retention and revenue.
How to perform RFM analysis in 4 steps
- Collect the necessary data: Gather data on your customers’ recency, frequency, and monetary value. This information can be sourced from your marketing automation platform and several third-party integrations. Be sure you use a central source of data truth for your RFM analysis.
- Segment your customers: Use the data to divide your customer base into segments based on their RFM scores, like high-value and low-value segments, just to get started.
- Analyse each segment: Examine each segment to understand their behaviour and preferences. Identify patterns and trends, and then edit and optimise your marketing efforts to those specific customer segments.
- Develop targeted marketing strategies: Use the insights from your RFM analysis to create targeted marketing campaigns for each segment. For example, send personalised product recommendations to customers who haven’t made a purchase recently but have a high monetary value.
Klaviyo offers comprehensive features and tools to help businesses implement RFM analysis effectively. With Klaviyo, businesses can collect and analyse customer data, create customer segments, and automate personalised marketing campaigns based on RFM analysis.
Sign up for Klaviyo and start using your customer data to make smarter connections and grow your business.