📊RFM analysis
Segment your clients automatically by their purchase behavior
Last updated
Segment your clients automatically by their purchase behavior
Last updated
RFM, also known as RFM analysis, is a type of customer segmentation and behavioral targeting used to help businesses rank and segment customers based on the recency, frequency, and monetary value of a transaction. RFM marketing can help marketers and small business owners determine their target audience to use their budget most effectively.
This method gives customers scores based on 3 factors:
Recency: Recency refers to how recent a customer's last purchase was. Customers who have made a recent purchase, typically within the last few weeks, still have the product and brand on their minds and are most likely to make a repeat purchase. You can measure recency however you deem necessary for your business. However, it's important to note that some companies might not have customers ordering every few days, weeks, or even months. For example, a car company might sell a single car to an individual within ten years.
Frequency: Frequency is how often the customer makes purchases, which can help you identify repeat customers. For example, many clients make frequent repeat purchases within a set timeframe. Frequency is essential in determining the individuals most likely to continue shopping with your brand after their first initial purchase.
Monetary value: Monetary value refers to how much a customer spends within a given period. It's always important to consider because it can tell you a few things about consumer behavior. For example, you might find that customers with the highest monetary value don't purchase items as frequently as others but typically buy the most expensive products when they do.
The values of each factor allow businesses to provide objective analysis and determine which audience to target for the most effective advertising and marketing campaigns. Most companies use a scale between 1 to 5, but you can use any values you think are necessary and helpful in evaluating clients.
Number of purchases from 0 to 3: RFM - Beginners
Number of purchases from 4 to 7: RFM - Growths
Number of purchases from 8 to 12: RFM - Champions
Number of visits 0 to 3: RFM - Doubtful
Number of visits from 4 to 7: RFM - Medium (borderline)
Number of visits from 8 to 12: RFM - Loyal - Regular
Number of visits 0 to 3: RFM - Sleeping
Number of visits from 4 to 7: RFM - At risk
Number of visits from 8 to 12: RFM - Needs attention
In our system, you have the flexibility to customize the values of Recency and Frequency metrics, allowing you to tailor RFM segmentation to the specific needs of your business. This functionality enables you to more accurately and effectively manage customer interactions, enhancing their loyalty and satisfaction.
Recency (time since last visit/purchase):
Setting intervals: Define intervals to assess the recency of the last customer interaction according to your business type. For example, in the retail sector, you might use intervals like 0-10 days (high activity), 11-20 days (medium activity), and 21-30 days (low activity). For hospitality, intervals could be 0-20 days (high activity), 21-40 days (medium activity), and 41-60 days (low activity).
Frequency (number of visits/purchases):
Setting ranges: Frequency can also be customized according to your business specifics. For example, in a cafe, frequency ranges might be 0-3 visits (low), 4-7 visits (medium), and 8-12 visits (high). For health and wellness services, the ranges might be 0-2 visits (low), 3-5 visits (medium), and 6-9 visits (high).
Precise Segmentation: By adjusting the values of Recency and Frequency, you can create more accurate segments that reflect your customers' behavior, enabling a better understanding of their needs and preferences.
Enhanced Marketing Efficiency: Personalized RFM segments help develop more effective marketing strategies targeted at specific customer groups. You can better manage communication, offering customers the deals they are most interested in.
Improved Customer Retention: Understanding customer behavior and responding promptly to changes in their activity helps increase loyalty and retention. You can quickly react to declining customer activity and take measures to re-engage them.
Go to https://app.boomerangme.cards/clients
Click "settings"
To illustrate the capabilities of our system, here are examples for different business types using the predefined Recency and Frequency values:
Food and Beverage (Cafes and Restaurants)
Recency:
High: 0-10 days
Medium: 11-20 days
Low: 21-30 days
Frequency:
High: 8-12 visits
Medium: 4-7 visits
Low: 0-3 visits
Health and Wellness (Salons, Gyms, Spas)
Recency:
High: 0-15 days
Medium: 16-30 days
Low: 31-45 days
Frequency:
High: 6-9 visits
Medium: 3-5 visits
Low: 0-2 visits
Medicine (Clinics, Pharmacies)
Recency:
High: 0-20 days
Medium: 21-40 days
Low: 41-60 days
Frequency:
High: 4-6 visits
Medium: 2-3 visits
Low: 0-1 visit
Professional Services (Lawyers, Consultants)
Recency:
High: 0-25 days
Medium: 26-50 days
Low: 51-75 days
Frequency:
High: 3-5 visits
Medium: 2 visits
Low: 0-1 visit
Retail (Stores, E-commerce)
Recency:
High: 0-10 days
Medium: 11-20 days
Low: 21-30 days
Frequency:
High: 10-15 visits
Medium: 5-9 visits
Low: 0-4 visit
Hospitality (Hotels, Tourism Services)
Recency:
High: 0-20 days
Medium: 21-40 days
Low: 41-60 days
Frequency:
High: 5-7 visits
Medium: 3-4 visits
Low: 0-2 visit
