The Ultimate Guide to RFM Analysis: 3 Major Indicators and 6 Brand Application Examples to Help You Accurately Focus on Your Audience!

You may also want to conduct differentiated marketing and communication based on different customer values ​​and characteristics, thereby improving resource allocation and maximizing the benefits of CRM.

Among them, the RFM model is most commonly used by enterprises in practice.

In this article, I will tell you the detailed steps of using the RFM analysis model to help you identify customer pain points and opportunities. I will also use 6 actual brand cases to explain how you can break through pain points and seize opportunities after completing the analysis, thereby increasing customer lifetime value (LTV) and improving the integrity of the customer relationship management system.


Table of contents
What is an RFM analysis model? 3 key dimensions, divided into 8 customer groups
RFM and LTV have the same purpose: improving customer lifetime value should also start from these three levels
How RFM analysis helps to accurately target audiences and discover marketing opportunities and pain points
6 Brand RFM Application Examples: How to build a sound CRM based on opportunities and pain points?
Start RFM analysis now and launch a successful CRM!
RFM analysis model (RFM model): 3 key dimensions, divided into 8 customer groups
The marketing company Invesp mentioned the following 3 key data in its research and analysis of old customer retention and new customer acquisition:

(1) Existing customers are 50% more willing to try new products than new customers, and are willing to spend 31% more on new products.
(2) The cost of acquiring new customers is more than 5 times that of retaining old customers.
(3) Every 5% more old customers retained can increase overall profits by 25%-95%.

It can be seen from this that it will be a better resource allocation model for brands to invest resources in the analysis and retention of existing customers, and in-depth and long-term relationship management. The best tool to start customer structure analysis is the RFM analysis model.

The RFM analysis model was proposed by George Cullinan in 1961, but its application has not become outdated, but has endured. In 1994, Arthur Hughes of the American Database Marketing Institute pointed out that there are three most important indicators in the customer database that can be used to analyze customer value. They are still used by many corporate brands today, namely:

Recency: Last consumption time
Frequency: consumption frequency
Monetary: Single consumption amount
We can divide customers into groups according to the "high" and "low" of R, F, and M respectively. By placing these three key indicators on the X, Y, and Z axes, customers can be visually divided into eight quadrants, forming the following most common RFM model diagram:


Image source: Qibao.com
The above are the 8 types of customers classified by applying the RFM model. It is not difficult to understand that each of the 3 indicators has 2 categories, resulting in 8 combinations. However, although such analysis is detailed, it is a bit complicated and difficult to understand, and is not conducive to solution planning. This article suggests that when applying RFM segmentation, you should first return to the essence of R, F, and M, and think about the significance of these three indicators in improving customer value.

RFM and LTV have the same purpose: improving customer lifetime value should also start from these three levels
We are in <LTV customer lifetime value algorithm and cases: dismantling complex formulas to keep up with marketing trends! ＞As analyzed in one article, if the LTV calculation formula is disassembled, it can be found that as long as the three indicators of customers' "purchase frequency", "customer unit price" and "customer longevity" are improved, in other words - as long as customers consume more often, Spend more money per purchase and continue to spend for a longer period of time, and your LTV will naturally increase.


The "purchase frequency", "customer unit price" and "customer longevity" in the above LTV formula are highly consistent and similar to RFM. "Purchase frequency" corresponds to Frequency; "customer unit price" corresponds to Monetary; and Recency (the most recent consumption time) can be used as one of the important indicators for predicting "customer lifespan".

How RFM analysis helps to accurately target audiences and discover marketing opportunities and pain points
Recognizing the inseparable relationship between RFM and LTV, we understand the importance of RFM to customer lifetime value. In other words, if a company wants to increase customer (lifetime) value and create good CRM results, it must use RFM segmentation to point out the company's current customer group structure and analyze what pain points and opportunities it faces in each customer group. Only then can you take the next step. Next, let us take a look at the high and low levels of the three indicators R, F, and M in order, which opportunities and pain points represent respectively.

Recency⬇️ Sleeper
Low Recency means that the last consumption was a long time ago. In marketing and CRM terms, low-recency consumers are also called “sleepers.” Sleepers may not interact with the brand for a long time due to various reasons, which is a pity for the brand. Therefore, the brand needs to understand the reasons why consumers are asleep, and attract sleepers to repurchase in a way that is not overly disturbing and has incentives.

Recency⬆️ Active customers
A high Recency means that the customer's last purchase was recent. It also means that the customer has a favorable impression of the brand recently, and the brand has the opportunity to take advantage of the trend. Customers with high Recency are also called "active customers". Brands should try to increase the proportion of active customers and reduce the proportion of sleeping customers. This will create a healthier customer structure and maintain a better brand image.

Frequency⬇️ Rare customers
Low Frequency means that customers do not consume frequently. However, infrequent consumption does not mean that there is no potential for frequent consumption. If the brand's proportion of rare customers is too high and the proportion of regular customers is too low, it may lack a stable source of revenue and have an unhealthy customer structure.

Frequency⬆️Frequency
Frequency is high, which means they are frequent customers of the brand. Frequent customers of the brand are more likely to pay attention to the brand's updates. If F and R are both high, they can also be said to be highly loyal customers. These loyal customers are often the main members of the brand and become the focus of the company's membership management.

Monetary⬇️ General customers
A low Monetary means that the amount of money customers are willing to spend on each purchase on the brand is low. A customer group with low M and F will provide the brand with lower customer value, so the brand should try to improve the M and F of this group of customers. If it cannot be improved, you should not spend too much marketing resources on this group of customers.

Monetary⬆️ Golden Guest
A high Monetary means that the customer is willing to spend more money on the brand at one time and is also a prime customer of the brand. Customers with high levels of R, F, and M can be regarded as the brand's VIPs and important value customers. Because it provides the most value to the brand, the brand should make the most efforts to expand and retain these important value customers.

Finally, this article introduces the specific practices of some well-known brands based on the opportunities and pain points represented by the three indicators R, F, and M.

6 Brand RFM Application Examples: How to build a sound CRM based on opportunities and pain points?
RFM and CRM are inextricably linked. Finally, let us understand the 4 parts of RFM application through examples. They are the preparatory work of analysis and how to use digital tools to effectively improve the three parts of R, F and M to optimize the effectiveness of marketing and CRM.

(1) Preparatory work: automatically collect and integrate RFM analysis data, and perform label segmentation
Before doing RFM analysis, you must have complete data before you can divide customers into groups based on Recency, Frequency, and Monetary. However, in practice, it is already troublesome to classify customer data and label different customers. What is even more troublesome is to integrate data from different sources, and to frequently update data and labels manually.

However, there are some modular data integration services on the market, such as the all-round marketing platform MAAC provided by marketing technology company Crescendo Labs, which allows brands to quickly connect and integrate common member platform information, CRM, CDP, etc. Automatic labeling based on members' consumption behavior, automating the process of labeling and focusing on customers, achieving precise customer identification and saving efficiency.

Taking Recency's data as an example, MAAC has a built-in "members who have not spent in the past 180 days" as a focus label, and will automatically label members based on their consumption behavior, allowing you to filter and classify sleeping customers and active customers with one click. Of course, brands can also define their own labels to classify Recency into more different levels, or classify them according to different standards based on industry and brand characteristics.

(2) Recency | Awakening sleeping customers and consolidating active customers: AI predicts consumption potential
After understanding which customers have recently purchased and which have not, the next step is to send different communication messages to different Recency customer groups. The fashion brand VEMAR usually makes good use of the function of LINE CRM. When using Crescendo Labs' MAAC for audience promotion, it will push corresponding LINE marketing messages based on "members who have not spent in the past 180 days" to effectively wake up sleeping customers.

Crescendo Labs' MAAC also recommends brands to use built-in AI models to more carefully use the "recent consumption time" dimension, combined with other indicators, to use machine learning to predict customers' potential purchase probability in the near future. For example, the closer the last purchase time is, the higher the probability of purchase is. By analyzing a large amount of data and the predictive model provided by MAAC, the brand may find that active customers who have purchased within three days are almost impossible to purchase again. At this time, the brand should not send disturbing messages to these customers to avoid increasing negative perceptions.


(3) Frequency | High efficiency, non-intrusive: precise communication, smart delivery time, automated customer journey
Different customers prefer different brands with different consumption frequencies.

Brands can first try to communicate more accurately to increase customer consumption frequency and avoid causing customer fatigue and disgust, or even causing future communication opportunities to be ignored or blocked. And precise communication means sending the right message to the right person at the right time.

"Send the right message to the right person"
Brands can try to collect and use other zero-party data to conduct more detailed targeted marketing and promote precise personalized messages. For example: Japanese underwear brand PEACH JOHN uses MAAC's automatic labeling function to receive discounts by filling out LINE questionnaires. Even the products that new LINE friends are interested in are "wireless underwear", "functional type" or "sleeping underwear", etc. Wait, you can create labels as soon as you join.

Based on effective data and audience focus, the average opening rate of marketing messages promoted by PEACH JOHN reaches over 50%. Large events such as anniversary celebrations and shopping festivals usually have an opening rate of up to 60-70%. PEACH JOHN also pointed out that after using LINE and MAAC as marketing tools, he found that "LINE's members are really active, the efficiency is very high, and the number of active members has also increased."

"Send a message at the right time"
The makeup brand MAKE UP FOR EVER makes good use of MAAC's smart sending function to automatically capture the user's active time. These times are also likely to be the time when users are relatively more willing to click on messages. MAAC can help brands send products to users at the right time. In addition to having a relatively high opening rate, it is also less likely to disturb people.


Automated Journey: Automatically send “the right message to the right person at the right time”
Through the customer journey, brands can better understand customer experience, interactive behaviors and touch points. At the touch points of digital marketing, MarTech tools can be used to design automated customer journeys based on customer preferences, consumption frequency and consumption habits, and make full use of Data enables marketing automation, efficiently diverts users, and creates a smooth customer experience.


In order to prevent new friends from being blocked and leaving after receiving the gifts, "zingala Silver Corner Zero Card" specially gives a sense of expectation in the welcome message, emphasizing that "you will get the shopping gold in a week" to give friends an incentive to stay. The Silver Corner Zero Card triggers an automatic journey through the tag of the new friend gift, and creates a second wave of contact experience with the "Quiz Turntable Game" seven days later, achieving an automatic journey completion rate of up to 92%! Chen Ruixing, senior deputy general manager of Yinjiao Zero Card, said: "The functions provided by Crescendo Labs' all-round marketing platform MAAC are very rich and practical, especially automated marketing, such as automatic responses and automatic journeys, which can reduce labor costs and the chance of human errors. .

Recommended reading: LINE marketing for gifted students without hiding anything (1)｜Up to 632% LINE friend growth rate: Silver Point Zero Card Trilogy to Efficiently Increase Fans

(4) Monetary | Mastering VIP Golden Customers: In-depth Membership Management

For different audiences of Monetary, of course, different resources should be invested, different content should be promoted, and different ways of interaction should be used.

The amount of money a customer is willing to spend at a single time is an important analytical dimension for brands. The two indicators of Recency and Frequency are more related to the appropriate interaction time point, while the Monetary indicator is more related to the product orientation and price band of the push.

GOMAJI, a large e-commerce platform, uses the product recommendation message function of Crescendo Labs MAAC and uses AI algorithms to automatically push featured product graphics that meet consumer preferences. Take GOMAJI's 10th anniversary celebration as an example. GOMAJI targeted LINE friends who interacted frequently within 30 days and used a machine learning model to analyze their friends' consumption footprints. In just 3 days, the click-through rate exceeded 81% and more than 430 orders were received!


In addition, transactions with a high Monetary may take a longer time for customers to consider, requiring layers of interaction and precise promotion to complete the final conversion. For example, the car brand NISSAN sells passenger cars for RMB 600,000 each, and it attaches great importance to membership management and thoughtful service.

In order to ensure that customers can obtain key information and enjoy fast and convenient services from the early stages of car ordering, purchase and delivery to after-sales maintenance and repairs, NISSAN started operating LINE official accounts and cooperated with the all-round marketing of Crescendo Labs The platform MAAC communicates its brand value to more than 400,000 active users in Taiwan. The head of NISSAN's digital marketing department said: "The interface of Crescendo is easy to understand and easy to operate. And because LINE is constantly being updated, Crescendo follows us, so we can use the latest features."

Start RFM analysis now and launch a successful CRM

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