Customer Analysis with CRM (RFM and CTB Analyses)

How to Analyze Your Customers with CRM

In today’s world of diversified customer needs, it is becoming increasingly difficult to maintain relationships through uniform marketing. CRM analysis is gaining attention, and it is a method to maintain good relationships with customers and attract fans and repeat customers.

CRM stands for Customer Relationship Management. CRM makes it possible to analyze various types of customers. 

Let’s take a closer look at the typical methods of analyzing customers in CRM and how to use each of them.

Rank your customers – RFM analysis

RFM analysis is a method of grouping customers using three indicators. It is often used in B2C businesses such as e-commerce sites. First of all, let’s take a look at what RFM analysis is all about.

Overview of RFM analysis

RFM analysis is a method named after the initial letters of three words: Recency, Frequency, and Monetary. The meaning of each word is as follows:

• Recency: Date of the most recent purchase
• Frequency: Frequency of purchase
• Monetary: Purchase amount

RFM analysis analyzes the buying behavior of customers from these three perspectives and ranks them.

For example, if a customer has purchased a product many times in the past and the total amount of money spent is high, it can be expected that the customer is good and is likely to purchase in the future. 

Similarly, customers who have purchased products many times in the past and have a large cumulative amount of money, but have not purchased any products for several years, are likely to have been lost to other companies.

In this way, you can divide the customer rank according to the data R, F, and. However, the number of groups and classification methods vary depending on the company performing the analysis. 

Purpose and characteristics of RFM analysis

The purpose of conducting RFM analysis is to select an efficient approach for each ranked group of customers to increase sales and profits and achieve greater cost-effectiveness.

The key is cost-effectiveness. Massively applying the same approach to all customers may improve sales, but it is more likely to result in unnecessary costs.

By using RFM analysis to rank your customers, you will be able to make appropriate approaches to potential customers and implement cost-effective measures.

Grouping by purchase amount – decile analysis

Decile analysis is an analysis method that uses customer purchase amount data. It is often used to extract good customers with high sales contributions. Let’s take a look at how we actually analyze it.

Overview of Decile Analysis

The word “decile” means “tenth” or “one-tenth.” A familiar example is “deciliter,” which means one-tenth of a liter. The first step in decile analysis is to sort all customers from the purchase history data in order of purchase amount and divide them into ten equal groups of 1 to 10.

Next, you’ll add up the purchase amounts per group and calculate how much of the total. By comparing the group’s share of sales, you can learn about each group’s purchasing trends and implement cost-effective measures tailored to the group’s characteristics.

Purpose and characteristics of Decile analysis

The purpose of decile analysis is to analyze customers’ high and low purchasing motivations. Because of these characteristics, you can choose to do narrow and deep marketing for customers who are highly motivated to purchase and broad and shallow marketing for customers who are less willing to purchase. The difference is that while RFM analysis ranks by date and frequency of purchase, decile analysis ranks by dividing a symmetrical axis, such as purchase amount, into ten equal parts.

Although it is a relatively easy method to analyze because there is little data to handle, it is necessary to note that the results change depending on when and from when the period of sales data is separated.

Separate by meaningful elements – segmentation analysis

Segmentation analysis is an analytical technique of grouping customers using the needs and attributes they have. Let’s take a look at some of the specific methods and characteristics of segmentation analysis.

Overview of segmentation analysis

We have various attributes such as age, gender, hobbies, and region of residence. Categorizing these attributes is called segmentation, and the analysis for this is called segmentation analysis. 

For example, you can segment customers who have purchased products by age to understand which age group has a large purchase volume, or conversely, identify the age at which purchase volumes are low. 

Segmenting not only by age but also by gender and region will lead to a more detailed understanding of needs.

Objectives of segmentation analysis

The goal of segmentation analysis is to identify groups that will be actively marketed by extracting attributes that will make them more willing to buy the product.

In addition, segmentation can be performed in more detail, allowing for more granular analysis than RFM and decile analysis.

Classify customers by three indicators – CTB analysis

CTB analysis is an analysis method that groups customers from three perspectives: Category, Taste, and Brand.

Let’s take a closer look at CTB analysis.

CTB Analysis Overview

CTB analysis is a method of grouping customers from three metrics to predict what purchasing behavior they will take next:

• Category: Categorize products into broad and small categories to find rough customer preferences
• Taste: Figure out what kind of style you prefer in color, shape, and other designs and sizes
• Brand: Understand your favorite brands, such as manufacturers, fashion brands, and characters

For example, you might want to categorize products purchased by customers into main categories, such as fashion items or food.

In addition, among fashion items, it is available in small categories such as T-shirts and Y-shirts and further subdivided into designs, sizes, brands, etc., so that you can grasp customers’ needs.

Purpose and characteristics of CTB analysis

The purpose of CTB analysis is to understand the hobbies and tastes of each group and to take an approach that suits each customer.

While RFM and decile analysis emphasize quantitative factors, CTB analysis is an analysis that is conscious of qualitative perspectives such as product categories and brands.

Summary

In this article, I introduced several methods of grouping and analyzing customers in CRM.

No matter which analysis method you use, the key is to collect and accumulate customer information. 

Building and operating a CRM from the ground up is often more difficult the more customer data a company has to deal with, so it is generally best to partner with a system vendor or other provider of CRM solutions to implement it.

There is a wide range of things to consider, such as whether the system has the functions and specifications to handle the analysis your company needs and whether it can store the large amount of data that your company needs. 

Therefore, when implementing CRM, consult with the appropriate partner who can support operational practices, such as post-implementation analysis.