Data mining is the process of working with your data to identify important customer trends, behaviors, segments, patterns, etc. Every organization has historical data in one way or another.
Customer purchases, customer inquiries, customer service interactions, customer surveys, sales reports, data from partners and distributors… all of these are good sources for data that you can use for data mining and identifying trends, issues and opportunities for your business.
Data mining reveals important information regarding your customers that can help you identify different customer segments based on different segmentation criteria depending on your business needs. For example, by using simple data mining techniques you can easily identify segments of customers who buy more often, who buy more quantities, who are likely to continue to be your loyal customers, customers with changing purchasing behavior… There are many different ways to segment your customers from simple transactional data available in every organization.
Customer segments are useful for answering many strategic questions and can help you make smart decisions by identifying who is likely to remain loyal customer and who is not, who are the customers who will more likely respond to a certain offer, what products are hot and what products will be hot next year…
Data mining and customer segmentation is all about identifying patterns. However, before you use data mining and segmentation you need to make sure you know how you will use your new information. Many organizations use many different analytical tools and techniques but they are not good at using the information they obtain through data mining and customer segmentation.
3 Important Questions in Data Mining and Customer Segmentation
The three very important questions you need to answer are: 1. What is the purpose of my data mining and customer segmentation 2. What are the variables or attributes I am going to use in my segmentation 3. How I am going to use the information I obtain through my data mining and segmentation By considering these three questions you are creating a simple to follow structure for your analysis. This is called directed or planned data mining and it is usually more effective than simply playing with your data without a particular plan or objective.
Using the RFM Analysis and RFM Methodology
While there are different ways and approaches to data mining one of the simplest and most useful methodologies that can be used by anyone is RFM Analysis. If you don’t use RFM Analysis this is a good news because it will definitely reveal important and actionable information for your business. RFM Analysis is very simple approach that anyone can use – even business people without any analytical skills.
What is RFM Analysis?
RFM Analysis is a very simple methodology used for data mining and customer segmentation with the purpose of identifying certain customer behavior.
RFM uses three variables to answer three very important questions for your business and it is an abbreviation of the three variables:
1. R = Recency (Answers the question: how recently a customer made a purchase from your business?),
2. F = Frequency (Answers the question: How often a customer makes a purchase from your business?) and
3. M = Monetary Value (Answers the question: How much a customer spends in your business?).
The RFM methodology allows you to easily create different segments of your customers based on these three variables or attributes. You can create different segments of your customers by creating categories for each of the three attributes. You define the relevant categories based on your business for example one approach might be to create five categories for Monetary Value by segmenting customers in 5 segments based on their transaction history and another example will be to segment your customers into 5 categories based on when was the last time they made a purchase from you.
The RFM methodology and RFM analysis have been very effective for many companies in different industries and markets because this is a very simple, universal and flexible approach. RFM allows you to play with different combinations of categories for R, F and M in order to identify relevant, actionable and important information for your business.
RFM can help you segment customers in many useful ways, for example with RFM you can easily create a segment of your high transactions customers who have not purchased from you in the last 6 months but used to be loyal and frequent customers before that – this is a segment which is very important for your business and requires a customized sales and marketing efforts tailored to this segment. This is just one simple example of the many ways you can utilize RFM for your business.
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