When RFM segmentation is not needed

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A large amount of data is required. RFM analysis is only effective if you have a large customer base and user data.
You can't set it up once and for all. Segmentation needs to be updated as the customer base changes constantly. If you do segmentation once and manually, it will quickly become outdated.
Limited criteria: The analysis takes into account only three parameters and ignores other important factors such as seasonality or behavioral characteristics.
Difficult to apply to potential customers. The method only works with existing customers, but can help identify segment characteristics for finding new customers.
The main disadvantage of RFM analysis is that it can provide distorted data, since metrics often reflect external factors, and not just customer loyalty. In addition, not all companies have an analytics system that provides data, which means it is more difficult to segment 100% of customers using the RFM method.

RFM analysis can be a valuable tool for marketing strategy, but it is list of afghanistan cell phone number not suitable for every company. Here are some examples when RFM analysis may not be useful:

The company has a small customer base. If you have only 100 customers and divide them into 27 segments based on RFM criteria, many segments will have too few customers to analyze. It is worth starting segmentation if the base contains about 1,000 customers and 3,000 transactions.
The company is new to the market. For recently launched startups, it is too early to conduct RFM analysis, since all customers have made purchases relatively recently. It is important to wait a few months to accumulate enough data for analysis. If there are few transactions, it may take months to collect data.
The company does not have data on all three parameters. If the business model does not include data on the recency of purchases, their frequency and the receipt, the method will not work. For example, SaaS services are often sold once with subsequent regular renewal of the subscription, and here the metrics of frequency and recency do not fully work.
The product does not imply repeat purchases. If you sell products that people usually buy rarely (for example, real estate), RFM analysis will not provide complete information, since the frequency of purchases will not be important. It will also be difficult to use it to increase the average check or develop a customer base.
The company has no plans to work with the database. RFM analysis should only be performed if you have the resources and desire to work with the data obtained to improve marketing activities. Without the willingness to apply the results of the analysis to the development and implementation of strategies for working with clients, the analysis itself is meaningless.
We have a separate article on customer segmentation . Use it to find the right method for your company.

How to divide customers into segments by RFM
To segment your customer base using RFM analysis, you need to follow three steps.

Data collection
Segmentation begins with collecting all the necessary data about customers. For B2B, this may be the company name, taxpayer identification number, contacts, position, and name of the decision maker. In B2C, this is usually the full name, email address, and phone number of the customer. And most importantly, data on dates, types, and amounts of transactions are needed.

Determine the period for which customer data will be collected. You can manually add it to the table or automate the process using a CDP platform.