Data Science and Analysis has revolutionized business marketing along with almost every other business domain. It has proven to be highly efficient and productive in Targeted Marketing making the marketing budget shrink for organizations and has increased sales considerably.

RFM is a method used for analyzing the customer values based on their shopping habits and past trends to figure out the products they will be interested in; target them with the right products marketing to make them feel that this email is customized just for them to create a more personalized experience. This process helps in growing the brand-consumer relationship exceptionally. 

RFM considers and Analyzes Recency, Frequency, and Monetary Value through Machine Learning based on the past shopping trends of customers. It enables you to derive the best marketing strategy for each classified group of your customers to target them with the right offer. The RFM does the Data Analysis based on:

• Recency: Recency is the data that tells you how recent has a customer purchased your product. This can enable you to check feedback from your product – if a customer is satisfied with the product over a long term use or they liked it at first glance and the initial experience is optimal for them.
• Frequency: Frequency allows you to have a look at customer shopping behavior that how often they tend to buy a specific product and what drives them to do so. You can also figure out the shelf life and utility of specific products through Frequency Data Analysis using Machine Learning.
• Monetary Value: Monetary value enables you to have a look at how much a customer has spent on specific types of products or in a set time range. It will provide insights and help in your marketing strategy and techniques more efficiently to come up with the best offers to target each group according to their past shopping trends and behaviors. 

RFM Segmentation

RFM Segmentation has a wide array of possibilities – you can customize according to the size and type of business operation you are running; it helps you to achieve optimal results in Data Mining and Data Analysis, and get the expected results you have planned by implementing those analyses to your marketing techniques. 

Segmentation through RFM allows you to track different patterns based on Recency, Frequency, and Monetary Value and combine these with different patterns as you like to get the results you are looking for. RFM segmentation is necessary to come up with an effective marketing strategy and target customers with offers that make them feel valued and as if the solution is tailor-made for them. It will ultimately increase the revenue earned in sales and saving your overall marketing budget. 

RFM Segmentation can be done on different criteria like classifying the customers who have purchased in the past 10 days and 30 days. It is effective to check if you can send them a marketing email combined with a survey to ask their feedback about the product or you can give a returning offer to a customer that has bought in the last 90 days and has not purchased again. 

Same way, when you combine Recency and Monetary Value, you can have a classification of customers from the past 30 days who have bought a substantial sum of your product. This way, you can derive a pattern through Machine Learning to get a clear picture of their interests and market trends to send them marketing emails regarding similar products that they have recently been interested in. 

Another example would be combining Frequency and Monetary Value to classify a group who has been purchasing your products or products of similar nature regularly of a substantial sum, and you can send them the customized offers to that group with the best value. To know more about RFM segmentation and implement the same for your business, feel free to contact NextBee.