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By means of this project I am trying to create a value-based customer segmentation model using RFM(Recency, Frequency, Monetary) analysis in python using pandas, numpy and matplotlib

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What is Customer Segmentation?
Customer segmentation is the process of dividing customers into groups based on common characteristics so companies can market to each group effectively and appropriately. A company might segment customers according to a wide range of factors, including:
* Demographics
* Transaction history
* Geography
* Psychographic


Why Segment Customers?
Segmentation allows marketers to better tailor their marketing efforts to various audience subsets. Those efforts can relate to both communications and product development. Specifically, segmentation helps a company:
Create and communicate targeted marketing messages that will resonate with specific groups of customers, but not with others (who will receive messages tailored to their needs and interests, instead).
Select the best communication channel for the segment, which might be email, social media posts, radio advertising, or another approach, depending on the segment.
-Identify ways to improve products or new product or service opportunities.
-Establish better customer relationships.
-Test pricing options.
-Focus on the most profitable customers.
-Improve customer service.
-Upsell and cross-sell other products and services.

How to Segment Customers?
Customer segmentation requires a company to gather specific information about customers and analyze it to identify patterns that can be used to create segments.
Some of that can be gathered from the customers purchasing information such as job title, geography, products purchased, for example. Some of it might be gleaned from how the customer entered your system. An online marketer working from an opt-in email list might segment marketing messages according to the opt-in offer that attracted the customer, Other information, however, including consumer demographics such as age and marital status, will need to be acquired in other ways.
Typical information-gathering methods include:
-Face-to-face or telephone interviews
-Surveys
-General research using published information about market categories
-Focus groups

One commonly used techinque for business-to-consumer marketing is Recency Frequency Monetary analysis, where:
Recency: Recency is how recently for the date of analysis did the customer make a purchase. Customers who have purchased recently are more likely to purchase again when compared to those who did not purchase recently.
Frequency: Frequency is how often did the customer made purchases. The higher the frequency, the higher is the chances of these responding to the offers.
Monetary: Monetary is the total revenue generated by the customer through thier purchases. Customers who have spent higher contribute more value to the business as compared to those who have spent
Product Categorizing: To find the categories of products previously purchased by the customers

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By means of this project I am trying to create a value-based customer segmentation model using RFM(Recency, Frequency, Monetary) analysis in python using pandas, numpy and matplotlib

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