slabrhn / rfm_analysis

CRM Analytics of Online_Retail_2 dataset

RFM_Analysis

CRM Analytics of PERSONA dataset

RFM Analysis In this study, customer segmentation was performed with RFM (Recency, Frequency, Monetary ) which is one of the Customer Relationship Management methods. RFM analysis measures customers in each category, according to Troy Segal’s article in Investopedia, a measurement value of 1-5 is common, with 5 as the highest/best value. The average of these categories results in a ranking of the “best” customers. (https://www.investopedia.com/terms/r/rfm-recency-frequency-monetary-value.asp)

WHY RFM

According to the Pareto principle, quite often 80 % of all results are based on 20% of actions/measures, which is why it’s also known as the “80/20 principle”. In marketing, the Pareto principle is often interpreted to mean that 80 % of the revenue is based on 20 % of the total customer base. RFM thereby determines characteristics that make up loyal, high-revenue customers. Therefore, segmenting the customers who have different effects on the system is important in customer-based marketing. In this way, it can be ensured that the churn customer rejoins the system, the loyalty of the customers who have just entered the system is increased, or the customers who have been in the system for a long time feel more valuable.

.Recency

Customers who have just purchased something are more likely to be loyal than customers whose last purchase was months or even years ago

.Frequency

.Loyal customers buy more frequently from a company. Accordingly, the value of purchase frequency is higher for them than for other customers.

.Monetary Value

Loyal customers often spend more money with their favorite companies than other customers. They can be motivated, for example, by promotions, product recommendations and offers.

Data Set

The dataset includes the sales of an online store between 2010 and 2011.

Variables

Invoice — Invoice Number “If this code starts with C, it means that the operation has been cancelled..”

StockCode — Product code “Unique number for each product.”

Description — Product Description

Quantity — Number of products purchased

InvoiceDate — Invoice Date

Price — Unit price(Sterling)

CustomerID - Unique number for each customer

Country — Name of the country