Understand the RFM model in depth
Model oriented to understand the purchasing behavior around:
The model uses quartiles as parameters. In simple terms, data is taken for the given period, outliers are excluded and the data is divided into 4 sections or quartiles.
The use of quartiles has the benefit of defining parameters relating to the data rather than configuring them externally, adjusting the categorization to each individual business.
For instance, think about how different the shopping frequency can be between a cafeteria and a computer store. Although both are retail, they are businesses with completely different shopping behavior.
A customer "moves up" in the category when he shows favorable buying behavior, usually in the parameter that determines his/her initial category.
For example, an Occasional client who increases the frequency with which he buys enough to go from quartile 3 to 4, automatically becomes a Loyal client.
The customer can also be downgraded if he shows unfavorable purchasing behavior.