space.template.RFM+analysis

=**​RFM analysis **= ** Q: What does RFM stand for? ** RFM refers to the use of the terms Recency, Frequency and Monetary.


 * Recency** – How recently a customer has purchased
 * Frequency** – How often they purchase
 * Monetary**- How much the customer spends

=**Q: What does RFM analysis mean? **=  RFM Analysis is a simple yet powerful method used for analyzing customer behavior and defining market segments. It is commonly used in database marketing and direct marketing and has received particular attention in the retail market.

It is based on both appropriate reasoning and experimental evidence of customer behavior. The idea is a simple one; consumers whom have purchased from you recently are much more likely to respond to a new offer and/or new promotions than someone who has not made a purchase in quite sometime.

= = =**Q: How do you find this information? **=  Information can be easily illustrated by anyone with a customer database that includes purchase history. The database has to keep at least one piece of information in every customer record. This information is then put into a coding system.

=Q:How does this coding work? = After a purchase each consumer is then evaluated on their shopping habits (RFM)

**//In terms of Recency?//** This data is typically split up into five equal groups with each group being assigned a value of either 5,4,3,2 or 1. A code of “5” is given for the **__most__** recent purchaser. A code of “1” is given for the **__least__** frequent purchaser.

This data is typically split up into five equal groups with each group being assigned a value of either 5,4,3,2 or 1. A code of “5” is given for the **__most__** frequent shopper. A code of “1” is given for the **__least__** frequent shopper.
 * //In terms of Frequency ? //**

This data is typically split up into five equal groups with each group being assigned a value of either 5,4,3,2 or 1. A code of “5” is given for the **__most__** amount of monetary value A code of “1” is given for the **__least__** amount of monetary value
 * //In terms of Monetary? //**

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=<span style="color: #ff0000; font-family: Verdana,Geneva,sans-serif; font-size: 12pt;">Q:​What does this information tell us about are customers? =

<span style="color: #000000; font-family: Verdana,Geneva,sans-serif; font-size: 12pt;">Experience tells us that the best prospects for an upcoming campaign are those customers that are in the 5 spot for each factor, those customers that have purchased most recently, most frequently and have spent the most money.

In fact, a common approach to creating an aggregated score is to concatenate the individual RFM scores together, which means a customer’s score can range from 555 being the highest, to 111 being the lowest.

=**<span style="color: #ff0000; font-family: Verdana,Geneva,sans-serif; font-size: 12pt;">Q: What are the advantages to RFM analysis? **= <span style="color: #000000; font-family: Verdana,Geneva,sans-serif; font-size: 12pt;">1. Simplicity – easy to understand and implement 2. Relatively low cost 3.Great start to develop Relationships marketing

=**<span style="color: #ff0000; font-family: Verdana,Geneva,sans-serif; font-size: 12pt;">Q:What should one keep in mind when useing RFM analysis? **=

<span style="color: #000000; font-family: Verdana,Geneva,sans-serif; font-size: 12pt;">Although RFM analysis is a useful tool, it does have its limitations. A company must be careful not to over solicit customers with the highest rankings. Experts also caution marketers to remember that customers with low cell rankings should not be neglected, but instead should be cultivated to become better customers.