Database Marketing Tips

Database marketing is the most important part of successful direct marketing because it contains all the required information for creating customized and personalized engagement. Based on the prospect’s and customer’s source, stage, interest, engagement, etc. personalized experience can be created by the company in order to maximize the direct marketing experience.

How to improve your database marketing with RFM?

Substantial increase in marketing effectiveness, productivity and customization has been achieved by many companies by simply adding the RFM approach to database marketing. RFM methodology allows you to slice and dice the data in your database based on the 3 RFM variables: R, F and M which stand for recency, frequency and monetary value.

Let’s take a look at these variables and how they can drastically improve your direct and database marketing:

1. Recency

This variable measures how recent each of your customers in your database is. The customer who purchased from you 1 week ago is generally more valuable compared to customer who purchased 3 years ago. The recency assigns points to each customer based on the last date of purchase. This variable scans the entire range of your purchase dates and categorizes all the customers into 5 categories by assigning a point on a scale from 1 to 5. The very same approach can be used for prospects and leads based on their last date of engagement.

Fill-in-the blank Excel KPI templates, dashboards, scorecards:

2. Frequency

The second RFM variable in database marketing is frequency. This measures how often your customers purchase your products or services. Those customers who do business with your company more frequently have higher lifetime value compared to customers who purchased only once. In addition these customers have a higher probability to purchase from you again in the future. Frequency measures and assigns the points from 1 to 5 based on the number of times a particular customer has bought from you.

3. Monetary

The monetary value variable is pretty obvious. It measures on a scale from 1 to 5 how much money your customers spend. This is important variable in loyalty programs, marketing campaigns and promotion planning because it allows you to drill down your customer data into 5 categories from low value customers to your golden customers. Based on their status you can customize and plan different promotions and offerings for various categories.

The bottomline is that in addition to your traditional or typical marketing variables like customer segmentation variables (age, location, social status, company, product interest, etc.) you should add the RFM concept to your database marketing. By doing this your direct marketing campaigns will become more personalized and customized while in addition you’ll achieve considerable cost savings in case of direct mail and event marketing for example because you’ll target the right customers for your offer.

The RFM marketing methodology is very simple to implement and yet very powerful because it targets and reveals the exact information you need to improve your overall marketing.

Related Resources:

Marketing Reporting Templates and Marketing Analysis Tools

RFM in Excel: Tools for Better Database Marketing

Situational Analysis in Marketing Strategy Development

Conjoint Analysis Tips

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