BIG PICTURE

Who Are Those 20% of Customers Generating 80% of Business?

The RFM model is a fundamental customer segmentation technique based on three attributes: how recently a customer has purchased (Recency), how often they purchase (Frequency), and how much the customer spends (Monetary). The results of RFM analysis help to make profit by reducing marketing costs as well as increasing the efficiency of marketing initiatives by better targeting an existing customer base.

RFM analysis has successfully been helping marketers for more than 30 years, why not improve it by combining it strengths with demographic data and present its results in a smart way?


CHALLENGES

Advanced Customer Segmentation for a Better Customer Experience

RFM analysis provides a business with advanced segmentation that leads not only to better customer experience through targeted communication, but also increases the efficiency of marketing spending. The analysis solves the following challenging questions.


1
How can I increase the ROI of my direct marketing campaigns?
2
Which customers should be reactivated, which cultivated, and which represent opportunities for a quick win?
3
Which customers are about to leave my business, do they represent a specific group?
4
Who are my newest customers, do they represent a specific group?
5
How can I identify non-responsive customers?
6
Is there a correlation between different RFM target groups and demographic data or my product base?
OUR APPROACH

The Power of Combined Data

RFM analysis software measures what your customers do in respect to what you offer: when they buy, how often they buy, how much they buy.

The demographic data of your customers provides you with the information of who your customers are: their age, income, household ownership, etc.

It is the combination of this data within CleverAnalytics that gets you the following:

  1. An overview of RFM analysis results combined with demographic data displayed on a smart map.
  2. Default pre-calculated segments of VIP customers, loyal customers, active customers, random customers, leaving customers, big spenders, budget-limited customers, and inactive customers.
  3. The values of attributes of RFM analysis (Recency, Frequency, and Monetary) can be filtered to see the results on a map and to export filtered data for additional use.
  4. The ability to combine customer segments of RMS analysis with demographic data, such as gender, age, or household income.

CONCLUSION

Digitally Transformed RFM

The RFM model as a key marketing segmentation method that had withstood the years has now been improved by digital transformation brought by CleverAnalytics. Our approach to RFM analysis is leveraged mostly by our valued customers, whose indivisible part of the marketing mix is direct marketing.

Become the master of RFM Analysis–the one known for lowering direct marketing costs and for increasing customer experience by targeting the campaign communication precisely while not cutting on the revenue stream. Take the next step: start our free trial or schedule a personal 1-on-1 online demo.

Related to RFM Analysis

Efficient Flyer Distribution

Efficient Flyer Distribution

Knowing who the most loyal customers are, who the ones who are about to leave or the biggest spenders are, all of these can help you in your direct marketing campaigns.

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Competitor Analysis

Competitor Analysis

RFM analysis gets you a different and advanced view on your customer base. We believe your competition deserves the same attention. See how your competition is doing.

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