Customer is the Kingmaker: A study through RFM Prism

Marketers constantly study the purchase style and behaviour of customers for aligning their marketing activity to suit the customer’s expectation and also to increase the sales and margin of its products or brands. One of their metrics for this is called RFM model comprising of Recency, Frequency and Monetary Value.

Companies always believe that customer is the kingmaker of any business and accordingly they focus greatly on them. They identify the need of target customer and design the marketing mix to satisfy their customer. The delighted customers show loyalty to the company and go for repeat purchases enriching the company’s business. Similarly, dis-satisfied customers do not go for repeat purchase, rather do bad mouth for the company and its products. Therefore, companies constantly try to satisfy existing customers and to attract current non-customers to purchase their product. This process goes on.

The psychographic purchase behaviour of the customer is usually influenced by motivation, perception, learning, belief and attitudes about a product, brand or a company. Motivation and selective attention may create new customers for trial, but selective retention and attitude towards the product used, can result in repeat purchases. A delighted customer can react in various ways like frequent buying, bulk buying and buying other products of the company too. Similarly, a dissatisfied customer may react in two different ways, by spreading bad mouth (Voice Option) or stop buying company’s product (Exit Option).

Marketers constantly study the purchase style and behaviour of customers for aligning their marketing activity to suit the customer’s expectation and also to increase the sales and margin of its products or brands. One of their metrics for this is called RFM model comprising of Recency, Frequency and Monetary Value. Recency speaks about when the last purchase was made by a customer for the product. This measure is based on the notion that a customer purchased recently is an active customer and he will also continue his purchase in feature. This leads to high possibility of revisit, re-purchase and more quantity purchase. This prompts the company to keep these customer group in one segment and design marketing efforts for them to reap more business with profit.

Similarly, frequency of visit by customers determines the material flow and necessity for replenishment of stock. Frequency is the number of visits by a customer in a specific time period. It enables to prepare a list of regular customers and to design appropriate marketing effort to retain such loyal customers for longer period. Thirdly, monetary value spent by an average customer speaks about the quality of purchase. For gaining higher return on investment, companies design special marketing action to retain these high value customers.

Customer segmentation can be made on the basis of these three factors (recency, frequency and monetary value) and appropriate marketing efforts (new product push, sales promotion scheme, stock positioning, supply chain plan etc) can be planned and be executed. RFM analysis is a data driven customer segmentation technique which divides the customer groups based on their Recency (last purchase date), Frequency (how often they buy) and Monetary Value (total spending). The objective of this model is to identify high-value customers and their behavioural pattern to design separate marketing efforts for different classes with an overall objective of customer retention and increase in return on investment (ROI).

Customer data is usually available in transactional databases of the company and can be extracted through data mining tools like SQL or Python and can be aggregated into a unified ‘customer-by-RFM matrix’. These data can be used for making predictive analysis to decide on various marketing decisions to be adopted. These decisions can be, integrating proper marketing mix, finding out optimal price to achieve higher revenue and profit, measuring marketing campaign effectiveness and forecasting short- or medium-term demand for company’s products.

The methodology of RFM analysis comprises of few steps like, assigning scores for customers in 3- or 5-point scale on each metrics, segmenting them to various segments based on scores awarded, and lastly, targeting defined customer group by sending tailored marketing messages. Various segments can be described as a) High R-High F-High M (considered as top customer, loyalists and brand advocates), b) Low R-High F-High M (high spending frequent but at risk as not buying recently), and c) Low R- Low F -Low M (low value inactive customers not worth for extensive marketing).

In a nutshell, the RFM model is a marketing tool for classifying customers into different classes based on three factors called as recency, frequency and monetary value. This exercise facilitates the marketer to predict buying behaviour and for appropriate marketing interventions with focussed attention and ultimately boosting overall revenue. This RFM model is one of the measures for customer mind-mapping on the basis of which appropriate marketing intervention is taken by the company.