Direct-to-Consumer Selling in a Cost of Living Crisis

BRISTOL, U.K. - Nov. 2, 2022 - PRLog -- RFM (Recency, Frequency and Monetary value) Analysis is the marketers' best friend in times of increasingly considered customer spending.

RFM is a database marketing analysis technique that seeks to understand an individual customer's **current** relationship with your organisation by determining the recency, frequency and monetary value of the purchases they make with your business.   This in turn drives improved segmentation, allowing organisations to assign messages, promotions and offers according to the buying style of the customer that you are communicating with  - at scale.

So how does RFM analysis work? RFM analysis allows you to assign a score to every record in your customer database, either at a point in time or continuously in a 'live' capacity, depending on how you wish to monitor scores.

Scores are determined on the following specific customer activities:

Recency (R)  – period since last purchase
Frequency (F)  – number of transactions
Monetary (M)  – total money spent with your organisation, often called Customer Lifetime Value (CLV or CLTV)

These scores can then be grouped and treated in like-styled ways.

Why use RFM analysis?  Knowing a person's RFM score means that you can assign communications or automation capabilities appropriate to their relationship with you.  RFM could, for example, support you in identifying a 'VIP' segment that you may wish to treat differently to a lower-value customer segment.  In this case RFM could support channel selection for differing audiences, or sharing exclusive invites ahead of wider customer launch to specific audience selections.

In today's climate, consumers' are being hit with rising costs on every front – talking to customers' in a way that is more appropriate to their spending patterns is surely both a more sensitive and common sense approach.  Not least because organisations can seek to keep customers engaged on their terms, but also because you can make marketing decisions based on a customer's likelihood to convert to a goal - for example, don't send expensive print catalogues to low value customers'.

Monitoring how scores change over time is also a particularly compelling aspect of measuring RFM as it indicates the health of your customer database and the trends experienced by your organisation over the course of the lifecycle of your customers'; as well as identifying if your marketing activities are working to move customers' in the right direction.  Organisation's that operate a House of Brands approach can find it very useful to see and apply marketing strategies across their portfolios in order to ensure appropriate up, or cross, sell initiatives.

To learn in detail about how to assign scores to your customer database, download the eBook from Hive Marketing: "What is RFM analysis, and how marketers can use it to their advantage" at https://rfmformarketing.com/