A01 chaf6542 06 se fm indd

Recency, Frequency, Monetary value (RFM) analysis

RFM is sometimes known as ‘FRAC’, which stands for: Frequency, Recency, Amount (obvi-

ously equivalent to monetary value), Category (types of product purchased – not included 

within RFM). We will now give an overview of how RFM approaches can be applied, with 

special reference to online marketing. We will also look at the related concepts of latency and 

hurdle rates.

Recency

This is the recency of customer action, e.g. purchase, site visit, account access, email 

response, e.g. 3 months ago. Novo (2004) stresses the importance of recency when he says:

Recency, or the number of days that have gone by since a customer completed an action 

(purchase, log-in, download, etc.) is the most powerful predictor of the customer repeat-

ing an action . . . Recency is why you receive another catalogue from the company shortly 

after you make your first purchase from them.

Online applications of analysis of recency include: monitoring through time to identify vul-

nerable customers and scoring customers to preferentially target more responsive customers 

for cost savings.

Frequency

Frequency is the number of times an action is completed in the period of a customer 

action, e.g. purchase, visit, email response, e.g. five purchases per year, five visits per month, 

five  log-  ins per week, five email opens per month, five email clicks per year. Online applica-

tions of this analysis include combining with recency for RF targeting.

Monetary value

The monetary value of purchase(s) can be measured in different ways, e.g. average order 

value of £50, total annual purchase value of £5,000. Generally, customers with higher monet-

ary values tend to have a higher loyalty and potential future value since they have purchased 

more items historically. One example application would be to exclude these customers from 

special promotions if their RF scores suggested they were actively purchasing. Frequency is 

often a proxy for monetary value per year since the more products purchased, the higher the 

overall monetary value. It is possible then to simplify analysis by just using recency and fre-

quency. Monetary value can also skew the analysis for  high-  value initial purchases.

Latency

Latency is related to frequency, being the average time between customer events in the cus-

tomer life cycle. Examples include the average time between website visits, second and third 

purchase and email clickthroughs. Online applications of latency include putting in place 

triggers that alert companies to customer behaviour outside the norm, for example increased 

interest or disinterest, then managing this behaviour using e-communications or traditional 

communications. For example, a B2B or B2C organisation with a long interval between 

purchases would find that if the average latency decreased for a particular customer, then 

they may be investigating an additional purchase (their recency and frequency would likely 

increase also). Emails, phone calls or direct mail could then be used to target this person with 

relevant offers according to what they were searching for.

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