The RFM - Analysis is a powerful tool to be utilized in order to segment your customers. Each segment represent a group of customers with the same characteristics when it comes to recency (time since last purchase), frequency (how often they come back to buy), monetary value (the money spent on each purchase). 


The number of segment displayed in Engage is dependent on your customer data. This means that Engage will calculate the maximum number of segment to be used and still keep all of them significantly different. 

The segment are intended to be used in marketing activities and below table can be utilized as a starting point.


SegmentDescriptionMarketing
ChampionsBought most recently, most often and spend the mostNo price incentives. New products and loyal programs instead
Loyal CustomersBuy most frequentlyR and M could be used to further segment and understand marketing strategies
New CustomersCustomer bought recently, but are not frequent buyers
Run campaigns that focus on loyalty, like for example membership deals/benefits etc.
Potential LoyalistRecently made a couple of purchase at above average frequencyRun campaigns that focus on loyalty, like for example membership deals/benefits etc.
Can’t Lose themMade frequent and big purchase in the past, but it has been a while since the last purchaseReactivation Campaigns
Needs AttentionPurchased recently but and have not made previous frequent purchasesAggressive price incentives
At RiskHaven’t purchased for a while, used to purchase frequently with decent spendAggressive price incentives and reactivation campaigns
HibernatingMade small purchases frequently but a long time since last purchaseDon’t spend to much on marketing
Lost CustomersStopped buying, used to purchase below average on frequency, but spend good moneyM could be used to further segment and find the once that should be targeted for re-acquiring
Lost Cheap CustomersLast purchase long ago, purchased little, didn’t spend a lotDon’t spend a lot re-acquiring business


For more information regarding the RFM analysis, please visit the blog. Link to blog