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.
|Champions||Bought most recently, most often and spend the most||No price incentives. New products and loyal programs instead|
|Loyal Customers||Buy most frequently||R and M could be used to further segment and understand marketing strategies|
|New Customers||Customer bought recently, but are not frequent buyers||Run campaigns that focus on loyalty, like for example membership deals/benefits etc.|
|Potential Loyalist||Recently made a couple of purchase at above average frequency||Run campaigns that focus on loyalty, like for example membership deals/benefits etc.|
|Can’t Lose them||Made frequent and big purchase in the past, but it has been a while since the last purchase||Reactivation Campaigns|
|Needs Attention||Purchased recently but and have not made previous frequent purchases||Aggressive price incentives|
|At Risk||Haven’t purchased for a while, used to purchase frequently with decent spend||Aggressive price incentives and reactivation campaigns|
|Hibernating||Made small purchases frequently but a long time since last purchase||Don’t spend to much on marketing|
|Lost Customers||Stopped buying, used to purchase below average on frequency, but spend good money||M could be used to further segment and find the once that should be targeted for re-acquiring|
|Lost Cheap Customers||Last purchase long ago, purchased little, didn’t spend a lot||Don’t spend a lot re-acquiring business|
For more information regarding the RFM analysis, please visit the blog. Link to blog