Then, within each of them, we give users points (. from to or from to ), for example, for the Recency dimension a person who made a purchase in our online store in the last week will receive points from us a person who has made a purchase from us in the last months will receive points a person who has made a purchase from us in more than months will receive point The scoring within the dimension and the weighting of individual dimensions should be well thought out and always consider and assign bas on the industry, consumer trends, good knowlge of the products and services offer, or even the market situation.
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Ultimately, the RFM value will be higher the less time has elaps since the last purchase, the more often a given user makes purchases with us, and the higher the value of revenue resulting from that user’s conversion is for us. What does such a division look like in practice and what activation methods can be appli to particular customer database groups? Bas on the analysis, customers can be initially divid due to low RFM average RFM high RFM The group of customers with low RFM are those who are not particularly interest in our brand and are not attach to it in any way.
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These can be customers who have made a onetime purchase or who make them incidentally. It is characteristic for this consumer group to buy when the price of the products offer by the store is appropriately low or lowest compar to the competition. This group reacts slowly and poorly to marketing and promotional campaigns and is the most difficult to loyalize and activate. a bargain or price customer. The activation of this group consists in communicating all kinds of promotions, price deals and bestsellers at the lowest prices compar to the competition.