In e-commerce retail, we encounter challenges in “customer classification” on a daily basis. With consumers being diverse in their needs and behaviors, treating each customer in a completely standardized manner as a seller will not effectively achieve growth objectives.
Here, it’s essential to mention a model test Oceanwing is conducting – the “AMC-RFM Model”. The RFM Model holds a very important place in identifying high-value and high-potential customers.
– What is “AMC-RFM Model”?
Recency, frequency, monetary value (RFM) is a model used in marketing analysis that segments a company’s consumer base by their purchasing patterns or habits. It is part of Amazon Marketing Cloud (AMC) analysis. In particular, it evaluates customers’ recency (how long ago they made a purchase), frequency (how often they make purchases), and monetary value (how much money they spend). RFM is then used to identify a company’s or an organization’s best customers by measuring and analyzing spending habits to improve low-scoring customers and maintain high-scoring ones.
– What we are doing?
Our team is conducting a study on a client brand to analyze the consumer behavior of its users. This research will enable us to better understand the needs and preferences of customers, allowing us to offer products or services more effectively. Additionally, this approach can enhance customer satisfaction and increase customer loyalty, thereby boosting sales and profits. It also allows for the identification of high-value customers and potential loyal customers, enabling us to take measures to increase their loyalty, such as offering special discounts and personalized recommendations.
The current AMC-RFM application testing is continuously being optimized. We monitor the effectiveness of the RFM model bi-weekly to ensure its ongoing efficacy. Additionally, we track customer behaviors and trends within segments, adjust thresholds, and revise strategies accordingly.
Overall, we are excited about this test and will deliver findings in December!