RFM analysis allows you to determine who your best customers are based on an analysis of their purchases: the frequency and recency, when their last purchase was made, and the amount they spend.
Thus, RFM analysis helps establish strategies to increase customer satisfaction and turn them into regular customers to boost e-commerce revenue.
We’ll show you how to perform RFM analysis and establish these strategies.
RFM analysis is a segmentation model that identifies the best customers based on their spending habits. It’s a customer segmentation technique that helps increase e-commerce sales.
It’s a classification to better understand the value of different segments of a brand’s customer base based on their behavior. The more you know about your customers, the better you can tailor your strategies to their needs and preferences.
Therefore, it’s about
using customer data to develop strategies that encourage recurring purchases and increase the spending per purchase. These strategies aim to provide customers with what they need at any given time. Thanks to this personalized treatment, customers will not have the need or temptation to switch to another brand.
RFM stands for
Recency, Frequency, Monetary (recency, frequency, and monetary value).
The RFM model analyzes three concepts, which are numerically ranked on a scale of 1 to 5. Higher numbers indicate better results. Thus, the best customers are those who score the highest based on the following criteria:
This way, a scale is established, and customers contributing the most value are identified.
The main objective of using the RFM model is to increase revenue, but it also offers other benefits:
RFM analysis facilitates customer segmentation based on their value. This allows you to create specific campaigns for different segments and tailor your messages accordingly.
Because a customer who has made a single purchase has different needs than a repeat customer. The brand needs to remind the former that it exists and encourage another purchase, while for the latter, the brand can establish a promotion system, for example.
Through this customer segmentation, marketing departments can compare the benefit of a new customer to that of an existing one. This helps in budget allocation and sales strategies.
RFM analysis allows you to obtain data related to how users navigate through the e-commerce platform and understand metrics such as the site’s churn rate. This helps brands develop retention strategies.
Segmenting customers based on their characteristics makes it easier to create specific campaigns tailored to each type of customer, satisfying their individual needs.
Having customer information and segmenting them by type will result in improvements that translate into an increased conversion rate.
RFM analysis is simpler than other methods, making it easier to integrate into promotions and other marketing initiatives.
We’ve seen how important it is to get to know your customers and understand their behavior.
This is the key to developing effective strategies and actions, adapting messages according to the customer’s stage in the buying process.
Because a customer visiting an e-commerce platform for the first time has different needs, wants, or desires than a repeat customer.
How can you gain this understanding of your customers?
At We are testers, we can assist you with some of our tools:
The Archetype Test helps you identify sociodemographic and behavioral patterns among your customers to create different segments based on their common characteristics and patterns.
With the Segmentation Study, you can identify behavior patterns among your customers and group profiles based on common characteristics. It also helps you understand their purchase motivations and obstacles during the buying process.
A Satisfaction Study allows you to collect customer feedback and evaluate their satisfaction levels, ultimately improving the shopping experience.
Do you want to learn more and find out exactly how we can assist you with your specific case? Get in touch with our team, and we can develop a research project tailored to your needs.
Update date 15 April, 2024
