Start with Data, end with Value, How RFM and K-means improve Our Marketing Strategy.

Marketing can be a complex and challenging task, especially when it comes to delivering the right message to the right audience at the right time and through the right channel.

To address this issue, we took on a project that utilized Salesforce data to identify customers with won opportunities. We then analyzed their behavior using the RFM Model (Recency, Frequency, and Monetary Value) and an unsupervised classification algorithm called K-means Clustering to segment them into distinct groups.

By doing so, we were able to determine which message would be most effective for each group and deliver it through the appropriate channel at the optimal time.

We did not have to determine the optimal number of clusters as it was already defined by the number of campaigns the marketing team needed to deploy. This approach enabled us to create a more targeted and effective marketing strategy that increased customer engagem

ent and ultimately drove revenue growth.