Recency
They looked at how recent customer interactions were to measure engagement.
Customer Segmentation Model
Advanced Analytics
Customer Segmentation
See how our team's new way of sorting customers increased a client's marketing plan. With a huge customer database to manage, the client needed a clear, practical method to split and reach different groups.
The Story
The Client
A company was having trouble with market segmentation. They wanted to improve their large customer database to better target their marketing.
The Challenge
They needed a solid system to group customers by different demographic and economic details, so they could target their marketing better and improve customer relationships.
The Solution
The RFM (Recency, Frequency, Monetary value) Segmentation Model is a tool used to analyse customer buying habits and group them into clear categories.
Our team used SQL to pull data and mixed clustering methods (DB scan, Agglomerative clustering, and K-means) with Ensemble learning. This helped us build an algorithm that groups customers based on their financial and demographic details.
The path through market segmentation models was full of challenges. Still, combining expert knowledge with fresh ideas led to a new framework. The RFM-based Customer Segmentation Model turned out to be a useful tool. It helped the client find valuable customer groups for more focused marketing.
What it can do
Why This Matters
This case study highlights the impact of data-driven segmentation on formulating precise marketing strategies. If you’re aiming to refine your customer engagement or overhaul your marketing tactics, our expertise in AI and analytics stands ready to guide you to exceptional outcomes.