SegMind AI

Intelligent Customer Segmentation & RFM Analytics Platform

SegMind AI is an AI-powered customer segmentation and RFM (Recency, Frequency, Monetary) analytics platform that helps businesses identify, understand, and target their customers more effectively.
Built on Azure Machine Learning, Azure Databricks, and Microsoft Fabric, it automates the process of data extraction, customer scoring, clustering, and persona creation, enabling personalized marketing, churn prediction, and profitability optimization.

Orchestration

Azure Data Factory

Data ingestion and scheduling

Transformation

Azure Databricks (PySpark, Pandas)

RFM scoring, clustering, data prep

Modeling

Azure ML / Databricks MLlib

Segmentation models (K-Means, Hierarchical, DBSCAN)

Storage

Microsoft Fabric / SQL Database

Stores scored customers and segments

Analytics

Power BI / Fabric Reports

Visualization, trend tracking, churn analysis

Automation

Logic Apps / Synapse Pipelines

Campaign triggers, alerts, workflow automation

Business Benefits

Precision Targeting - Enables hyper-personalized campaigns for each segment

Automation - Reduces manual analytics and marketing segmentation

Customer Intelligence - Provides 360° view of customer behavior and loyalty

Increased ROI - Higher engagement and conversion through targeted actions

AI-Driven Learning - Continuous model improvement based on customer patterns

Secure & Scalable - Built on Azure-native, enterprise-grade infrastructure

Recency-Based Questions

1.Who are our most loyal customers?

2.Who are the customers that haven’t purchased recently?

3.What percentage of customers haven’t purchased in the last X days?

4.Are customers who purchased recently spending more?

5.How often do high-revenue customers return?

Frequency-Based Questions

1. Who are our most frequent buyers?

2. What percentage of customers have made only one purchase?

3. How many customers have made purchases more than X times?

4. Which customers buy frequently but spend less per transaction?

5. Do customers with high frequency scores purchase specific products?

Monetary-Based Questions

1.Who are our highest-spending customers?

2.How many customers contribute to the top 80% of our revenue?

3.What is the average monetary value per customer?

4.Are high-spending customers also frequent buyers?

5.Which customers are spending less over time?

Churn & Retention Analysis

1.Which customers are at risk of churning?

2.What is the average time before a customer churns?

3.How many customers have decreased their purchase frequency?

4.What RFM segments have the highest churn risk?

5.How effective are our retention campaigns on different RFM segments?