Fashion Customer Intelligence Engine

Overview
KPI & RFM
Churn Analysis
Sentiment Analysis
Predictive Analysis
Architecture Diagram

Inspiration

This project is designed as a Tableau-powered analytics solution that integrates customer behaviour, real-world fashion product data, and predictive insights into business workflows using modern data platforms. The goal is to help fashion and luxury brands move from static reporting to actionable, real-time decision-making.

What It Does

By combining Tableau Cloud analytics, Slack notifications, and CRM-ready insights, this solution transforms data into actionable intelligence—helping fashion and luxury brands reduce customer churn, improve lifetime value, and optimise product and merchandising strategy.

How I Build It

1. Data Ingestion & APIs Product-level data, customer transactions, and sentiment signals are ingested using Python-based data pipelines and simulated API connections. These APIs represent real-world integrations such as: 1. E-commerce platforms (Farfetch / Net-a-Porter–like systems). 2. Review and sentiment sources. 3. Trend signals (search interest & seasonal demand). The processed datasets are published to Tableau Cloud for scalable analytics.

2. Tableau Cloud Analytics Layer Tableau Cloud serves as the core analytics engine where: 1. Customer churn risk is calculated. 2. Predictive trends are visualised. 3. Fashion category performance is analysed. 4. Business-ready insights are surfaced through storytelling dashboards. Dashboards are designed in a slide-style format, enabling non-technical users to quickly understand risks, opportunities, and next actions.

3. Slack Integration To enable real-time decision-making, key insights from Tableau trigger alerts to Slack, such as: 1. High churn risk detected in key customer segments. 2. Negative sentiment spikes for specific fashion categories. 3. Revenue at risk crossing predefined thresholds. This allows marketing, CRM, and merchandising teams to respond immediately without manually monitoring dashboards.

4. Salesforce CRM (Conceptual Integration) The solution is designed to integrate with Salesforce CRM, where Tableau dashboards can be embedded directly into workflows. Churn risk scores and predictive insights can be used to: 1. Prioritise customer re-engagement. 2. Trigger retention campaigns. 3. Support data-driven merchandising decisions.

By leveraging the Tableau platform’s extensibility, this solution demonstrates how analytics can seamlessly connect insights to action across collaboration and CRM tools.