Discovery Phase
The goal was to develop a comprehensive end-to-end data analytics solution tailored for the retail industry. The solution is designed to seamlessly integrate data from a wide range of retail sources, including CRM systems, ERP platforms, traditional RDBMS databases like MySQL, and unstructured data formats.
Business Requirement
To empower retail enterprises to leverage their data effectively, driving informed decisions and optimizing business processes for better customer engagement and operational efficiency.
Functional Requirements
Advanced analytics features powered by AI and machine learning, such as:
Sentiment analysis
Product recommendation engines
A scalable data lake to handle structured, semi-structured, and unstructured data.
Technical Requirements
Ingestion of data from various sources, including:
Customer Relationship Management (CRM) Systems
Enterprise Resource Planning (ERP) Systems
Product Inventory Data
Product Batch Data
Point of Sale (POS) Systems
E-commerce Platforms
Social Media
Campaign System
Product and Order Survey
Product Catalog
Purchase Order Detail
Order Detail
Sales Data
Web Application
Mobile Application
Customer Loyalty System
Success Criteria
Deliver advanced analytics capabilities across the following retail domains:
Customer Analytics
Customer Segmentation
Customer Lifetime Value (CLV) Prediction
Churn Prediction
Customer Sentiment Analysis
Product and Marketing Analytics
Product Recommendation Systems
Market Basket Analysis
Campaign Effectiveness Analysis
Sales and Inventory Analytics
RFM (Recency, Frequency, Monetary)Analysis
Sales Forecasting
Inventory Optimization
Price Optimization
Demand Forecasting
Operational Analytics
Supply Chain Optimization
Fraud Detection (optional)
Workforce Management (optional)
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