Retail Data Management
A data analytics and reporting system that turns purchase history into sales and marketing intelligence for retail operations.
Software Type
Data Analytics & Reporting System
Industry
Retail
Year
©2022
About
Project Overview
A retail enterprise specializing in consumer goods, operating through both physical stores and an online platform. The company sought to analyze customer behavior and optimize sales strategies by leveraging historical purchase data.
Needs & Challenges
The client had accumulated a large volume of customer purchase history data but lacked the proper tools or platform to analyze it effectively. They aimed to uncover shopping trends, customer behavior patterns, and product consumption models to enhance their marketing and sales strategies.
Our solutions
Rabiloo delivered a powerful data analytics and reporting system that enabled the client to extract actionable insights from their large datasets. By leveraging AWS Redshift as a data warehouse, the platform efficiently handled high data volumes and supported complex queries. The system provided detailed reports and predictive analytics on customer behavior, consumption trends, and product strategies, empowering the client to make informed business decisions.
Technology stack
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Development Model: Hybrid (combination of on-premise and cloud deployment)
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Testing Method: Manual testing
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Task Management Tool: Slack (for team communication and task tracking)
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Key Challenge: Big data processing and storage via AWS Redshift
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Programming Languages: Java 8, Spring Boot 2 (backend), VueJS (frontend)
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Data Warehousing System: AWS Redshift (for storing and processing large volumes of transactional data)
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Cloud Infrastructure: AWS EC2, RDS, S3, Lambda, EventBridge, CloudWatch
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DevOps & CI/CD Tools: Docker, GitLab CI
Main functions
1. For Business Users (Analysts & Sales Managers):
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Customer Behavior Analysis: Easily analyze purchase history to identify customer trends, preferences, and buying patterns.
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Statistical Reporting: Generate detailed reports on product sales, revenue, and other key performance indicators.
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Demand Forecasting: Use data insights to predict product demand and optimize inventory and marketing strategies.
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Data Visualization: Intuitive charts and dashboards enable faster understanding and better decision-making.
2. For Administrators:
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Data Management: Integrate and manage data from multiple systems efficiently using AWS Redshift as a centralized data warehouse.
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User Access Control: Manage user roles and permissions for analysts and managers to access reports and analytical tools.
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Performance Optimization: Ensure high-speed processing and smooth handling of large-scale datasets, including billions of records.
Outcomes
Driving revenue growth through data-driven customer insights
In-depth analysis of customer behavior enables the company to better understand customer needs and preferences, thereby optimizing marketing strategies and driving revenue growth. The solution delivers value through:
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Data-driven decision making: Analytical reports help identify which products to focus on, which to phase out, and how to adjust sales strategies for greater effectiveness.
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Inventory management & demand forecasting: Based on historical purchasing patterns, the system helps predict product demand, optimize stock levels, and minimize out-of-stock situations.
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Enhanced customer experience: By understanding customer habits and preferences, the business can offer personalized services, products, and promotions—boosting customer satisfaction and retention.
