Development of a Scalable Customer Behavior Analytics Platform for FMCG Sector

The client operates within the demanding AdTech industry, facing challenges such as a legacy data infrastructure that doesn't meet growing analytical requirements, dependencies that hinder onboarding new clients, non-scalable data collection processes based on periodic heavy tasks, and insufficient documentation. These issues limit their ability to deliver timely, personalized content and scale their analytics operations.

A mid-sized FMCG company seeking to optimize customer engagement through advanced data analytics and personalized content delivery.

• Develop a flexible and high-performance data aggregation system utilizing a modern database solution to handle large volumes of customer behavior data.
• Refactor existing microservices to improve scalability and modularity, enabling faster data processing and analysis.
• Implement comprehensive integrations with third-party advertising and marketing tools to enrich data sources.
• Establish a development process that ensures rapid, high-quality software delivery with clear documentation and specification standards.

• A flexible data aggregation engine built on scalable NoSQL technology to replace the current heavy, periodic data gathering processes.
• Real-time data processing and microservices refactoring to increase scalability and responsiveness.
• Third-party API integrations to enhance data collection and synchronization with marketing and advertising systems.
• User interfaces for data visualization and reporting to facilitate actionable insights.

• Advertising and marketing platforms for data enrichment
• Third-party analytics tools for comprehensive customer insights

• High scalability to handle increasing data volumes with minimal latency
• Performance optimization for real-time data processing
• Robust security measures to protect sensitive customer data
• Clear documentation and specifications to facilitate ongoing development and maintenance

The new analytics platform aims to significantly improve data processing scalability, enabling real-time customer behavior insights. This is expected to facilitate more effective personalized content delivery, increase marketing conversion rates, and streamline onboarding of new clients. Additionally, the refactored microservices and enhanced data aggregation capabilities will reduce operational bottlenecks, supporting sustainable growth in a competitive AdTech environment.