Development of a Scalable Data Analytics Platform for AdTech Performance Insights

The client faces difficulties in consuming, transforming, and preaggregating massive data streams for effective analysis. Traditional tools limit real-time analytics, hinder hypothesis testing, and impede rapid decision-making. Additionally, there is a need for robust creative auditing and geolocation data exploration to optimize marketing efforts and ensure brand safety.

A large-scale digital advertising agency seeking to enhance campaign performance analysis, audience segmentation, and real-time reporting through advanced data infrastructure.

• Implement a data processing infrastructure capable of handling and transforming large-scale streaming data efficiently.
• Enable real-time analytics and interactive dashboards to monitor campaign performance, audience engagement, and market trends.
• Develop models for accurate multi-channel attribution to evaluate the effectiveness of advertising touchpoints.
• Create ad hoc reporting capabilities with rapid response times through preaggregated data streams.
• Build a creative audit tool for dynamic creative analysis, sandboxing, and malicious behavior detection.
• Design toolsets for geolocation and bidstream data analysis to support hypothesis generation and validation.
• Establish data orchestration infrastructure for automatic data-driven actions, reducing reliance on third-party tools.

• Large-scale data ingestion and transformation engine for streaming data.
• Real-time dashboards providing insights into campaign metrics, audience behavior, and industry trends.
• Attribution modeling tools to evaluate multi-channel campaign interactions.
• Preaggregated data layers supporting rapid ad hoc query execution.
• An internal creative analysis sandbox for dynamic creative unpacking and malicious behavior detection.
• Tools for geolocation and bidstream data exploration for hypothesis testing.
• Automated data orchestration system to trigger actions based on data insights.

• Third-party data sources for bidstream and geolocation data.
• Internal data warehouses or lakes for data storage and retrieval.
• Real-time alerting and monitoring systems.

• System scalability to handle increasing data volumes and user load.
• High availability with 99.9% uptime and automated monitoring.
• Data security and compliance, especially around user privacy and sensitive data.
• Response times for ad hoc queries under 2 seconds with preaggregated data.
• Robust fault tolerance and disaster recovery mechanisms.

The implementation aims to significantly improve data processing efficiency, enabling real-time insights and hypothesis testing. Expected outcomes include faster decision-making, improved campaign performance attribution, enhanced creative review processes, and more actionable audience segmentation. Ultimately, this will lead to increased campaign ROI and stronger market positioning.