Development of a Proprietary AdTech Stack for a Streaming Media Platform to Enhance Data Control and Monetization

The client, a leading OTT streaming service, currently relies on third-party advertising platforms, limiting their control over ad operations, data privacy, and monetization strategies. Privacy regulations and industry shifts demand a proprietary AdTech solution that consolidates campaign management, ad serving, and audience data, enabling the client to create a self-contained walled garden ecosystem for better revenue control and data ownership.

A large streaming media provider operating a video-on-demand service seeking to build an in-house advertising technology infrastructure to regain control over their data and revenue streams.

• Design and develop a comprehensive in-house AdTech stack including an ad server, self-serve ad platform, data lake, and customer data platform (CDP).
• Replace reliance on third-party ad-serving and campaign management tools to ensure full data control, privacy compliance, and monetization flexibility.
• Enable targeted advertising through integrated audience segmentation and real-time campaign optimization capabilities.
• Create a scalable, secure, and flexible architecture capable of handling varying volumes of data and user interactions.
• Facilitate integration with existing content management, analytics, and external data sources to enhance audience targeting and measurement.

• A self-serve ad platform with campaign creation, creatives upload, ad targeting setup, and campaign monitoring capabilities.
• An ad server supporting video (via standardized protocols such as VAST 4.2) and image ad delivery within the streaming platform.
• A data lake integrating data from the streaming platform, analytics tools, subscription databases, and third-party sources; capable of organizing, cleaning, and schema management.
• A customer data platform that retrieves audience data from the data lake, creates audience segments, and exports this data to the ad server for targeted ad delivery.
• SDKs and integrations enabling ad targeting and audience identification via identifiers such as bloom filters, with support for real-time bid responses.

• Existing content management system (CMS) for content metadata
• Analytics platforms for event and user behavior data
• External data sources for interest-based audience segments
• Machine learning and data analysis tools for data science initiatives
• Payment systems for billing management

• System scalability to handle increasing data volume and user activity
• High performance with low latency for real-time ad targeting and campaign updates
• Security and privacy compliance, including adherence to relevant regulations
• System availability and reliability with minimized downtime
• Maintainability and ease of updates through modular architecture and CI/CD

Implementing the in-house AdTech stack is expected to enable the client to achieve complete ownership of their ad operations, reduce dependence on third-party vendors, and optimize ad revenue streams. It aims to improve targeted advertising efficiency, allowing for more personalized campaigns, and facilitate compliance with evolving privacy standards. The platform will support scalable growth and provide detailed data insights, ultimately enhancing monetization potential and user engagement.