Research Paper

Core Innovation

This paper proposes NextAds, a generation-based paradigm that replaces retrieval-based personalized video advertising with AI-driven creative generation and integration. It introduces two representative tasks and benchmarks, demonstrating feasibility of end-to-end pipelines that dynamically generate personalized video ads, enabling continuous refinement from user feedback.

Why It Matters

Personalized video ads currently rely on limited, static creative inventories that fail to adapt to diverse users and contexts, reducing effectiveness. NextAds enables continuous, real-time generation of tailored creatives, improving user engagement and advertiser ROI. This scalable approach transforms digital advertising workflows by integrating generative AI for ongoing optimization.

Potential Customers & Pain Points

• Digital advertisers – Limited personalization reduces ad impact
• Video platforms – Need scalable dynamic ad creative solutions
• Ad agencies – Restricted by static creative inventories
• Brands – Desire higher engagement through tailored ads

Business Model

Subscription and usage-based pricing for access to the AI-powered video ad generation platform, with tiered plans for advertisers and agencies based on volume and customization features.

Competitive Landscape

• Google Ads
• Facebook Ads
• The Trade Desk
• Innovid
• VidMob

Implementation Challenges

• High complexity in real-time video generation and integration
• Ensuring creative quality and brand safety in AI-generated ads
• Adoption resistance from advertisers used to traditional workflows
• Data privacy and user consent challenges for personalization

Validation Strategy

• Pilot deployments with digital advertisers to measure engagement uplift
• A/B testing comparing AI-generated creatives versus traditional ads
• Collecting user feedback and performance data to refine generation models
• Partnerships with video platforms to integrate and scale the solution