Intelligent Advertising Delivery System and Techniques: From Budget‑Constrained Bidding to Multi‑Channel Optimization

The presentation begins with an overview of the online advertising ecosystem, describing the three key participants—advertisers, media platforms, and users—and the challenges advertisers face in maximizing marketing effectiveness under complex traffic and pricing environments.

It then traces the historical evolution of Alibaba's ad‑tech stack: from simple CPM/CPC pricing to value‑aware OCPM/OCPC, the introduction of budget‑constrained bidding (BCB) that automatically allocates spend under a fixed budget, and multi‑constraint bidding (MCB) which additionally enforces cost limits such as CPC caps.

Advanced sequence bidding (MSBCB) is presented to capture long‑term user value by planning multiple exposures, using reinforcement learning and reward‑shaping techniques to balance short‑term gains against long‑term conversion potential.

The multi‑channel smart bidding (CCSA) framework is described, showing how a unified minimal interface distributes advertiser budgets across search, recommendation, and brand channels, while each channel applies its own BCB/MCB or sequence‑bidding algorithms to achieve global optimality.

Experimental results demonstrate that the proposed reinforcement‑learning‑based methods outperform traditional linear or heuristic baselines, delivering up to 10% improvements in ROI and GMV in production. The talk concludes with a roadmap for further research in data intelligence, mechanism design, algorithmic upgrades, and product iteration.