This article examines the chronic pain points of traditional marketing, explains how AI‑driven multi‑agent collaboration can create a data‑rich, automated, and continuously optimized marketing loop, and presents a real‑world case study with measurable performance gains and practical implementation guidelines.
This article presents a comprehensive technical analysis of using large language models to build a task‑oriented multi‑turn dialogue system for intelligent marketing, detailing architecture, intent detection, slot extraction, prompt design, dialogue management, practical experience, and future research directions.
This article details Haola's end‑to‑end algorithmic ecosystem for its ride‑sharing service, covering the machine‑learning platform built on Hadoop/YARN, the architecture and evolution of the matching recommendation engine, transaction‑ecosystem governance models, and intelligent marketing strategies including uplift modeling and optimization.
The talk explains uplift modeling for intelligent marketing, showing how causal lift predictions—derived from randomized experiments using two‑model, one‑model, or tree‑based methods—identify truly responsive users, evaluate performance with AUUC/Qini, and were applied to Taopiaopiao’s coupon allocation via knapsack optimization, highlighting challenges and future directions.
Didi’s Xiaoju Car Service leverages a reinforcement‑learning framework with Double DQN and graph‑embedding‑based personalization across its traffic‑distribution, tagging, portrait, targeting, strategy, and reach‑optimization modules, replacing manual rule‑based marketing, and achieves roughly 8 % new‑user lift, 50 % cost reduction, and significant gains in open and conversion rates.
This article describes how Didi Ride‑Sharing leverages reinforcement learning and graph‑embedding techniques to model and optimize user‑operation marketing, detailing system architecture, algorithm design, experimental ROI improvements, and personalized message delivery for enhanced conversion and cost efficiency.
