Precise Marketing Algorithm and Practice in HaLao
HaLao’s precise marketing system combines Pu‑Learning lookalike models, graph‑embedding user similarity analysis, and TSA/EM optimization within a robust feature‑engineering and deployment framework, delivering over 20% ROI gains and 3‑10× user growth while addressing low‑ROI and targeting inefficiencies.
This content discusses HaLao's precise marketing strategies, focusing on algorithmic implementations and technical frameworks. It covers business background, marketing scenarios, and pain points in precision marketing, including challenges like low ROI and inefficient audience targeting. The technical aspects include Pu-Learning frameworks for lookalike modeling, Graph Embedding techniques for user similarity analysis, and optimization methods like TSA and EM models. Future directions involve expanding graph construction and intelligent budget allocation thresholds.
The presentation details technical components such as feature engineering (offline/real-time), algorithm modules (lookalike modeling, intelligent allocation), and deployment infrastructure (data platforms, vector engines). Business outcomes highlight 20%+ ROI improvements and 3-10x user base expansion through algorithmic optimizations.
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