OPPO’s Multi‑Scene Unified Modeling and Intelligent Power System for Application Distribution

In the current industry climate, cost reduction and efficiency are essential, but preserving user value is equally critical; OPPO’s Internet Application R&D Platform and Search Algorithm Department, led by Lai Hongke, addresses this tension through sophisticated recommendation technology.

OPPO’s app distribution faces a vast scenario span—from finance to gaming—resulting in highly sparse interaction data and long conversion chains. To overcome data sparsity, OPPO implements a full‑scene unified modeling approach that shares global features across the software store, game center, and other distribution channels, expanding its KV store from 2 TB to 30 TB and increasing feature count from 100 million to over 10 billion.

The unified model leverages a Multi‑Gate Mixture‑of‑Experts (MMOE) architecture, allowing shallow and deep conversion targets to share embeddings, dramatically reducing the number of CVR models while improving conversion rates. This framework also supports the oCPX capability, which lets advertisers set explicit optimization goals (e.g., download, registration, payment) and automatically bids based on predicted conversion probabilities.

On the infrastructure side, OPPO builds an intelligent power system that dynamically throttles traffic, prioritizes high‑value users, and applies tiered resource allocation (V1.0 → V3.0). These optimizations raise traffic support by up to 20 % and revenue by a similar margin without sacrificing user experience.

Overall, OPPO demonstrates that integrating advanced AI‑driven recommendation models with robust engineering and data‑sharing architectures can simultaneously achieve cost reduction and value creation in large‑scale mobile app distribution.