Strategies for Expanding User Circles and Content Matching in Short‑Video Platforms

The piece begins by highlighting the difficulty of expanding user circles for platforms like TikTok, Douyin, and Kuaishou, emphasizing the need for careful exploration, strategic penetration, and tactical measures such as celebrity collaborations and exclusive content to attract new users.

It then outlines a data‑centric approach, first gathering external trend signals from global hot lists, LBS rankings, and query analysis, and building a competitive radar that maps rival content to identify gaps and opportunities.

Next, it discusses circle planning: segmenting users by content supply versus demand, evaluating KOL availability, and deciding whether to focus on content mining, KOL introduction, or a balanced strategy to gradually grow new‑circle engagement.

The article stresses the importance of precise matching between newly identified content and target users, using text and image similarity, crawling techniques, and historical content mining to ensure relevance and fairness in distribution.

It further describes a full‑process impact model that integrates data‑driven user acquisition, cost‑benefit analysis, and algorithmic tagging to connect users with appropriate content, followed by retention tactics such as targeted push, old‑user recall, and continuous metric monitoring.

Key pitfalls are highlighted, including the risk of alienating existing users while chasing new ones, the necessity of granular content segmentation, and the need for robust A/B testing and multi‑dimensional evaluation of recommendation, algorithm, and business metrics.

Finally, the article concludes that successful circle expansion requires a systematic, iterative framework combining data, algorithms, product experiments, and content creator engagement, turning the multi‑sided platform into a smart, responsive growth engine.