Data Analytics Framework for Optimizing Web3 Campaign Strategies: Integrating Contract Risk, Gas Economics and User Behavior
Từ khóa:
Web3 analytics, smart contract security, gas price forecasting, Sybil detection, user retentionTóm tắt
The explosion of Web3 applications necessitates effective user acquisition strategies; however, current execution often suffers from network congestion, security vulnerabilities and low retention. This paper presents a comprehensive Data Analytics Framework to optimize Web3 strategies by integrating three critical dimensions: contract risk, gas economics and user behavior. The methodology employs a multi-pillar approach: utilizing static analysis with dependency graphs for risk quantification, applying ARIMA forecasting for low-cost windows and leveraging DBSCAN clustering with cohort analysis for user assessment. Empirical results on the Ethereum network validated the target contract's low risk profile (0.20) but revealed a critical 10-hour divergence between the optimal cost window (09:00 UTC) and peak user activity (19:00 UTC). Resolving this conflict, the system recommended a strategic deployment at 14:00 UTC, prioritizing long-term retention over immediate cost minimization. These findings demonstrate that the framework effectively transitions campaign management from intuition-based execution to precision engineering, maximizing Return on Investment.
