Chainfeeds Briefing:
Arbitrum DAO has distributed over 153 million $ARB to more than 100 protocols through multiple incentive programs, aiming to drive user growth, capital liquidity, and ecosystem development. But which plans truly produced effects, and which were barely effective?
Article Source:
https://x.com/castle_labs/status/1930254327966208399
Article Author:
Castle Capital
Perspective:
Castle Capital: Despite massive expenditure, Arbitrum's incentive programs have consistently struggled to deliver long-term results. Metrics like TVL and transaction volume often spike briefly during reward periods, but users quickly abandon the platform once incentives end. This cliff effect has sparked widespread community doubts about the sustainability and return on investment of these incentive programs. Simultaneously, multiple incentive projects lack unified standards in goal setting, structural design, and data measurement, making cross-period comparisons and experience accumulation challenging. Programs like STIP, STIP Bridge, and LTIPP vary in objectives and scale, but most lack adjustable mechanisms or metrics aligned with long-term ecosystem goals. To address these issues, a unified assessment framework was introduced, breaking down each incentive program into four components: objectives and expected outputs, project design, actual outputs, and changes and experience summaries. This framework enables horizontal comparisons of different internal and external projects based on unified dimensions. The research distilled several key insights: first, most users are reward-driven and only participate when incentives exist, with true retention depending on the product's inherent attractiveness and ecosystem fundamentals; second, incentives are suitable for expanding protocols with existing product-market fit, not for generating hype for projects without demand; third, monitoring and feedback mechanisms are crucial, with the zkSync Ignite project significantly improving efficiency through real-time dashboards and governance mechanisms; fourth, avoiding hard deadlines and implementing gradually decreasing incentive releases can more authentically reflect product stickiness. Additionally, the report highlighted that clear objectives help execution and tracking, while unfocused incentives can disperse resources and lack effectiveness. Many failed projects also exposed gaps in user-side infrastructure - even with abundant funding, without user-friendly visualization tools, tutorials, or information transparency, substantial participation remains challenging. Market cycles also dramatically impact incentive effectiveness: in bear markets, focus should be on user education and ecosystem preparation rather than chasing high metrics. Finally, retention analysis provides more meaningful insights than single data points - TVL growth doesn't equate to long-term success and requires in-depth analysis combining user segmentation, retention periods, and user behavior tracking. Based on these observations and experience summaries, five core pillars were proposed for future incentive program design. First, measurement standards and KPI design: develop multi-level indicators aligned with DAO's long-term goals, establish unified dashboards and data feedback mechanisms for real-time adjustment and retrospective analysis. Second, project structure and design: focus on protocols with existing product-market fit, avoiding purely high-metric pursuits, and incorporate flexible adjustment and decreasing release mechanisms. Third, governance and adaptation mechanisms: establish dedicated operational teams to manage incentive processes, set checkpoints and stop-loss mechanisms, ensuring alignment with DAO priorities. Fourth, user segmentation and retention strategies: acknowledge initial user motivations, design convertible retention paths like check-in mechanisms and loyalty programs. Fifth, market marketing and ecosystem collaboration: project launches must include clear communication strategies, brand visuals, FAQs, and visualization dashboards to enhance user engagement. These recommendations not only address previous incentive misconceptions but also provide a practical roadmap for Arbitrum DAO's capital deployment and ecosystem construction in the next phase.
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