Hook is an oracle-free, on-chain, orderbook-based option protocol designed for fast-moving crypto assets. It aims to reward users for their contributions to the protocol—whether they’re trading across Hook’s perpetual markets or providing liquidity. The key challenge involved:

• Building an engaging and rewarding points program.
• Ensuring fairness by recognizing and incentivizing genuine efforts.
• Developing a methodology that optimizes useful liquidity and activities that contribute to the protocol’s growth.
• Implementing a system that is resistant to Sybil attacks.
• Creating a data pipeline that handles data ingestion, ETL processes, point calculations, and API serving for the calculated points.

To address these challenges, Hook partnered with OpenBlocks to implement Treasure Hunt in June, an innovative points program designed to drive on-chain activity and attract significant trading volume.

Hook utilized OpenBlock’s Campaign Optimization tool which provides data-driven incentive modeling, ensuring that rewards were distributed fairly and effectively to build a high-quality, long-term community.

The incentive methodology calculated points for activities directly contributing to the Hook protocol’s goals, rewarding both takers and makers involved in perpetual trading. Hook also utilized Scenario Testing to model trading volumes and parameterize the incentive optimization mechanism effectively.

Engagement and Participation: The program made the earning process transparent and achievable through on-chain activities. Users were also rewarded for referring others to the platform, encouraging network growth through word-of-mouth marketing. Additionally, the treasure hunt program introduced competitive trading competitions, motivating users to engage more actively in the protocol. As a result, Hook’s trading volume surpassed $2M in July, doubling month-over-month over the past two months.

Sybil Attack and Wash Trading Resistance: OpenBlock’s Sybil analysis tools are instrumental in safeguarding the program against malicious activities. Using graphical analysis, we developed a data structure capable of identifying Sybil attacks and wash trading. Our algorithms and monitoring tools ensured that rewards are distributed fairly, only reaching genuine participants.

Results: Hook’s Season 1 closes in August, with Season 2 set to begin in October, incorporating learnings from the initial campaign. Future programs are upgraded based on data and insights gathered. These adjustments will keep incentives attractive and optimized for Hook’s next growth phase, maximizing resource allocation for continued success.