HODL-C1
Last updated
Last updated
HODL-C1 is our token investor scoring model designed to identify blockchain addresses with a high likelihood of becoming long-term token holders. Deployed on Ethereum, Polygon, and BSC, it delivers actionable customer intelligence by accurately predicting investor behavior. With nearly 90% prediction accuracy, HODL-C1 enables blockchain businesses to optimize operations—whether refining sales strategies or enhancing security—by understanding and engaging their customer base more effectively.
Developed as a turnkey solution, HODL-C1 brings advanced AI capabilities directly to your application without the need for an in-house data science team. Its insights empower businesses to offer tailored, dynamic benefits, such as optimized IDO terms, while providing an enhanced user experience that mirrors the personalized touch found in Web2.0 services.
HODL-C1 offers high-resolution targeting by delivering address-specific customer intelligence. Its predictions allow launchpads to design tiered benefits and dynamic offering terms that reward long-term holders fairly, regardless of their wallet size. This means more inclusive and effective customer segmentation, helping you cater to a diverse investor base.
Other key features include its ability to process massive volumes of on-chain data, enabling the model to stay current with evolving blockchain behaviors. With an intuitive design, HODL-C1 transforms complex data into clear, actionable insights that drive smarter business decisions.
HODL-C1 is powered exclusively by on-chain data, drawing from Ethereum, Polygon, and BSC networks. It leverages extensive datasets—including millions of wallet records, billions of transactions, and comprehensive token features—to develop a robust understanding of investor behaviors. For example, on Ethereum alone, the model was trained using over 49 million wallets, nearly 900 million token features, and more than 1.6 billion transactions.
This rich dataset enables HODL-C1 to capture the nuances of wallet activity, from trading frequency to overall token holding patterns. The breadth and depth of the data ensure that the model’s insights are both precise and scalable, providing a reliable foundation for its high-accuracy predictions.
HODL-C1 is powered exclusively by on-chain data, drawing from Ethereum, Polygon, and BSC networks. It leverages extensive datasets—including millions of wallet records, billions of transactions, and comprehensive token features—to develop a robust understanding of investor behaviors. For example, on Ethereum alone, the model was trained using over 49 million wallets, nearly 900 million token features, and more than 1.6 billion transactions.
This rich dataset enables HODL-C1 to capture the nuances of wallet activity, from trading frequency to overall token holding patterns. The breadth and depth of the data ensure that the model’s insights are both precise and scalable, providing a reliable foundation for its high-accuracy predictions.
HODL-C1 stands out with nearly 90% prediction accuracy across Ethereum, Polygon, and BSC. This impressive performance metric reflects the model’s ability to correctly identify addresses that are poised to be long-term token holders, a critical capability for optimizing dynamic initial DEX offering (IDO) terms.
To ensure that HODL-C1’s impressive performance is robust and not simply a result of overfitting to its training data, we conduct extensive out-of-sample testing. This means we evaluate the model on fresh, unseen data—separate from the data used during training—to simulate real-world conditions. By confirming that the model maintains its high prediction accuracy on this new data, we build confidence in its ability to perform reliably in live environments.
HODL-C1 is primarily used to generate personalized, data-driven recommendations for blockchain businesses. One key use case is optimizing IDO terms by identifying high-value investors, enabling launchpads to offer the most compelling benefits to wallets with the greatest potential for long-term engagement. This targeted approach helps both the launchpad and its fundraising teams secure a more committed investor base.
Beyond optimizing token offerings, HODL-C1 can serve as a powerful tool for customer intelligence. By providing detailed insights into investor behavior and segmentation, the model supports more informed decisions in marketing, product design, and operational strategies. Whether you’re looking to refine your sales approach or enhance overall security, HODL-C1 delivers the precision and depth needed to understand and serve your customer base effectively.
