Recently, we launched a leaderboard for nominators on Polkadot, available at app.motif.network. This tool provides essential information about addresses, including nominators and pools, and displays the actual APY received by users.
Currently, the interface highlights the “problem” and current risks for nominators. Historical data is available but not utilized in the current frontend. This data generally confirms our initial research: achieving maximum APY is a complex task.
Question: How can we help users address solutions to those problems effectively? How can we assist them in securing the best staking outcome?
We have identified a few potential solutions and would greatly appreciate your input. We believe that testing one solution on Polkadot and another on Kusama would be ideal. We seek advice on which solution might be best or if there are other innovative ideas to consider.
Potential Solutions:
- Simple Nominator Interfaces with Historical Information (No Predictions): This interface would show where and when nominators have been nominated, when they lost their rewards (and the reasons), and other relevant details. Nominators can review their nomination history and discover effective solutions (only a dedicated page on the Motif).
- Nominator Interfaces with Historical Data + Predictions and Risks: This would include up-to-date statistics, along with predictions and risks based on this data. It would provide information on when they might lose their nomination, which validators are unstable, and more. Nominators would receive a set of risks and recommendations for further actions on demand. (only a dedicated page on the Motif).
- Validator Data with Statistical Information and Risk Predictions for Current Nominator: Instead of just providing a current validator set, this solution would offer a set of validators with associated risks and opportunities tailored specifically for the nominator (no validators presets). Nominators could assess the predicted performance of each validator and make informed choices. (only a dedicated page on the Motif).
- Nominator Bug-Fixing ML Model with Chatbot Interface: A chatbot that provides information on the current state of a nominator, compares it with similar cases, and offers proactive solutions (similar to the suggestions above). Nominators can learn their current status directly in the chat and receive basic recommendations. (only chat without any dedicated page on the Motif).
- Interactive Validator Recommendation System for Nominators Based on Past Issues: A context-aware system that connects nominators and validators, offering recommendations based on current states. Nominators can receive dynamic recommendations depending on the immediate global status of validators and nominators through their preferred channel (e.g., Telegram/email). (only chat without any dedicated page on the Motif).
- Nominator Risk Notification System with Prediction Model: An autonomous event-based system that allows users to subscribe to notifications and be warned of risks before they occur (typically a few eras in advance). Nominators can subscribe to events related to their nominations (both personal and pool-related), enabling them to receive advance notice of proposed actions. Unlike option 5, this system provides advance warnings of potential risks without an integrated interface on Motif. Notifications will be sent via Telegram/email.
P.S. We have streamlined our approach by removing plans related to personal accounts, user-specific backend, current backend/frontend refactoring, and any cross-options for solutions above (above rn only page or chat). We are focusing directly on the features you might consider important to test.
We look forward to your feedback on how to enhance the staking experience further for the system.