| A | B | C | D | E | F | G | |
|---|---|---|---|---|---|---|---|
1 | Target | level 0 | level 1 | level 2 | Detail | Deliverables | Comments |
2 | Objective 1 - Reporting and Monitoring | Fund flow tracking (Outflow of eachl funding address) | Overview of the funds usage | Dashboard with grant funds flowing in and out | - Cumulative outflow Volume (Progress Bar) - Transfer volume by day (Bar Chart) - Transfer out destination address breakdwon (Pie Chart) - group by address (Top 10) - grouped by address type (EOA Contract Address...) | Dashboard | Pay attention to whether the initial funds are misused / not according to proposal |
3 | Incentive claims | - Overall claim progress - Claim progress by protocols | Dashboard | Need to get all the claim logs | |||
4 | Monitor and report abnormal $ARB flow | Huge capital flows | Amount of single transaction/single hour/single day > N (based on a percentage of the total amount for each project) | Bot | |||
5 | Abnormal liquidity | Normally, $ARB can only be transferred to the smart contract address used for issuing incentives as per the proposed guidelines - Funds flow to EOA addresses - Funds flow to CEX address - Funds flow to Dex - Fundsl flow to bridges | Bot | The key is to find relevant address labels | |||
6 | Abnomal reward claim | Alert for abnormal incentive distribution (e.g. 80% of incentives are sending to 1 wallet) | Bot | The core is to define abnormal behavior | |||
7 | Anti-cheating monitoring (Who was the reward given to, and were it given to some risk addresses?) misallocation, unethical behavior | Flag claimant risk | Claimant analysis Dashboard | 1. Basic information An overview - Reward cumulative claim percentage - cumulative reward distribution group by address Break down into protocols - Reward cumulative claim percentage - cumulative reward distribution group by address | Dashboard | Need to get all claim logs for each protocol and 1. Incentive pools / addresses 2. Incentive rules | |
8 | 2. Abnormal behavior - Rewards re-allocation - If multiple address rewards are collected to a certain EOA, all relevant addresses are considered risk addresses - The key is to define the collection behavior. - E.g. It is normal for many addresses to claim and then staking in a certain pool (transferred to a smart contract). | Dashboard | Risk address (collection behavior) If multiple address rewards are collected under a certain EOA, all relevant addresses are considered risk addresses The core here is to define the collection behavior. For example It is normal for many addresses to claim and then staking in a certain protocol (transferred to a smart contract). Many addresses claim to be collected to an EOA address, which may be risky Risk address (botnet behavior) Take the behavior on the chain (historical behavior + behavior in re-incentive activities) and find the address of the suspected botnet It may take some time to define here: the possible definition appears multiple times and does the same thing at the same time | ||||
9 | 3. Wash trading alert - Percentage of Wash trading Volume - Percentage of Wash trading addresses - Percentage of Wash trading addresses claim rewards | The key is to indentify washtrading behaviour, which may be various from sector to sector | |||||
10 | Objective 2 - Data Aggregation and Impact Analysis | Data aggregation | All-in-one dashboard demonstrating all the data | Put all dashboards provided by STIP protocols in one dashboard as well as in a readable and logical manner for the better understanding | Dashboard | ||
11 | Impact Analysis on ecosystem Overall + by sector + by protocol | TVL | - Total TVL - Daliy TVL & Daliy TVL Breakdown - flow in & flow out - Breakdown by Protocol - Breakdown by Token Top 10 / Token type(Stable Coin ,stToken...) - Breakdown by Bridge (may be too complicated tbd) | Dashboard | The key is labeling and obtaining valid token prices | ||
12 | Transaction | - Total Transaction Count - Daliy Transaction Count & Transaction Count Breakdown - Breakdown by 'To Address' , group by protocol - Breakdown by 'From Address' top 100 users - Avg. Transaction Count per day/ user | Dashboard | ||||
13 | Gas fee | - Total Gas Consumption (L1 + L2) - L1 Gas vs. L2 Gas - Daliy Gas fee & Daliy Gas fee Breakdown - Breakdown by 'To Address' , group by protocol - Breakdown by 'From Address', top 100 users - Daliy Gas Price | Dashboard | ||||
14 | User | - New User - Active User - The penetration rate among L1 active addresses Retention of new users - Cohort analysis of retention (7-day / 30-day retention rate) - Weekly retention, monthly retention - line chart Retention of active users - Cohort analysis of retention (7-day / 30-day retention rate) - Weekly retention, monthly retention - line chart | Dashboard | ||||
15 | Volume | Daliy Volume & Volume Breakdown - group by Protocol - group by Token | Dashboard | ||||
16 | Behaviour Analysis Methods of standardization and benchmarking across protocols | Scoring system for Dapps | Criteria - User size: active users/cumulative users - Growth: number of daily new users - Value: tvl per user - Active level: tx count per user - User Stickiness: New User Retention Rate/Overall User Retention Rate | Dashboard/Website | Design a weighted scoring system to evaluate the performance of each dApp and compare the score before and during the STIP | ||
17 | Scoring system for Users | Criteria - Maturity: types of protocols engaged, cumulative tx number - Active level: active days on a weekly / monthly basis - Value: Number of precipitated assets - Governance: delegate voting, participate in ARB governance | Dashboard/Website | Design a weighted scoring system to evaluate the maturity of users and compare the score before and during the STIP | |||
18 | LTV (Long-Term Value Analysis) | Long-term contributions to TVL Long-term contributions to activity Long-term Contributions to txn | Dashboard | Post-STIP analysis, we will continue to monitor the data | |||
19 | Analysis of capital utilization efficiency | Calculation of ROI | Arbitrum network as a whole & breakdown into protocols | Average cost of - acquiring new users - activating existing users - adding TVL per unit - long-term retained users (post STIP) - long-term retained TVL (post STIP) | Dashboard/Report | ||
20 | Comparison among all protocols / incentive methods | - Compare all the costs mentioned above - Investigate the best incentive method in each sector | Dashboard/Report | ||||
21 | Claimant Analysis Understand the user behaviour of claimants | Dealing with incentive rewards (percentage stacking chart) | - Long-term holding - Transfer Out - Directly Sell - Delegated governance - Direct participation in governance | Dashboard/Report | |||
22 | User types (percentage stacking chart) | - Overlap of claimants among incentive projects - Arb holder - Airdrop farmer - cohort by volume - cohort by balance - cohort by activies | Dashboard/Report | ||||
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