Team Lampros Labs DAO - LTIPP Research Bounty Proposals

Archive LTIPP Bounties
1

Proposed Research Topic -

We, members of the team Lampros Labs DAO, would like to work on the below-mentioned research topics -

1. Comprehensive Analysis of Incentive Program Effectiveness and Value Generation for LTIPP Participating Protocols on Arbitrum

2. Effects of Growth Incentives on Non-Recipients Protocol in STIP & BSTIP

Research Project 1 -

Title - Comprehensive Analysis of Incentive Program Effectiveness and Value Generation for LTIPP Participating Protocols on Arbitrum

Objective - To conduct an in-depth investigation into the effectiveness of the Long-Term Incentive Pilot Program (LTIPP) for protocols participating in the Arbitrum ecosystem, evaluating their value generation, user acquisition, and engagement, while exploring innovative mechanisms and strategies for optimizing incentive program design and value capture.

Core Scope - Sub-Research Questions - (Recommended by Council)

Sector Growth, User Interaction, and Incentive Effectiveness - (Wintermute ARB, GMX/Saurabh)

  • Identify which sectors (e.g., DeFi, gaming) witnessed the largest growth in user activity and user base during the incentive programs.
  • Analyze user retention rates and interaction patterns within each sector, categorizing actions as reward-driven or genuine long-term usage.
  • Evaluate different ways incentives are utilized across the Arbitrum ecosystem and their effectiveness in creating sticky liquidity and long-term user engagement.

User Actions with ARB Rewards and Unintended Incentivized Actions - (Wintermute ARB, 404 DAO)

  • Investigate how users utilize the ARB rewards received from various protocols and their subsequent actions.
  • Track the flow of ARB rewards, categorize actions (e.g., selling, reinvesting, adding to liquidity pools), and analyze behaviour by protocol cohorts.
  • Identify any unintended incentivized actions resulting from the current incentive programs and propose adjustments to mitigate such behaviours.

Funding Mechanisms and Dollar-Cost Average of Incentives - (GMX/Saurabh)

  • Explore and assess the various funding mechanisms employed for distributing incentive funds across the ecosystem.
  • Research different funding mechanisms, evaluate their effectiveness in terms of capital efficiency and value distribution, and propose new mechanisms if applicable.
  • Calculate the average cost of $1 ARB spent on incentive programs and the corresponding return on investment for the Arbitrum ecosystem.

High-Velocity Incentive Systems and Total Value Returned (TVR) - (404 DAO)

  • Identify incentive systems that enable the highest velocity of value generation and circulation per ARB token distributed.
  • Analyze different incentive systems, measure their value generation velocity using appropriate metrics, and identify the most effective systems for optimizing value capture.
  • Define and compute the Total Value Returned (TVR) metric for each protocol participating in incentive programs, and compare results to assess the effectiveness of incentive programs in driving value creation and retention.

Optional topics - (If time permits we will include analysis on these optional topics as well)

Mercenary Users and Multi-Protocol Engagement - (Wintermute ARB)

  • Determine the percentage of users/wallets engaging with multiple protocols simultaneously to maximize rewards from incentive programs.
  • Analyze wallet activity across different protocols, identify patterns of multi-protocol engagement, and quantify the extent of mercenary behaviour.
  • Investigate the impact of mercenary users on the overall ecosystem and propose strategies to mitigate potential negative effects.

Reward/User Ratio and Market Demand - (Wintermute ARB)

  • Identify protocols with the highest and lowest rewards per user during the incentive programs.
  • Analyze user activity trends in relation to reward levels, and identify inflection points in user behavior based on the reward/user ratio.
  • Evaluate the correlation between reward levels, user engagement, and market demand for various protocols and their offerings.

Why this is an important topic to research -

  • Incentive programs like LTIPP involve a lot of resources, so we need to understand if they are effective and valuable for participating protocols.
  • By analyzing user behaviour, engagement, and value generation, we can optimize incentive program designs to achieve better results.
  • Understanding funding mechanisms and sustainability is crucial for the long-term success of incentive programs and protocol growth.
  • Insights into cross-protocol interactions and network effects can help foster collaborations and ecosystem growth.
  • Identifying best practices and recommendations will benefit not just LTIPP participants but the entire Arbitrum ecosystem.
  • Evaluating reward distribution and allocation strategies can help protocols attract and retain users/liquidity more effectively.
  • Assessing protocol competitiveness and differentiation through incentives can inform better positioning strategies.
  • Uncovering unintended consequences allows for course-correction and risk mitigation.
  • Quantifying the value captured by protocols can guide future investment and incentive budgeting decisions.
  • The research provides a framework for measuring the ROI and cost-effectiveness of incentive programs.

We have divided our work in Milestones and created a roadmap to work on this research bounty. Sharing it here for reference.

Milestone Breakdown of this Research by Lampros Labs DAO.

How you will present this information to the DAO -

  • We will create a detailed final report with clear explanations, visuals (charts, graphs), and actionable insights.
  • The report will be accompanied by interactive dashboards showcasing key metrics and data visualizations.
  • All data, code, and methodologies used in the research will be open-sourced in a public data repository.
  • The report, dashboards, and data repository will be shared publicly for transparency and knowledge-sharing.

Research Project 2 –

Title - Effects of Growth Incentives on Non-Recipients Protocol

Objective -

  • Study the spillover effects of incentive programs on protocols within the same category that did not receive incentives.
  • Focus on a specific category like decentralized exchanges (DEXes) or lending protocols that received incentives in STIP Round 1 or STIP Backfund, and compare the user(DAU, MAU), TVL, and fee growth of non-recipient protocols within the same category.

Why this is an important topic to research -

  • Incentive programs aim to boost growth, but their impact on non-recipient protocols in the same category is unclear.
  • Understanding spillover effects can help assess the overall effectiveness of incentive programs on the ecosystem.
  • Insights into user behaviour, TVL, and fee trends for non-recipients can inform future incentive program designs.
  • Identifying potential negative consequences or unfair advantages for non-recipients is crucial.
  • The research can guide protocols on strategies to benefit from or mitigate the effects of incentive programs.

We have divided our work in Milestones and created a roadmap to work on this research bounty as well. Sharing it here for reference.

Milestone Breakdown of this Research by Lampros Labs DAO.

How you will present this information to the DAO -

  • We will create a comprehensive report with clear explanations, visuals (charts, graphs), and key findings.
  • The report will be accompanied by interactive dashboards showcasing relevant metrics and data visualizations.
  • All data, code, and methodologies used in the research will be open-sourced in a public data repository.
  • The report, dashboards, and data repository will be shared publicly for transparency and knowledge-sharing.

Research Team Information -

Team background -

About Team Lampros Labs DAO -

At Lampros Labs DAO, our mission is to foster innovation and support the growth of the Arbitrum ecosystem. We are dedicated to building a decentralized future by contributing to projects that enhance the Arbitrum network’s scalability, security, and user experience. We aim to foster a collaborative environment for Arbitrum, bringing in a new user base and spreading awareness about the Arbitrum ecosystem.

Our team is dedicated to data analysis and visualization, to make complex data simple to understand for every user of Arbitrum. Through our expertise in data engineering, statistical analysis, machine learning, and blockchain analytics, we aim to provide insightful and actionable insights that can drive informed decision-making and optimize the Arbitrum ecosystem’s growth and development.

Contributions done by Members of Lampros Labs DAO in Arbitrum Ecosystem -

Lampros Labs DAO | Arbitrum Contributions

Team Members -

@Euphoria -

Euphoria is a management postgraduate from a Tier 1 institute, specializing in data and analysis, project management, and marketing. He excels in data visualization and analysis, leveraging his expertise to derive insightful conclusions from complex datasets. With a strong background in project management, Euphoria is adept at coordinating team efforts and ensuring seamless execution of research initiatives.

@Blueweb -

With powerful experience in the blockchain industry, Chain-L has developed and built various projects across multiple ecosystems. He possesses a deep understanding of the underlying technologies and has worked extensively with Layer 2 solutions, including Arbitrum, Optimism, and Polygon. He led the numbaNERDs task leaderboard while encouraging other data analysts to contribute to the DAO. Chain-L is skilled in analyzing on-chain data, and tracking key metrics like user growth, Total Value Locked (TVL), and engagement levels.

@ARDev097 -

ARDev is skilled in data warehousing, ETL processes, and database management systems like MySQL and PostgreSQL. He is an expert in integrating on-chain data sources, data cleaning, and ensuring data quality. ARDev is proficient in using blockchain data analysis tools like Dune Analytics, creating interactive Dune Dashboards, and developing spellbooks for analyzing user behaviour and interaction patterns within the Arbitrum ecosystem.

@jason42 -

Jason is highly skilled in statistical analysis and data mining techniques. He is proficient in using programming languages like Python for exploratory data analysis and identifying patterns within complex datasets. Jason has extensive experience with econometric modelling and quantitative analysis, which are critical for assessing financial mechanisms and cost-effectiveness.

Why your team is the best fit to research this topic -

Our team, Lampros Labs DAO, is the ideal choice to conduct this research due to our extensive hands-on experience and proven expertise in analyzing user behaviour, interaction patterns, and incentive program dynamics within the Arbitrum ecosystem. We have completed numerous projects involving data collection, analysis, and impact assessments specific to Arbitrum, including Sybil/impact analysis, delegate voting patterns, and governance participation studies.

This domain knowledge, coupled with our skills in handling large datasets and understanding the intricacies of incentive program mechanics, makes us uniquely qualified to deliver comprehensive and actionable insights for this bounty program.

We are familiar with the Arbitrum incentive programs, including STIP Round 1 and STIP Backfund and have closely followed and studied the various incentive programs implemented on Arbitrum, giving us the necessary context and knowledge to effectively evaluate their impact on the ecosystem.

We have extensive experience in analyzing decentralized exchange (DEX) and lending protocol data on Arbitrum. We have consistently worked on extracting and processing on-chain data specific to these protocol categories, giving us a deep understanding of the underlying metrics and patterns.

Some of the relevant tasks that we have completed for the Arbitrum ecosystem are -

Collusion analysis on the arbitrum governance forum (User Activity and Collaboration)

Understanding Factors That Lead To Successful Grant Applications

Collusion analysis on the arbitrum governance forum (Analyzing Sentiment Dynamics and Engagement Patterns)

Analysis of Delegates Voting Pattern

Analyzing Governance Participation Data

LTIPP Voting Dashboard

STIP-Bridge Voting Dashboard

Budget -

Requested budget -

We are requesting a budget of 27,724 ARB for both the research.

Cost breakdown (including both the research topics) -

  • Research and Data Gathering - 5,000 ARB
  • Data Analysis, Data Visualization & Dashboard Creation - 15,000 ARB
  • Platform Subscription (Dune) - $999 * 3 months - 2724 ARB (1ARB ~ 1.1 USD).
  • Report Creation and Compilation - 5,000 ARB
11 Likes
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Hi @Euphoria,

thanks for putting together a great research bounty proposal! Both research projects are well-rounded with clear deliverables and goals which we appreciate. Our only concern is that there is a considerable amount of research questions and deliverables within scope and we wouldn’t want sections receiving inadequate research time due to the workload being so large. However, the deliverables table should certainly help with this.

1 Like
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Hey @WintermuteGovernance,

Thank you for your comments, we will look into all questions once again and re-distribute tasks among team members expected to work. If there are inconsistencies in what we will be able to answer in the given timeframe, we will eliminate a few questions to focus well on the rest.

4

Thanks for your application @Euphoria. We appreciate the approach to tackle multiple of the Council’s research questions as well as providing a milestone breakdown with deliverables. Overall, the budget seems very reasonable but we have some questions on research project 2.
You state the objective:

Can you provide more details on the proposed scope? Will you be addressing one specific category or do you plan to address all subcategories that received incentives?

1 Like
5

Hi @404DAO,

Thank you for your comments!

Regarding research project 2, our primary focus will be on specific categories such as DEXes and lending protocols. We believe a comprehensive study requires an in-depth understanding of all protocols within a category. Therefore, we will initially limit our scope to one committed category. However, if time permits, we are open to expanding our research to include additional subcategories.

6

Lampros Labs DAO Proposition

Lampros Labs DAO has demonstrated consideration into evaluating metrics contained within the LTIPP Research suggestions. Building a variety of metrics surrounding Arbitrum’s Governance Programs, Incentives, Voting Participation, and more. The proposal is well quantified and measurable with the milestone breakdown.

Our Concerns

The proposal needs clarification on some of the following:

  1. How are you looking to represent some of the mentioned KPIs and its effectiveness on Dune, what charts would you showcase?
  2. An issue that persisted with various categories of the STIP Round 1, was the sybilling that occured, how will you address this in understanding user behaviour and incentive spent?
  3. Would be good to get understand what specific measurable metrics are you looking to identify for the topics in the research?
  4. The scope of research is quite large, wondering would it be reasonable to cover all aforementioned topics of research?
  5. The second research project on the effects of growth incentives on non-recipient protocols is interesting but may need a more concrete hypothesis and expected outcomes. It’s important to clarify how this research will specifically benefit non-recipient protocols and the broader ecosystem.

Summary

Lampros Labs has made steps to support the Arbitrum ecosystem and its DAO, we suggest clarity to the above questions and focusing on a few milestones that would be the most effective in your research to improve the impact to the community in understanding. Providing concrete information on the metrics and the milestones, will help the success for the execution of the proposal.

1 Like
7

Thanks for submitting your application as well as your responses back to comments, @Euphoria!

With a max budget of 200k ARB to be allocated towards the LTIPP research bounties, Lampros Labs ranks near/at the top of my list of recommendations.

What I like:

  • The proposed research projects and scope well satisfy the intended objective of the LTIPP research bounties.
  • At 27,724, this is a very reasonable budget for the scope of the research projects that has been proposed to be covered.
  • Lampros has demonstrated prior work completed to produce dashboards and analysis on the Arbitrum ecosystem which is helpful to get a better understanding on potential work product to be delivered.
  • The team working on the LTIPP research bounty seems competent and well equipped to cover the task at hand.
  • Milestones and detailed breakdown of estimated time to be spent throughout.

My concerns:

  • Echo same concern raised by some other LTIPP council members about quantity of research topics potentially overtaking quality/detail of final work product. Agree on the focus of Research Project 1 being the core focus and Research Project 2 should serve as a stretch goal.
  • Would like to see more details behind the methodology of analysis and measurement.
1 Like
8

Hey @Saurabh,

Thank you for the valuable feedback and questions regarding our research proposal.

We appreciate the opportunity to clarify and provide more details on the points you raised.

Here are our responses to each of the above questions -

  1. Representation of KPIs and their effectiveness on Dune -

    We plan to create interactive dashboards on Dune that showcase key metrics and trends related to the research topics.

    The Dune platform provides the following chart types to visualize data -

    • Bar Charts
    • Area Charts
    • Scatter Charts
    • Line Charts
    • Pie Charts
    • Counters

    We will create interactive dashboards on Dune, utilizing the appropriate chart types from this list to effectively represent the key metrics and trends related to our research topics. The selection of chart types will be based on the suitability of each visualization for the specific data being analyzed. Our goal is to provide clear and insightful dashboards that leverage the available charting capabilities on the Dune platform.

    Additionally, we are requesting a Dune subscription to download the available data. With this downloaded data, we will create various visualizations that go beyond what is currently available on Dune, aiming to represent the information more clearly and understandably.

  2. We understand that analyzing Sybil attacks is important for accurately understanding user behaviour and the effectiveness of incentives spent during any incentive programs including STIP, bSTIP or LTIPP.

    We can leverage the Sybil data reported by LayerZero. We can filter out identified Sybil addresses and transactions, enabling us to obtain a more accurate representation of genuine user behaviour and incentive effectiveness.

    However, while we have the capability to explore this topic in-depth, it falls outside the core scope of our current proposal. Given the time constraints, we are not committing removal of Sybil addresses during our analysis. But if that shall be a priority and the council considers it important we can revise it in the proposal.

  3. Below are the major general metrics (for both the research projects) that we are going to include in our research report and dashboard, but we will also incorporate other specific metrics relevant to each research project.

    • User Growth Metrics - We will analyze daily active users (DAU), monthly active users (MAU), the number of new users acquired during the incentive program period, and the user growth rate compared to the pre-incentive period for each participating protocol.

    • User Engagement and Retention Metrics - We will measure the average transaction volume per user, average transaction frequency per user, and user retention rates at various time intervals (e.g., 1-day, 7-day, and 30-day) to assess user engagement and retention.

    • Total Value Locked (TVL) Metrics - We will evaluate TVL growth for each participating protocol during the incentive program, the percentage of TVL increase attributable to the incentive program, and TVL retention post-incentive program.

    • Protocol Revenue and Fee Metrics - We will analyze the total trading volume and fees generated during the incentive program, as well as the average fees per user and transaction, to assess each protocol’s revenue and fee generation.

    • Reward Distribution and Utilization Metrics - We will examine the total ARB rewards distributed per protocol, the reward distribution among users (using metrics like the Gini coefficient for inequality distribution of ARB rewards among participating users), and the percentage of ARB rewards sold, staked, or provided as liquidity by users.

  4. After careful consideration of all the council member’s feedback and re-evaluating our proposal, we have decided to keep the following two research topics as optional and not commit to them as part of the core scope -

    • Mercenary Users and Multi-Protocol Engagement.
    • Reward/User Ratio and Market Demand.

    While we have the capability to explore these topics, we want to prioritize and focus our efforts on the other research questions outlined in the proposal. However, if time permits, we will also be happy to include analysis on these optional topics. Our goal is to deliver high-quality and comprehensive insights within the proposed timeline.

  5. We agree that a more concrete hypothesis and expected outcomes would strengthen the proposal.

    Our hypothesis is that incentive programs may have spillover effects, both positive and negative, on non-recipient protocols within the same category. By analyzing key metrics like user growth, TVL, and fee trends for these protocols, we aim to quantify these effects. The expected outcomes include identifying potential advantages or disadvantages faced by non-recipients and proposing strategies to mitigate negative impacts or capitalize on positive spillovers.

    This research will benefit non-recipients by providing insights to better navigate the incentive landscape and the broader ecosystem by informing future incentive program designs.

Please let us know if you have any other questions. We will be happy to answer that!

1 Like
9

Hey @karelvuong,

Thank you so much for your valuable feedback and comments. We appreciate the positive points raised regarding our proposed research projects, scope, budget, team competence, and milestones and it means a lot to us.

To address your concerns -

  1. Regarding the concern about the quantity of research topics potentially impacting the quality and detail of the final work product, it resonates with comments received from other council members and we have re-evaluated the questions covered in our research that we are deciding to keep the Mercenary Users and Multi-Protocol Engagement and “Reward/User Ratio and Market Demand” topics as optional.

    As for Research Project 2 on the effects of incentives on non-recipients, we aim to quantify potential positive and negative spillover effects by analyzing user growth, TVL, and fee trends within the same protocol categories. This will identify advantages/disadvantages faced by non-recipients, propose mitigation strategies, and ultimately benefit the entire ecosystem by informing future incentive program designs.

    Our core focus will be on the other research questions outlined in Research Project 1 and Research Project 2, ensuring we deliver high-quality and comprehensive insights within the proposed timeline. If time permits, we will be happy to include analysis on these optional topics as well.

  2. We appreciate your interest in understanding our methodology in more detail. To address your concern, we would like to elaborate on our approach and the key steps we will take to ensure a comprehensive and reliable study.

    • Data Collection: We will primarily rely on the Dune Dashboard to collect on-chain data related to user activity, transactions, token transfers, and smart contract interactions. This data will be collected for the specific time periods relevant to the incentive programs being studied.

    • Data Preprocessing and Cleaning: Before conducting our analysis, we will preprocess and clean the collected data to ensure its quality and reliability. This will involve filtering out irrelevant or erroneous data points and handling missing or incomplete data.

    • Metrics and KPI Calculation: Based on the cleaned and preprocessed data, we will calculate the specific metrics and KPIs outlined in our proposal, such as user growth, retention rates, transaction volume, TVL, and reward distribution.

    • Data Analysis and Visualization: We will employ various data analysis techniques, to identify trends, patterns, and correlations within the data. We will also create informative visualizations, such as charts, graphs, and dashboards, to present our findings in a clear and accessible manner. These visualizations will be designed to highlight key insights and support data-driven decision-making. For visualization, we will first focus on the options available on the Dune platform. As we advance, we will also utilize Python libraries like Plotly to create more interactive visualizations.

    • Deliverables and Reporting: Our final deliverables will include a comprehensive research report detailing our methodology, findings, insights, and recommendations. The report will be accompanied by interactive dashboards and visualizations, allowing community members and users to explore the data and findings in a user-friendly manner. We will also provide access to the underlying data and analysis scripts to ensure transparency and reproducibility.

By following this approach, we aim to deliver a thorough and reliable study that provides valuable insights and actionable recommendations to the Arbitrum community. We are committed to maintaining the highest standards of data integrity, analytical thoroughness, and research ethics throughout the project.

Please let us know if you have any other questions. We will be happy to answer that!

1 Like
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Hello @WintermuteGovernance @404DAO @Saurabh @karelvuong,

We appreciate the comments and feedback from all council members. Accordingly, we have made changes to our proposal.

The two major changes are -

  1. We have kept the “Mercenary Users and Multi-Protocol Engagement” and “Reward/User Ratio and Market Demand” topics as optional. Our core focus will be on the other research questions outlined in Research Project 1. If time permits, we will include analysis on these optional topics as well.

  2. We have added a Milestone and Deliverables Breakdown for Research Project 2 on the effects of growth incentives on non-recipient protocols. This will help council members track the flow and progress of this research project.

We are committed to delivering high-quality and comprehensive insights within the timeline.

We would be happy to answer any other questions or provide further clarification if any council members have any.

1 Like