🎯For Web3 Marketing Agencies

Use Case

Introduction

Nodanomics developed online software to prototype web3 economy mechanics, run instant simulations and even monitor web3 economy health real time after launch. It's user friendly, low cost and does not require coding skills. Having access to such a simulation can help web3 founders to fine-tune their economies and ensure their tokens are on the right track.

The product has unique features such as

• User-friendly interface with drag-and-drop nodes

• Powerful engine to run Monte Carlo or Agent-based simulations.

• Nested loops for granular and accurate prototyping

• Connected to actual web3 data for monitoring economy health

• Connected to Google Drive for fast integration web3 economy design sheets

Project Description

Reach enables anyone looking to promote their content to tap into a pool of engaged, verified, and audited user base, and remunerate them for their contribution to their network effects.

$REACH Token utility:

• Mission Creation: Use $REACH to create regular missions and ETH to premium missions on the platform.

• ETH Raffles Participation: Hold a minimum of 1,000 $REACH to be eligible for ETH raffle rewards.

• Revenue Sharing: Hold at least 10,000 $REACH to participate in sharing 100% of the platform's fee revenue.

• Mission Credit Purchases: Buy mission credits with $REACH, with introductory prices at 25 $REACH per credit.

$REACH Token Model Overview:

Project Scope

Tokenomics audit addressed several issues:

1. Assesses whether the economic incentives within the tokenomics model are aligned with the project goals

2. Evaluate the long-term sustainability of the project by examining token emission schedules, supply dynamics, and mechanisms for maintaining economic stability

3. Identify and mitigate various risks associated with the project tokenomics, providing a roadmap for risk management strategies

Audit process:

1. Sign NDA

2. Questionnaire and quoting

3. Sign agreement

4. Develop tokenomics prototype at Nodanomics studio and run 1st simulation

5. Recommend improvements

6. Prototype updates and run 2nd simulation

7. Audit Reporting

Tokenomics Audit parameters:

1. Proper allocation of ETH proceeds from premium missions across Leaderboard, Raffle and Revenue Sharing pools

2. Adequate proceeds per average stakeholder

3. Required minimum balance in $Reach to participate in Revenue Sharing Pool

4. Sufficient buying pressure at $Reach/ETH DEx

5. Proper total token supply, initial token price and initial liquidity

Audit Execution

Initial tokenomics setup:

1. Allocation of ETH proceeds from premium missions: Leaderboard 20%, Raffle 70% and Revenue Sharing pools 10%

2. Proceeds per average stakeholder - N/A

3. Required minimum balance in $Reach to participate in Revenue Sharing Pool - N/A

4. Sufficient buying pressure at $Reach/ETH DEx - N/A

5. Proper total token supply, initial token price and initial liquidity N/A

Based on the initial tokenomics design and parameters setup we started building a web3 economy prototype using Nodanomics studio. Prototyping implies using several components or we call it nodes such as:

Data Node. The data node is responsible for storing numeric values. We use this node to check pools balances such as Leaderboard pool

Formula node. This node is responsible for calculating mathematical expressions. The inputs can either be dynamic, as logic connections attached to the node or constants, present in the expression itself. The inputs can also be the value from other components using the tag notation system. The node is used to calculate DEx pool liquidity and token price on daily basis

Origin node. This component is responsible for generating new resources to be added to Data components. It generates a new day when the economic loop is over.

Sink node. This component is responsible for draining resources from Data components. When a creator purchase mission it drains tokens from the wallet

Loop node. This component allows the user to create code loops. The logic that’s inside the component will be executed n number of times. In our case it repeats several times and generates stochastically missions creation, its value, allocation of proceeds across pools, buying pressure for DEx.

Overall prototype looks as following

We challenged the prototype through Monte Carlo simulation. It is a computational technique that uses random sampling to model and analyze complex systems or processes. In the context of a tokenomics audit project, which involves assessing the economic aspects of a token, Monte Carlo simulation is a valuable tool for risk assessment and scenario analysis.

Here's summary of Monte Carlo simulation process

1. Identified key parameters in the tokenomics model that are subject to uncertainty or variability.

2. Assigned probability distributions to the identified parameters. These distributions represented the uncertainty or variability associated with each parameter.

3. Used the defined probability distributions to generate a large number of random samples for each parameter. The number of samples was sufficient to capture the potential range of values for each parameter.

4. Analysed the aggregated results and assessed the risk associated with different aspects of the tokenomics model. This helped in identifying potential vulnerabilities and understanding how sensitive the system is to changes in specific parameters.

5. Conducted scenario analysis by manipulating specific parameters to simulate various factors. Evaluated how the tokenomics system performs under different scenarios and identify potential strengths, weaknesses, opportunities, and threats.

Aggregated results showed that most likely selling pressure would be excessive that turns token price into negative dynamics. So it required changing initial economics parameters.

After analysing potential risks on economic sustainability we suggested changing tokenomics parameters by allocating 70% ETH proceeds from premium missions into the leaderboard pool. This amount is programmed to send ETH into DEx to swap for $Reach tokens and send $Reach back to the Leaderboard pool for rewards. Create a threshold of 3000 $Reach at ending balance to get eligibility for revenue sharing pool. We ran Monte Carlo simulation once again and showed that most likely buying pressure will be sufficient to offset selling pressure that comes from tokens released by early investors. Through the estimation of expected trading volume we defined parameters such as total token supply, initial token price and initial liquidity.

Through large scale simulation we validate the minimum required balance of $Reach at user wallets to be eligible to participate in Revenue sharing pool.

$Reach token was launched in Dec '2023 and is now trading at 2x vs initial token price of $0.03. $REACH tokens can be traded on centralized crypto exchanges and decentralized exchanges. The most popular exchange to buy and trade Reach is Gate.io, where the most active trading pair $REACH/USDT has a trading volume of $68,824.46 in the last 24 hours as of 23 Jan 2024. Other popular options include Uniswap V2 (Ethereum) and MEXC. The highest price paid for Reach ($REACH) is $0.3128, which was recorded on Jan 14, 2024. The lowest price paid for Reach ($REACH) is $0.05375, which was recorded on Dec 27, 2023, which is still above initial token price. The fully diluted valuation (FDV) of Reach ($REACH) is $6,240,758. This is a statistical representation of the maximum market cap, giving the maximum number of 100 Million $REACH tokens in circulation today.

Monitor the project economy health

Nodanomics studio allows monitoring tokenomics health realtime. For such purpose, the studio has functionality to drag actual data from ETH blockchain and connect it to the prototype. It runs simulation using actual data, creating near time visibility in terms of expected token price, buying and selling pressure, treasury token balance etc. It gives a powerful tool to mitigate any potential risks in advance.