💸Rev Share

DataBot's Revenue-Sharing Model Integrated with DataBot's Revenue Generation

1. Sources of Revenue for DataBot

• Subcriptions: We will collect $DATA and $ETH through our subscription plans

• Taxes from Trading (1%): 40% of our taxes on volume.

• Future Revenue Streams: Custom AI Solution, Advertising & Cross-Promotion

2. Allocation of Revenue

• Tier Holders (80%)

• Increasing and incentivizing LP (20%)

3. Revenue sharing distribution model

The revenue sharing system is not yet active. It will be activated when we reach a sufficient level of revenue. In the meantime, we will use the revenue to buy back and burn DATA.

Example of distribution for 80 eligible users (current) and $100,000 Revenue Share

We are distributing a $100,000 revenue share among 80 users across 3 tiers (T2 to T4). Tiers T0 and T1 will not receive revenue sharing, while T2, T3, and T4 will. Here's the comprehensive overview, including the table and explanations of each value.

Tier	Token Holding	Users (U)	Reward Boost	Total USD Reward	Average User Reward
T1	1M	-	0	-	-
T2	2.5M	18	1	$4,762	$265
T3	5M	25	2	$19,048	$762
T4	10M	37	4	$76,190	$2,059

• Explanation of Each Value

1. Token Holding (T): The predefined amount of tokens required to be held to qualify for each tier. Tiers with higher token holding requirements are typically more exclusive.

2. User (U): Indicates the distribution of 80 users across the tiers. More users are in the lower tiers (T0 and T1), which do not participate in revenue sharing.

3. Reward Boost (R): A multiplier that increases the impact of each tier in the reward distribution. Tiers T0 and T1 have no reward boost as they do not share in the revenue, while higher tiers have increasing reward boosts.

4. Weight: Represents the combined influence of Token Holding and Reward Boost on the reward distribution. It's calculated for tiers participating in revenue sharing (T2, T3, and T4), influencing their share of the total rewards.

$$W = T \times R$$

5. Total Weight: The sum of the weights for eligible tiers, used to determine the share of the total rewards.

$$W_{total} = \sum_{1<tier<5}W$$

6. Rewards Multiplier: A factor calculated to distribute the total rewards of $100,000 across the tiers based on their weights. It's derived from dividing the total rewards by the sum of weights of participating tiers.

$$M = \frac {Total \space {Rewards}} {W_{total}}$$

7. Total USD Rewards: The actual dollar amount allocated to each tier, determined by multiplying its weight by the reward multiplier.

$$R_{USD} = W \times M$$

8. Per User USD Rewards: The average amount received by each user in a tier, calculated by dividing the tier’s total rewards by its number of users. This value indicates the share of revenue that each user in the tier receives.

$$R_{user} = \frac {R_{USD}} {U}$$

This model ensures a structured and fair distribution of revenue, where only the tiers with investment (T2, T3, and T5) receive shares of the revenue, reflecting their token holding and reward boost. The absence of revenue sharing for T0 and T1 is indicated by their zero reward boosts and consequently zero weights in the distribution.

4. Distribution mechanisms TBA