Monetary Policy

The monetary policy of the $BATCH ecosystem is based on the fees and reward rates:
  • PaaS Fees (per query)
  • Similarity Search aaS Fees (per query)
  • DB as a Service Fees (per query + storage)
  • Share of FB
  • Share of Users
  • Share of Bridgers

Current Monetary Policy

We set fees such that the total cost of operations is around 20% of the total fees collected, which is a conservative rate when compared to successful SaaS startups. The amount equal to the total cost is directly going to FirstBatch in order to break even. The rest of the fees are profit to be shared among FirstBatch, Users, and Bridgers.
FirstBatch could make being profitable a priority and take a high percentage of the profits, but it makes more sense to keep profit margins low in the beginning in order to capture market share aggressively and compensate early adopters that give high-value feedback. Also, distributing the profits instead of distributing the fee revenues directly ensures profitability no matter how big or small the profits are, which is good enough, especially at the seed stage of the project. For these reasons, the initial share of FirstBatch’s profits will be around 20% of the total fees collected, which means around 40% of all fees go directly to FirstBatch.
The rest of the fees will be divided between users and bridgers. Both bridgers and users are key roles in the ecosystem, and the trade-off between their incentives needs to be handled carefully. While users are incentivized by both the content quality and monetary rewards, bridgers’ only incentive is the financial return they get. In other words, query amount is a function of content quality and user rewards while content quality is a function of bridger rewards, so it makes sense for total bridger rewards to be double the amount of total user rewards.

Future Monetary Policy

After the token’s launch, all 6 variables can be adjusted periodically based on the protocol activity, service providing costs, change in stakeholder incentives, etc. by analyzing the protocol usage data and simulations.