We highlight what's driving NEAR on-chain activity and how that affects NEAR's tokenomics.
We recently launched NEAR on our Blockchain Activity Monitor (BAM) and as part of our launch, we wanted to highlight what’s driving activity on NEAR and how to think about the tokenomics of NEAR using fundamental data from Artemis.
TL;DR
As a high level refresher, NEAR is a smart contract layer 1 that uses PoS. In order to solve for scalability concerns, the NEAR protocol uses sharding technology. We won’t get into much depth about the technical details of sharding but at a high level this framework allow nodes in the network to only have to process and store a subset of the chain rather than the entire chain. This allows nodes to just process transactions in their subset rather than in the entire chain, making it less computationally expensive for every node.
Although there are clear benefits to NEAR adopting sharding such as higher transactions per second and lower hardware requirements to become a node there are also 2 major trade offs for adopting this technology: lower security and high centralizations. By splitting the chains across multiple set of nodes its easier to control the entire chain by only needing to attack a single node. This compromised node could share information on invalid transactions with other nodes, potentially compromising the entire network’s security. Furthermore, the possibility of collusion arises with the splitting of nodes into smaller groups. Such collusion could potentially lead to a form of centralization that goes against the ethos of Web3.
Sharding was also proposed for the Ethereum network as early as 2013. Ethereum has never fully adopted this technology because unlike NEAR, which built their chain with this technology from the ground up, Ethereum would need to migrate their chain onto this new technology. Migrations are significantly tougher to execute then building from scratch which is why the Ethereum networks switch to sharding is slated to be sometime in 2024 (4 years after the launch of NEAR) and almost 11 years after the initial proposal.
Similar to other L1 chains, transactions fees are burned to create deflationary pressure. However, unlike Ethereum, there are no priority fees. Validators are instead compensated solely from staking rewards. 4.5% of the total token supply every year is distributed to validators as incentives in exchange for computing, storage, and securing the transactions. Another .5% of total supply is distributed to the treasury for the foundation to use to promote growth of the protocol. This averages around ~136,000 new tokens being minted daily (2).
Ethereum, similar to NEAR, has a target inflation rate of 4.5%. However, unlike NEAR, Ethereum has recently become deflationary which means that Ethereum has began to burn more tokens than the amount of tokens being distributed daily from paying the validators. This causes the daily total Ethereum supply to decrease. Ethereum being deflationary implies future value of the token will not get diluted from the tokens being emitted to compensate validators.
Transactions fees on NEAR like other L1 chains are also being burned. However, unlike other chains there is a 30% / 70% split for transactions fees that are used to call smart contracts. In these transactions, 30% of the fees are given to the smart contracts that are called in the transactions (split evenly amongst all the contracts called in the transactions) and the remaining 70% is burned. This mechanism rewards contracts that are heavily used on NEAR.
NEAR users and transactions were roughly flat until September ‘23 when there was a huge increase in DAUs and transactions.
With the Activity Monitor we can see that activity is being consolidated in two main categories: Social and Gaming. Peeling back these categories, we see that it is really two applications which are the main drivers of activity on the chain: Sweat (Gaming) and Kai-Ching (Social).
Before September it was mostly gaming which was being driven by Sweat. With the launch of Kai-Ching in early September, NEAR usage spiked and the continued usage has been dominated by Kai-Ching, a shopping and mobile app that allows users to get rewarded in $KAIC token when shopping on KaiKai.
In order for NEAR to become deflationary like Ethereum, ~130k token / day would need to be burned on NEAR. Recently NEAR’s burn rate was roughly ~1.6k tokens / day which was driven mostly by the launch of Kai-ching. However, NEAR still has a long way to go to become a deflationary chain like Ethereum. Currently, SWEAT and Kai-ching contribute to ~80% of total tokens being burned daily. It is clear that these two applications are a big driver of usage on chain and has lead to increases in adoption of NEAR. Yet it is still to be seen if these two applications alone can drive up demand of usage for NEAR and create a sustainable increase in token burn.
Sweat also known as Sweat Economy is a fitness app that is the evolution of the breakout App called Sweat Coin. The premise is simple, you get tokens for every step you take which you can redeem for prizes (such as a trip to NEARcon) or fiat currency. They recently launched in the US early October 2023.
Looking at the app page and its predecessor there are over 6,000 ratings and a few reviews. This signals that there are real users actively trying the app. The reviews are mixed and its hard to pinpoint the exact number of unique users but it is clear that Sweat has real users trying out the app.
We can track the usage on chain and see that there are consistently 50,000 unique wallets interacting with the Sweat application on chain. From the graph, it was clear that usage on NEAR was heavily dominated by wallets interacting with Sweat smart contracts with over 50% of transactions fees being attributed to users using Sweat. Sweat’s dominance of NEAR gas fees used dropped significantly after the launch of Ka-Ching — SWEAT now makes up ~10% of all NEAR gas spent down from the peak of 60%.
As we can see from the graph, Sweat DAAs have been on a decline but recently picked up due to their launch in the US in early October. It’s important to note that the gas burned / user has been steadily decreasing meaning each new user is contributing less to token burn than before. It will be important to see how this metric trends over time. If Sweat is able keep a high ratio of gas burned per user while also increasing DAU this would imply that that Sweat is able to retain high value users who contribute to token burn.
Kai-Ching is a payment system and stablecoin that is built by cosmose AI which is a company that specializes in ai powered shopping experiences. They built the popular shopping app KaiKai and phone lock screen app KaiKai NOW. The NEAR foundation recently did a strategic investment valuing the company at $500million USD. The product is reportedly popular in SEA where users use the app to pay at restaurants and other selected stores. As users use the app to pay, they receive cash back in the form of Kai-Ching where 100 Kai-ching is worth 1 USD. It does not seem to have officially launched on NEAR as a token but is said to be redeemable on the KAI KAI app.
There has been a lot of coverage around the app such as this tweet from Ilia (the cofounder of NEAR) highlighting how users were able to use the app to pay for coffee at token2049, a popular crypto conference in Singapore.
KAIKAI is currently not available in the US and despite the high amount of coverage there hasn’t been a clear demo showcasing how exactly the app works. Despite the mystery behind the actual product and real world usage, we can still glean some insights by looking at on chain data. Using the activity monitor, we can see that it is the fastest growing application on NEAR and is contributing the most to gas usage on NEAR.
Doing a similar analysis as Sweat we see that Kai-Ching gas burn / address is much lower than Sweat. Kai-ching weekly average is around ~.001 NEAR / Address vs Sweat’s .003 NEAR / Address, but has been steadily increasing and is close to surpassing Sweat. This shows that the application is not only getting more users, but also getting these users to contribute more to chain usage and token burns.
In order for NEAR to become deflationary like Ethereum, ~130k token / day would need to be burned on NEAR. Recently NEAR’s burn rate was roughly ~1.6k tokens / day which was driven mostly by the launch of Kai-ching. However, NEAR still has a long way to go to become a deflationary chain like Ethereum. Currently, SWEAT and Kai-ching contribute to ~80% of total tokens being burned daily. It is clear that these two applications are a big driver of usage on chain and has lead to increases in adoption of NEAR. Yet it is still to be seen if these two applications alone can drive up demand of usage for NEAR and create a sustainable increase in token burn.
From the on-chain metrics, we saw that both Kai-Ching and Sweat drove meaningful on chain usage of NEAR. However, it is still to be seen if these applications can sustainably grow their user counts and drive more token burn for NEAR. The chain still has a long way before becoming deflationary like Ethereum, but these new applications are pushing NEAR towards that path. With the introduction of ordinals on NEAR and NEAT the first ordinal token, we could see that become a reality sooner.
Appendix:
(1) NEAR technical architecture (nightshade): https://near.org/papers/nightshade
(2) NEAR protocol tokenomics: https://near.org/blog/near-protocol-economics
Disclaimer: The authors, affiliates, or stakeholders of Artemis may hold interests in the tokens or protocols mentioned in this content. This disclosure highlights potential conflicts of interest and is not an endorsement to buy or invest in any specific token or protocol. The content is for educational and informational purposes only and should not be construed as investment advice in any form. Readers should approach this information cautiously and consider their unique circumstances before making investment decisions. The views and opinions expressed are subject to change without notice, and Artemis bears no liability for any loss or damage arising from the use of this information.
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