“Tokenomics” for a Decentralized Yelp
I recently was consulted to devise a token-economic incentive structure for a “decentralized Yelp” — i.e. a decentralized restaurant review service, where users write reviews of restaurants and these reviews are then rated (via likes/dislikes) by other users. Restaurants can also use the platform to advertise selectively.
The main challenge of creating a proper, healthy, tokenized economy is resolving for the innate conflict of interest between platform users and token holders/hodlers/speculators.
The fact that any utility token can be traded on a crypto exchange completely detracts from its inherent use, although on the other hand, when platform users wish to cash out — to whom do they turn?
Decentralized service creators face a severe conflict of interest between potential users and speculators in that the value of their inherent platform token is subject to speculation outside the network on select crypto exchanges.
Worse still, ICOs/Token Sales/TGEs present perverse incentives for founders in that money is raised quickly and in great amounts for this reason only, with little to no thought given to the effect of a speculative, volatile token price on the usability of the end platform.
Platform participants will only be incentivized if their accrued tokens are able to be exchanged for other valuable cryptocurrencies, and ultimately, back to fiat.
Therefore, a utility token must be offered for sale on some sort of exchange, be it an implicit OTC or a standard one like Binance.
Hence there needs to be speculative counter established within the “tokenomics” — to prevent a volatile and rising token price — be it through a specific inflation rate, and/or token lock-up period.
I chose to concentrate on a restaurant review service solely, even though Yelp provides reviews and ratings for the majority of businesses.
Initial parameters (source https://www.yelp.com/factsheet):
· 30M initial users increasing 4.5% yearly (the platform “demand”)
· 10M Restaurants increasing 5% yearly (the platform “supply”)
· 400M initial tokens to be issued
Devising a proper tokenized economic model must align incentives so that:
a) Platform users issue honest, quality reviews of their eating experiences and are “justly compensated”
b) There is a stable growth rate of users and restaurants
c) There is a stable token velocity
d) There is a stable token price as listed on exchanges
Let’s begin.
TOKEN SUPPLY
First, the Token Supply — 400M Tokens. Tokens can be divisible to two decimal places (i.e. you can purchase and/or receive a tenth of a token).
How did I arrive at this number? I chose 10 initial tokens to be given to platform participants (restaurants and users — raters/reviewers) once they register.
Based on 10 initial tokens and assuming 30M already active users and 10M listed restaurants,
(30M+10M) / 10 = 400M Total Tokens
Now, do we make this a deflationary currency (i.e. token supply is held constant at 400M) or do we institute a particular inflation rate?
Deflationary currencies don’t make sense because it incentivizes hodling as the token supply diminishes, which makes the token more expensive to use and thus the underlying decentralized service worthless. (See the first part of our previous MV=P…Que piece for an in-depth explanation.)
Thus, our token supply will be inflationary. But at what rate?
Based on our initial parameters of user and restaurant growth rates, our token supply inflation rate should roughly be equivalent in order to keep a constant rate of 10 tokens per new participant sign-on.
This equates to a reasonable yearly inflation rate of 4.63%.
INCENTIVIZING QUALITY REVIEWS
We want users to post quality reviews.
Quality reviews are denoted by a set number of likes.
Thus, we need to pick an arbitrary number of “likes” that will denote a quality review.
Then we need to rank reviews.
We therefore need to incentivize platform participants to rate reviews — give likes/dislikes.
Where do we start?
We are going to use our 10 tokens-per-platform-participant metric as a base.
We want to rank/list reviews according to when they were posted (date/time) — so reviews posted first will be listed in order, so that other users may then rate.
Thus, here is the incentive structure for reviews:
• Unlimited number of reviews can be posted, but only 30 will be compensated via number of likes.
• First review to receive 10 Likes will receive the max reward of 10 tokens, and so on following a downward sloping (concave) reward curve.
• Reviews must be a minimum of 50 words.
On Yelp, how many reviews do you read? Probably the first 3–5, and no more. This is the reason for the downward concave curve we’ll see below.
I picked 30 reviews to ensure enough chances for users to be compensated for their review.
Also, we must ask — what separates one quality review from another? Honesty? The particular, inherent tastes of a reviewer?
The answer is — not much, really. Therefore, the difference in compensation for the top, quality reviews will be minimal.
INCENTIVIZING LIKES/DISLIKES
For there to be quality reviews, there must be likes/dislikes.
So now for the compensation structure for clicking “like” or “dislike”:
• Likes/Dislikes will be rewarded similarly on a downward sloping curve but will start with a token reward max of 5.
• The First likes/dislikes on a review will be compensated the most, up to the 21st like/dislike (total).
• However, a user can only like/dislike a review once they have written a review first with at least 3 likes (i.e. one review with at least 3 likes per like/dislike).
Since clicking like/dislike is easy to do, there must be a barrier of some sort — ergo why review raters must be writing quality reviews themselves first.
TOKENOMICS ADDENDUMS
Additional parameters for enhanced skin-in-the-game for platform participants and to prevent malicious behavior (i.e. creating fake reviews, accounts, and ratings):
• Users must stake 2 tokens to write a review.
- Upon receiving at least 3 Likes they will receive the 2 tokens back.
• Besides writing one review that receives 3 likes per like/dislike, users must also stake 2 tokens to like/dislike a review.
- The user will receive their 2 tokens back depending on whether their like or dislike coincided with the overall majority of likes or dislikes (21 total).
• Users posting a new Restaurant to review must also write an initial review.
- Users posting a new restaurant review will receive a 2 token reward once their review is completed.
• Restaurants can create an account, so users can begin posting reviews of their establishment for a cost of 3 tokens.
- They can also advertise on the platform by paying 1 token per day (or more to get more attention as per other restaurant bidding).
- They can purchase additional tokens through select token exchanges.
TOKEN PRICING AND ENSURING STABILITY
Now the part that stumps all decentralized platform creators (or should at least):
(1). What is the optimal fiat price for a token (to provide an incentive for platform participants)?
(2). How to keep this token price stable/prevent speculation?
As far as an optimal token price in our decentralized Yelp example— tokens should be listed at around $20.
If we revisit our token rewards for posting quality reviews and initial likes/dislikes, a top review will receive 10 tokens or $200 (after staking 2 tokens or $40) and an initial like/dislike will receive 5 tokens or $100 (also after staking 2 tokens).
To ensure token price stability, a lock-up will be instituted for all platform participants.
Token holders may only sell their tokens on a select token exchange at full price after at least 6 months of purchase.
• The earliest they can sell is after 3 months, but they will only receive 50% of their token value, with the remaining proceeds to be redistributed proportionally to platform users/restaurants.
• They can always purchase additional tokens via an exchange during that time frame.
Notice we did not bring up Token Velocity more than once. Token Velocity is only an issue if the platform participant growth rate slows significantly, or, rises too quickly. If it rises too quickly, well that’s a good problem to have, as we want the network to expand — and the token supply should rise accordingly. If the platform growth rate slows significantly then there must be an issue with the platform incentive structure.
All the talk on token velocity being such a damper on token price is stated with the assumption that the whole world will be using said decentralized service.
As long as the token maintains a not only steady fiat value, but a high enough one, the velocity rate should not be an issue.
CONCLUSION
This model can change if our initial growth rate parameters are not accurate. The review rewards as well as likes/dislikes rewards and token staking should be modified to reflect the true number of tokens per initial platform participants. So 10 tokens per new participant may not be an optimal number.
The incentive structure was also quite arbitrary. Ultimately, we want participants to behave for the good of the platform, and to prevent fake accounts/reviews/ratings.
Two factors however must be present for a decentralized platform to be successful:
(1) Ensuring an inflation rate that mimics platform participant growth.
(2) Preventing token speculation as per a user token lock-up period.
Contact me at brian@austere.capital for additional “tokenomic” design and modeling consultation.
