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if (name === 'viewof percentUsersRegisterName') { - return new Inspector(this.userConversionRef.current); - } - if (name === 'viewof removalRate') { - return new Inspector(this.removalRateRef.current); - } - if (name === 'viewof ensUserbar') { - return new Inspector(this.ensUserbarRef.current); - } - if (name === 'viewof dollarPriceDomain') { - return new Inspector(this.dollarPriceDomainRef.current); - } if (name === 'viewof discountRate') { return new Inspector(this.discountRateRef.current); } - if (name === 'viewof lockedUsdBar') { - return new Inspector(this.lockedUsdBarRef.current); + if (name === 'viewof percentUserBuysPack') { + return new Inspector(this.percentUserBuysPackRef.current); } - if (name === 'viewof netPresentUtility') { - return new Inspector(this.netPresentUtilityRef.current); + if (name === 'viewof userBuyPerYear') { + return new Inspector(this.userBuyPerYearRef.current); + } + if (name === 'viewof dollarPriceStickers') { + return new Inspector(this.dollarPriceStickersRef.current); } return null; }); @@ -54,387 +45,58 @@ class App extends Component { userbarRef = React.createRef(); - userConversionRef = React.createRef(); - - removalRateRef = React.createRef(); - - ensUserbarRef = React.createRef(); - - dollarPriceDomainRef = React.createRef(); - discountRateRef = React.createRef(); - lockedUsdBarRef = React.createRef(); + percentUsersBuysPackRef = React.createRef(); - netPresentUtilityRef = React.createRef(); + userBuyPerYearRef = React.createRef(); + + dollarPriceStickersRef = React.createRef(); render() { return (

Introduction

+

- The Status Network has a utility token, the Status Network Token - (SNT). What does that even mean? What utilities does it have and how - do their uses affect the rest of the ecosystem? Does it impact value? - What even is the value of a utility token? -

-

- These questions are hard, and there does not seem to be sufficient - academic answers to them. The technology enabling a “utility token” is - new, and transcendent of many older technologies. This consequently - means the models used to evaluate the older technologies will never be - able to completely describe the newer ones. We, as a community, need - to build new ones and evaluate them rigorously. -

-

- There is currently quite a bit of work being done in this field, but - it is mostly for investment firms to make appropriate capital - allocation decisions among a diversified portfolio of cryptoassets. - While this is drastically important for growth and project funding, - there is a lack of research on capital and resource allocation inside - of a single network. More specifically, any utility token needs to be - able to objectively evaluate various features and utilities of their - platform, and how they affect their ecosystem. For instance, we need - to be able to ask questions like: - - “How can we objectively measure the difference in the rate users use - feature X in Status and its respective impact on the ecosystem?” - -

-

- We will be launching Status with the following SNT use-cases, as - described in the{' '} - whitepaper and{' '} - the website: -

    -
  • Teller Network
    • -
  • Tribute to Talk
    • -
  • ENS Usernames
    • -
  • Sticker Market
    • -
  • SNT Curated Dapp Store
    • -
  • Liquid Funding (may not be available at launch)
    • -
  • Network Incentivization (launching after V1)
    • -
  • User Acquisition Engine (launching after V1)
    • -
-

-

- Each of these features leverage the SNT token, but in very different - ways. For instance, some features will require staking, some will - actually burn the token, and some will incentivize sending and - receiving. This means each will have differing effects on the supply - and demand of the token itself, and will need to be modeled - differently. It doesn’t stop there as Status is an open and - permissionless platform for developers to build on and use, which - means that anyone can build SNT use-cases that affect the overall - supply and demand. But how do we know what effect a utility has? Where - do we go to try and evaluate its usefulness? -

-

- To this end, we are starting a blog series detailing some of the - research we are doing within Status to objectively evaluate the value - flows of SNT, the potential effects of our implemented (and upcoming) - SNT use cases within Status, and how our potential user growth impacts - SNT. This work will encompass traditional economic and finance theory, - work currently being done in crypto-economics, and novel methodology. - That means a part of this endeavor is an attempt to get peer review - and evaluation of what we do by you, the community! -

-

- - DISCLAIMER: The work in this article (and mentioned notebooks) is - for modeling purposes only. The numbers herein are not to project - actual values locked up in Status and should not be used for - investment advice. It is our strict desire to create and improve - models that describe value flow of SNT use-cases (and similar token - use-cases), and how these use-cases compare to each other. - -

-

- Let’s start with the ENS naming system. In Status, for a little SNT, - you can register your username on the Ethereum Name System (ENS) so - others can find you easily. In order for us to apply models or - understand the economics of a use case, we first have to understand - what it is, how it works, and how it fits within the Status ecosystem. - Let’s start by breaking down how ENS usernames work within Status: + Let’s start by breaking down how the Sticker Market work within + Status:

    -
  1. User selects a unique username, {``}
    2. -
  2. User deposits 10 SNT into the ENS username dapp
    3. -
  3. - User is granted sole control over the subdomain {``} - .stateofus.eth for 1 year -
    4. -
  4. - User is able to get deposited funds after this yearly period, and - release the username back into available names. -
    5. -
  5. - User is now searchable within Status as {``} or - {``}.stateofus.eth outside of the Status app. -
    6. +
  6. Artist posts a Sticker pack for sale
    7. +
  7. Artist sets price of sticker pack
    8. +
  8. User purchases Sticker pack for use
    9. +
  9. User uses Stickers in Sticker pack in chat

-

- The use case and token flow are both relatively simple, but what are - the effects on the network? Let’s first try and model what value this - could potentially accrue over time. We can start by picking out the - variables in this process to see how things depend on each other. - Furthermore, the above values are what we currently use, but in terms - of modeling, we should turn those into variables that allow us to see - what effect each has on the overall mechanism. This can help inform us - (and you) on appropriate choices. -

Discussion of variables

Number of Users

- It is clear that this all depends on how many users Status has in the - app. If they are not using Status, then they won’t use the feature. - This is our base metric, and we will model it using compounding growth - and loss. We can start with a number of users that are using the - network, and set additional growth and loss variables (in percentages) - that define how this number changes over the next 10 years. This means - that every year, we expect a certain percentage change in users based - on the numbers of the previous year. Depending on how you set those - percentages, the number of users can grow very rapidly! Go ahead and - play with the following variables to see how the number of users - change over the years. + Here we will reuse a lot of the user estimations from the previous + blog post on{` `} + + ENS usernames + + .

Conversion rate of users to ENS username

-

- Ok cool. We have our user base locked and loaded for the next 10 - years, but not everyone is going to register an ENS username. We can - brand it, make it simple, and incentivize people to do it but the - reality is that that number will never be 100%. So the number of - people that DO decide to register an ENS username is what we want. We - get this number by multiplying the total number of users by the - adoption conversion rate, which is another variable. -

-

- Now not all users will keep their usernames. Some people will remove - their deposit after the year and bring their SNT back into - circulation. Some people will leave Status altogether. If they never - manually release their SNT from the ENS username contract, it can be - considered locked forever. For this, we will continue to consider them - users because from the contract's perspective, they are - indistinguishable. We’ll model the people who release their username - with another conversion factor. Go ahead and change these variables - and see how the following graph changes. -

-
-
-
-

- US Dollar Amount of SNT to Deposit, Discount Rate, and Net Present - Value -

-

- Now the contract itself locks up a specific amount of SNT per - username, but the goal is to model around a reasonable target price in - US dollars and have the contract change over time to adapt as the - price of SNT changes. Why do we do this? In order to evaluate value - flow overtime we need a relatively stable unit by which to measure and - normalize the value flows. We use US dollars due to the size, - stability and data availability for that market. While one can argue - that US dollars do not maintain their value in the long term, they at - least depreciate at a stable and predictable rate. The mechanisms and - governance around how this price change works is a subject still under - discussion and will be addressed in future articles (but we’ve got - some really cool ideas). So the knob we choose to tweak here is the US - dollar amount of SNT to be locked up. -

-
-

- An additional factor in using the US Dollar equivalent of SNT here is - that we can add a discounted cash flow analysis based on historical - data of USD. Future notebooks and articles will look into deriving and - modeling a discount rate purely in cryptocurrency. For brevity, this - article will only introduce the concept and gloss over a good portion - of the details and derivation of the terms within. For more - information, please visit the{' '} - - more detailed workbook - - . -

-

- A simple surface level description of a discount rate is the rate you - use to figure out how much present value a known future cash flow is - worth. In other words, how to presently evaluate the amount of money - you know will come in the future. Once you have the discount rate, you - can calculate the Net Present Value (NPV), which is given by - the following formula: -

-

- - {'$$NPV = \\sum^n_{t=1} \\frac{R_t}{(1+i)^t}$$'} - -

-

- where $$t$$ is the number of time periods (10 in this - article), - $$R_t$$ - is the net cashflow of that particular time period , and{' '} - $$i$$ is the discount rate. There is also a potential - for including the initial cost ($$t=0$$) of the - project. We are purposely not including this as Status absorbs the - investment cost for the network. There are quite a few subtle - arguments here around things like hurdle rates, payback periods, etc, - but we defer them and their potential utility to a future article. - Anyway, the concept of discounting future value has been around for a - long time. The earliest known reference was in the 6th century BCE{' '} - - Proverbs of Ahiqar - - : -

-
- A sparrow in thy hand is better than a thousand sparrows flying -
-

- You have probably heard a more common version is this, and Warren - Buffet does a good job of{' '} - - explaining it: - -

-
- How many birds are in the bush? When are you going to get them out? - and how sure are you? -
-

- Either way, more details on how we can do this will be explained in a - future article. Below is a knob to change this discount rate. The - higher the rate, the more unsure you are about the future income. Play - with both of these knobs to find out how much money will be locked up - in the ENS username contract over 10 years. -

-
-
-

- and all of this gets summed together to give you the NPV of ENS - Usernames within Status. To be more explicit, the NPV is the present - value of something based on a projection into the future. Based on the - values chosen above, we arrive at an NPV of: -

-
-
-
-

- In other words, after setting all of the above model inputs we have - finally come to a way of looking at how "impactful" ENS - usernames are in a single value. This value will become more useful as - we build out other models for other use cases so we can compare them - and see relative differences. Eventually, we will be able to see the - relative impact a given utility within Status has within the entire - ecosystem. -

+

Example Scenario Analysis

-

- It is also useful to look at how this number changes as we tweak the - input variables to see their impact. As an example, let's look at - what happens if we are able to do something to increase the number - Status users who actually register an ENS username (actually currently - in the works). This is an example of the question we postulated in the - beginning of this article. The default value is 50%, which leads to a - NPV of $45,745,047.00 (holding all default values constant). -

-

- What happens if we're able to increase this number, say, to 75%? - Keeping all other variables equal, this change alone changes the NPV - to $74,335,701.00, which is a 62.5% increase. -

-

- As another example, let's look at what happens if we increase our - yearly growth rate, going from 300% per year to 350% per year. Holding - everything else constant, with a 350% growth rate per year, we come to - NPV of $129,104,065.00 which is a 182.2% growth and would constitute a - superlinear relationship due to the effects of compounding growth. - Based on these two simple examples, it is clear we should spend more - time on user acquisition and continuous growth over increasing ENS - username conversion rates (OR BOTH!). -

-

- As you can see, by making models of our SNT use-cases, we can start to - ask questions and get numbers to give us actionable data (assuming a - decent accuracy of the model). Even if the actual numbers are - drastically wrong, but the relationships are correct, we can still - come away with quality information on how we spend our time, money, - and effort. -

+

Thoughts and Conclusions

-

- So what have we learned from all of this? How can we change the model - to better fit reality? Are their any actionable conclusions around ENS - usernames that come from this information? -

-

- As stated previously, this particular use-case and work done lay the - groundwork to build more complex models of the SNT use-cases. It also - helps introduce the concept of how different variables affect growth - and impact over time. If you plan to follow this series and work, we - suggest making sure you understand each step along the way because all - of this can get complicated fast. At the very least, we hope you have - been able to grasp a little of what goes on behind the scenes at - Status. -

-

- You have probably noticed that the default values for each variable is - not justified anywhere. This is a problem that we plan to face by - using historical data to make justified default values. Right now, we - have a toolset to see what happens when we change variables, but not - what those variables should be based in reality. These - workbooks are living documents that will change over time to include - such work. -

+

Call to Action

-

- Our goal is to continuously improve these methods and create more work - not only around ENS usernames, but with the entire SNT ecosystem. This - means we would love to get feedback from you, the community. If we - have done something incorrectly, or you know of some way to better - model various aspects herein, please join the discussion. We will be - posting all of these articles in{' '} - our discuss and linking around - the internet in relevant places. -

-

- If you are interested in the models created here and want to see more - detail, please see the more detailed notebooks on{' '} - ObservableHQ. There, you can - play, edit, and fork the notebooks for your own use cases. We would - love to hear your feedback! -

-

+

Future Improvements and Articles

  • probability of failure
  • justifications using historical data
  • assign variables and create equations for each
    • -
  • discussion around initial cost, hurdle rates, payback periods
    • +
  • variable sticker prices and popularity
    • +
  • market fees
);