A better way to price new domain names and usernames on web2 / web3
What’s in an online name? Back then all we had was im names and domain names. There was no value in im names, the more mysterious the better; but domain names were super valuable. Now, Usernames, nametags, hashtags, cashtags whatever you call it are more popular. Every new platform, legacy or web3 now has them.
When a new initiative which requires users to register IDs launch, all usernames are mostly offered at same price. Are all usernames equal? In the real sense of it, no, but then the platform lacks data to support how to price for a name.
Let’s take the domain name industry, when a new project launches, the registry created a sunrise people in which people can buy domains that are trademarked to them, the. followed by a landrush period where domains are offered at a premium price.
In a lot of registries, some domains are also set aside as premium — since the registry considers them to be valuable. The domain name space has still best tech in that industry but clearly archaic for obvious reasons, it’s a finite list that doesn’t possess feedback mechanisms to keep the list updated based on new/outgoing trends.
There’s a lot of interesting propositions on how to do this better or more importantly how to make pricing sustainable overtime as value of these assets don’t stay the same.
I want to focus on how to solve for pricing at state zero of a project. Raisin d’etre there’s already data in the world that one can rely on to some degree and get a sense of value.
I will put the nominal value of a name at 1, then run it through a set of boost criteria. The more data we have from the real world that can boost value the more multipliers the name gets.
I would probably put together a script and open source this — hope it inspires or form the basis for someone’s project out there. If you are also interested in helping here; feel free to hit me up. Collaborators always wanted.
Variables and their respective multipliers.
— — —
- Registered Trademarks : 8
- Known human names: 8
- Length of name: for 0 < length < 10, multiplier= 22 — (2*length)
- Known organization name: 12
- Conjugation of known human names (2, first and last name): 4
- Names where a Twitter/Instagram/ENS/Tiktok Handle with same same name of more than 5000 followers exist: 5. (chose to keep this weighting low and non-dynamic to avoid people or organizations being punished for their own success.
- English word found in the dictionary: 6
- .com of the phrase exists : 4
- None of the above: 1
This, here is a good start. Hope this sparks something in the domain space and move the world along a better direction wrt better username pricing.
Are there interesting data points I missed? Thoughts on improving this? Comments welcome.
