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ICO TOKEN DISTRIBUTION & ECONOMICS

ICO TOKEN DISTRIBUTION & ECONOMICS

Usually, a percentage of the tokens is sold to ICO participants and a percentage kept for the company’s needs. The token distribution and allocation of the token is usually a chapter in the future company whitepaper. A pie chart displays how and to whom tokens will be allocated. But how much tokens are allocated (amount) and what are they used for? how much token should I spend for advisor? is 15% of all tokens too much for founder? How many company use reward pool and what is the best size?

I’m trying to answer all these questions at https://ico.tokens-economy.com/distribution/ You can discover how much token are given for pre-sale, main sales, or reserved for particular needs across a bit less than 900 ICO!

 

After analyzing 896 ICO, up to 24 main categories used to describe token distribution have been identified:

advisors, airdrop, bonus, bounty, burned, community, company, crowdsale, ecommerce, foundation, founder, investors, legal, lockup, marketing, operations, pool, premined, presale, referrals, research, reserves, team

The tedious work was to get the data and map categories (people used a huge amount of synonyms: up to 1936 unique words/sentences, including typos) down to 24 categories!

Some examples:

  • crowdsale: ico, sales, crowd sale, crowd-sale, free sale, ico round, main-ico, coinsale, coin sale, ico token, public, …
  • bounty: ico bounty, bug bounty, gift, bounties
  • frozen: frozen, lock-up, vesting, lockup
  • and the list goes on….

After that, graphing all these values was easy thanks to #google charts API 

I will update the data regularly, so keep visiting this page in the future.

How it was done

  • Data are stored in Google Sheet, 2190 ICO, read from Whitepapers using PDFBox.
  • A category parser read and match token distribution categories (> 1936 unique words/sentences) and their respective values
  • A category reducer reduce the number of categories to a more manageable number by mapping similar category together. E.g. Early Bird investors -> preico
  • A category analyzer can query these data using multiple category selector strategies.

What’s next?

I will improve the category reducer over time to catch more and more synonyms and increase the coverage of ICO taken into account by the category analyzer.

I plan to export the rules used in the category reducer and display them beside each pi chart soon.

Feel free in comments to give me your feedback

About The Author

I worked with various Insurances companies across Switzerland on online applications handling billion premium volumes. I love to continuously spark my creativity in many different and challenging open-source projects fueled by my great passion for innovation and blockchain technology.In my technical role as a senior software engineer and Blockchain consultant, I help to define and implement innovative solutions in the scope of both blockchain and traditional products, solutions, and services. I can support the full spectrum of software development activities, starting from analyzing ideas and business cases and up to the production deployment of the solutions.I'm the Founder and CEO of Disruptr GmbH.

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