MLytics - NFT Pattern Detection Automation

We found unique data sources for NFT analytics! Next, we'll create APIs and integrate existing NFT tools to allow DeFi products and any sources of signal data (such as sustainability metrics).

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Inspiration

Market volume spent on NFTs is over $20B on OpenSea alone in the past 12 months. However, most projects are not long-term.

They profit at the beginning but then they:

  • don’t grow
  • don’t provide utility for their collectors
  • don’t progress the industry

One of the problems is from the software side incentivizing only short-term metrics.

There are 3-5 main data sources and APIs used for NFT analytics, but we've discovered 10+ others that can be innovative. We're adding them to the research arsenal for picking long-term projects that help the industry and utility for their users, plus a little bit of Machine Learning magic to reveal patterns.

What it does

Analyzes unique metrics for NFT projects

How we built it

Pulled data from multiple APIs, analyzed the data, created a dashboard to show patterns.

Challenges we ran into

NFT APIs have tons of data and the main APIs are extremely limited. We'd have to track raw transaction and process it ourselves to get meaningful insights, rather than pulling useful collection data to save ourselves some steps.

Accomplishments that we're proud of

Found some unique metrics that none of the popular tools are showing.

What we learned

Have a clear goal when you have ideas that involve many data sources and many ways to potentially show data. Establish clear tasks for diverse group of contributors.

What's next for MLytics- NFT Pattern Detection Automation

  • Process the data in more meaningful ways. We discussed Machine Learning and have experience in it, but did not apply any models to current data set.
  • Add additional unique metrics that popular tools have not discovered yet (there are a few that we have and will reveal in future hackathons).

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