Crypto Market Size Map

We previously talked about Gauntlet’s product vision — a platform to help people build secure and successful blockchain protocols and applications. This is fairly broad, and while it guides the work that we do, it doesn’t answer all of the questions we have about prioritization. We view what we are building as critical infrastructure for the blockchain space, and we want to scale this to as many people as we can, as quickly as possible. This means we need to build a product that solves shared problems, and that we need to figure out which sectors within the space are going to be the most important to serve first. We looked around to see if there was any good market research on:

1. How many blockchain companies there are, and what they are working on
2. The “market size” for each sector within blockchain

We scoured around, and didn’t find anything that had the data we were looking for, so we embarked on a path to collect and analyze that data ourselves. This proved difficult, as most of the data that we found was incomplete or inconsistent. However, we did our best to collect and combine this data into something informative and meaningful. It occurred to us that other companies building infrastructure in the crypto space — or other people following the market like investors — might also be interested in this data. Today, we are going to share it:

** Link to this interactive visualization **

We’ll also explain our methodology, which might help people understand this data a bit better. Lastly, we’ve published this to a public Github repo, where people can update and fork this data set as well as the accompanying visualization themselves:

Data Repository

There’s more info on where this data comes from in the repo, though most of it is from CoinGecko and State of the dApps. One caveat — though we spent quite a bit of time on this, we realize we’re likely missing a few projects and have some errors. Hopefully, by sharing the data, we can allow other members of the crypto community to contribute and help make things more complete and correct.

Insights

It’s best to explore the data yourself, but we’ll include a few excerpts from the data set:

• DeFi is the dApps/ smart contract vertical that has the strongest traction, it’s not even close. No surprises there.
• On top of that, there are a ton of DEXs. This was a surprise. 31 of the 84 DeFi projects we identified were distributed exchanges
• Proof of Stake protocols have raised 10x what proof of work protocols have, though PoW has 40x the market cap. Even without bitcoin, PoW still has 4x the market cap of PoS.

Understanding the Graph

The visual layout of the graph is directly determined by the questions we wanted to ask. We’ve created a hierarchical cluster (also known as an icicle graph) to help us answer questions about the market size. We hope to use this to answer questions like “What if we created a version of our product targeted for a particular market ?” Let’s say we are going after stable-coins — drilling into dApps, then Finance, then stable-coins show you the number of players in the space.

For more information, maybe to answer a question like “How many people in this space could pay $100,000 for this tool?” You can switch tabs (at the top of the visualization) to view other metrics like Market Cap and Funding, though we are still collecting this data (hence the “alpha” tag).

For these other metrics, we encountered a lot of incomplete data. We used this to create a lower and an upper bound on the size of each sector:

• The lower bound was the sum of the known values
• The upper bound is the average of those values extrapolated to the unknown data.

For example:

• A sub-sector has 10 projects, 5 of which have raised a total of $10mm, then the lower bound is $10mm, and the upper bound is $20mm.
• This “upper” bound is obviously not a true upper bound, or particularly accurate, but it does help when comparing two sectors with very different data availability

We’ve added the data for the upper bound in transparent cells to show how much of the size information is an estimate vs. verified

There’s still a long way to go on these other metrics, but we believe we are at a great starting point for other contributors to come in and help.

Contributing

If you’d like to contribute, you can find the repo of the data here. You can submit a pull request to:

• Correct or update an entry
• Suggest an improvement to the hierarchy
• Remove a project because you know it to be defunct or a “project of questionable legitimacy” (💩💲)
• Just add a source or verify the existing data — we could use stronger provenance for the results. It would be great to have a link to a source in every git commit.

It’s also easy fork and modify the visualization code, which is directly hosted on Observable. The easiest way to supply your own data to the visualization is to update base = d3.csv(<url>) with your own url.

In the end, we assume the market is going to grow, and we are building our product for that future, so it’s our market thesis which will drive our engineering investments as much or more than this data. However, understanding where the market is at is incredibly helpful for shaping that thesis and providing a gut-check on our intuitions about market opportunity. Hopefully others will find it helpful as well.

Thanks to Leland Lee for building the visualization and helping gather this data.