Good afternoon! In today's edition, we wanted to know about the crypto data that would make a big difference in the jobs of folks working around the ecosystem. Questions or comments? Send us a note at firstname.lastname@example.org
Executive director at the Blockchain Association
The crypto industry hears a lot of unfounded pushback from critics that there isn’t — or can’t be — a meaningful number of people working in crypto in this country. As executive director of Blockchain Association, a Washington, D.C.-based trade association representing the sector’s leading investors, companies, projects and protocols, I know from experience that there are thousands of brilliant minds from various industries that have come into crypto over the past few years: Putting a hard number to those converts would be very helpful in our conversations in Washington.
Across our nearly 100 member companies, there are currently more than 2,100 open jobs, including software engineers, communications experts and government relations professionals. However, we don’t have hard figures on the number of currently filled jobs across the industry — and the industry’s economic impact on the United States’ economy. It would be incredibly fascinating and useful to know how many people have come to crypto from Web 2.0 or other industries, where those jobs are clustered — especially given the remote, decentralized nature of the industry — and which cities are seeing the biggest growth.
Blockchain Association is working to compile this data across its membership and hopes to make it a resource for the larger industry in the future. By highlighting the number of builders, developers and innovators in this space — and the industry’s overall economic impact — we can demonstrate to Washington that crypto is here for good.
Cryptocurrencies have moved to the mainstream. Companies have built large crypto positions while crypto-native businesses are multiplying around the world. Our customers from across this spectrum tell us that they need the financial management tools that help them enact international payments or respond to subtle market FX shifts; not just for crypto, but for fiat too. They may, for example, need to on-ramp with fiat and settle a payment somewhere else in the world with crypto. To make that as quick, secure and efficient as possible, they need an institutional-grade window on crypto market data.
As a research analyst, aggregated on-chain analytics would be the most useful as they are the most difficult to get and play an integral role in research. For blockchains, a time series of metrics such as issuance, burn rate, daily active users, daily transactions, etc., are the most useful. A tool that can combine and compare these metrics across different chains would allow for easier comparisons. Additionally, smart-contract data for decentralized finance applications would be even more useful as it’s not readily available and the developers don't usually post any analytics.
Comparing similar KPIs over time such as supply-side revenue, protocol earnings, emissions, unlock schedules and monthly active users would allow for better relative valuation analysis. Currently, revenue and earnings data is scarce and differs between sources — doing data extraction for these can be tedious as each app uses its own terminology for different metrics. Diving deeper, sector-specific metrics such as those for lending protocols like borrowing volumes, utilization rate, liquidation levels, lending rates, etc., would shine some light on borrowing activity within DeFi. Lending is the lifeblood of an economy, and greater detail would help to measure different risks among the lender and borrowers. Sectors like decentralized exchanges, bridges and asset management would also benefit from more granular data to see which tokens are most traded and where these tokens are moving. More activity continues to move on-chain, so I expect this data will garner greater demand as it continues to become more valuable.
Kevin McAllister ( @k__mcallister) is a Research Editor at Protocol, leading the development of Braintrust. Prior to joining the team, he was a rankings data reporter at The Wall Street Journal, where he oversaw structured data projects for the Journal's strategy team.