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At the inaugural DuneCon, Dune’s first conference, I shared a presentation on the state of crypto in 2022.

I aimed to characterize the health of the crypto ecosystem at the most basic level. For example, quantifying the number of active wallets, the population of active developers, & other dynamics within the ecosystem.

The slides are embedded here with summary commentary below and linked here.

My Top 15 Observations from the Data:

1. 2.5m wallets are active daily across web3. Flat wallet count likely means relatively constant GDP in the ecosystem. We need more products to attract new users to bring in more GDP.
2. Binance, Solana, Polygon, & Ethereum wallets represent more than 80% of those daily active users.
3. Centralized exchanges manage roughly 100m total active wallets.
4. Trading volumes are down 60% which is mostly driven by asset price reductions. DEX average transaction size declined from $8k to $1.4k.
5. Centralized & decentralized exchanges trade at the same multiple & move in lock step.
6. NFT buyers outnumber DEX traders about 35:1 over the last 6 months but the traded volume is roughly equal between the two groups.
7. NFT trading volumes have fallen 97% from the top.
8. 40% of NFT buyers use Solana. Because the average Solana NFT is worth 10% of the average Ethereum NFT, Ethereum retains 90% of NFT traded value.
9. L2s (Arbitrum & Optimism) account for 30-40% of all transactions on Ethereum, but consume only 2% of the total gas, cementing their value.
10. About $250m flows into L2s each month.
11. MEV (maximum or miner extracted value) has tapered off due to FlashBots’ searchers. Lower MEV means users pay lower fees when they trade because the market is more efficient.
12. Developers push about 300,000 smart contracts to Ethereum every month, a figure that has been flat for the last five months.
13. Roughly 5,000 developers push code to web3 every week, down 20% from the beginning of the year. This number needs to increase significantly for the ecosystem to thrive.
14. Web3 companies (aside from L1s) have begun to trade at similar multiples to their web2 counterparts.
15. Web3 multiples are increasingly correlated to revenue. The investor community has matured its understanding of how to value a web3 company. This milestone will begin to shift the early & late stage private markets’ valuations. This is why marketing will become so critical in the next 12 months.

Overall, the crypto ecosystem finds itself in a winter. I see it as the coiling of a spring. So much innovation has been unleashed in the last few years, most of us are still absorbing the implications & working to identify the best applications of the 4 fundamental innovations of web3.

Today, Adobe announced its intention to acquire Figma for $20b, valuing the business at 50x current ARR, the highest multiple paid for any software company of scale. Congratulations to team Figma on building their impressive business.

Doesn’t this acquisition reset the market price despite this year’s 70% correction?

After the correction earlier this year, public valuation multiples had reset to those of 2017. That year, Cisco acquired AppDynamics for 17x trailing revenue. If we assume a company recognizes about 2/3 of its ARR as revenue, then I estimate the Adobe/Figma deal at roughly 75x trailing revenue.

Ten years ago today, I wrote a post titled “Choosing market segments on customer profitability.” How healthy are the business’s underling customers?

Today, that question matters more because of the recession than at any point in the last decade.

Selling to very profitable customers benefits a startup. Account executives can charge a highly profitable company more than one without much money. I compared the profit margins of selling to a grocery store, a restaurant & a software company to illustrate the point.

This chart holds the secret to successful hiring of go-to-market teams.

What is it? A stack rank of attributes within HubSpot account executive candidates that correlate to quota attainment. Preparation, adaptability, domain experience, & intelligence topped the list. Closing ability correlated negatively. The pushier the account executive, the worse the result. That result alone should encourage rethinking of AE interviewing.

By my rough estimation, there are approximately 30m monthly active web3 users (getting closer to that 100m user mark!) The activity rates of those users mirror web2 finance apps.

MixPanel recorded the activity rate of web2 finance apps at 10.7% DAU/MAU. In other words, 11% of users who use the app every month, also use it daily.

Dune Analytics provides insight into the DAU / MAU of Ethereum users for August.

During Bill Binch’s Office Hours, he predicted many more software startups would achieve 200% net dollar retention. In other words, the average customer’s spend would double each year. I’ve only seen a handful of companies achieve that mark. The most notable public company is Snowflake which routinely reports NDR of 171%.

Large NDR figures are hugely beneficial to startups. They imply strong product market fit. They provide predictable revenue growth. They result in better capital efficiency, an important metric in this environment.

This chart shows the relationship between the top 100 public projects’ revenue and their trailing revenue multiple. There’s none. The correlation asymptotes to zero. At least when looking at the ecosystem as a whole.

But let’s break the data down by category into the top 5 by revenue: L1s (blockchains), DEXs (decentralized exchanges), Credit (lenders), NFT Marketplaces (buy & sell Bored Apes), & Yield Aggregators (systems to maximize interest rates on deposits).

The summer of 2021 marked an influx of dollars & interest into web3. Since then, the fourth crypto winter has dropped snow atop web3, but the revenue decline isn’t equal across web3 software.


NFT marketplace revenue collapsed 62% since the beginning of this year. This chart shows the decline in monthly revenue from January to August. L1s’ monthly revenue has followed NFT marketplaces downward, falling 57%.

The parallel revenue drop suggests L1 revenue skews to NFTs today, likely upwards of 75% concentration.

Last week, I presented an overview of the fundraising market at the Traction Conference in Vancouver. The slides are embedded above & linked here.

My brief narrative of the slides follows

The current state of affairs arose as a result of the Global Financial Crisis. Since 2008, the US experienced an unabated 12 year bull market fueled by four waves of money printing which increased US money supply by 30%+. This experiment culminated with Covid. The supply chain shocks combined with many more dollars fueled inflation, which the Fed is fighting by raising rates.

In many board rooms, the most important go-to-market number this quarter is pipeline health.

For some companies, the pipeline may be less clear than a quarter or two ago. Summer seasonality may play a role. Macroeconomics might also be lurking within the numbers.

Pipeline fluctuations are normal. But any meaningful & unexpected surprise warrants introspection. Pipeline analysis often has four parts:

1. Craft the sales sandwich to predict your GTM conversion rates & determine if close rates have changed in parallel. Sales cycle plays an important role: if conversion rates remain the same, but if sales cycles double, the pipeline initially thought to be for this quarter isn’t ready to close for a half-year.
2. Build a lead generation calculator for your business using those conversion rates to understand how much lead volume the GTM engine requires to attain plan.
3. Employ Bill Binch’s Mojo Metric as a daily measure of pipeline health for the sales team. The mojo metric captures the net daily change in pipeline across new deals, expansions, & sales cycle changes.
4. Perform a second order pipeline analysis to understand where pipeline deviations start. A single pipeline number, say $7m doesn’t mean much. But $7m ready-to-close this quartery with 80% belonging to the ideal customer profile on a $1.5m bookings number means the company is about to crush its target.

Pipeline segments across five dimensions: