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A Network of Network Effects — Digital Dives Vol. 49

Blockchain technology has the potential to revolutionize the way we transact and cooperate with one another online. A key driver of its success is the concept of network effects, where the value of a blockchain network increases as more users participate in it. As we saw last week, Andrew Chen, a prominent Silicon Valley entrepreneur and investor, has identified three distinct forces of network effects: the Acquisition Effect, the Engagement Effect, and the Economic Effect.

Understanding and measuring the three forces is important when evaluating the potential growth and success of blockchain networks. In today’s Digital Dive, we’ll discuss how these dynamics apply to the analysis of different blockchains by looking at Layer 1s that have demonstrated positive and negative network effects. The analysis will cover Bitcoin, Ethereum, and Tezos

The Acquisition Effect is the ability of a public blockchain to drive user growth more efficiently as the network expands. To measure this for a product, analysts track the percentage of organically acquired users and changes in customer acquisition costs over time. While blockchains do emit considerable amounts of public data, obtaining this level of granularity can be challenging because they are decentralized and open-source networks without a central authority that controls user acquisition and retention. However, we can analyze user and developer trends over time:

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Bitcoin is the oldest public blockchain and it’s also the most decentralized, which preserves security and censorship resistance. These features help the chain boast the most users, but also lead to slower development. As a result, engineers have focused on other ecosystems. Ethereum allows for decentralized applications and smart contracts, attracting a robust community of engineers that have consistently rolled out innovations. Tezos is a newer blockchain designed to be more efficient, transparent, and self-governing but has faced delays and legal disputes, which may have hindered adoption. 

The Engagement Effect involves increased levels of participation as more people join the network and is measured by considering usage metrics and retention rates of different consumer cohorts. We can get a sense of the relative standing of different chains by looking at the following metrics:

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Bitcoin is leveraging this effect nicely. We’ve seen that the project has held on to its first-mover advantage by maintaining the highest level of Daily Active Users and more people holding BTC begets evermore peer-to-peer transfers over time. The number of newly acquired Bitcoin users has nearly regained the highs of the previous bull market. Ethereum’s new user acquisition has been more muted, but it’s important to note that since the euphoria of 2021, there’s been a robust roll-up ecosystem built on top of the main chain. This has almost certainly impacted Ethereum adoption directly because the lower fees on Layer 2 are compelling to new users who experiment with the technology for the first time. Ultimately, this is still good for the Ethereum ecosystem and leverages network effects. Tezos has seen bouts of meaningful new address growth, but the chain appears to lack sufficient density to keep users engaged. Overall active addresses have receded following bursts of fresh users. 

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It’s important to note that the chart above has two vertical axes, which I chose expressly to highlight the recent spike in novel Bitcoin development. Ethereum continues to win over the greatest number of new engineers, but recent innovations in the Bitcoin ecosystem have drawn significant attention. Meanwhile, the bear market is evident on Ethereum and Tezos where new developer adds are materially below the 2022 peaks. 

A similar situation can be illustrated by looking at the value of assets locked on the different chains. Ethereum’s TVL dwarfs the other two, but the rate of change on Bitcoin is intriguing: 

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Finally, the Economic Effect refers to higher monetization rates as the network expands. Relative performance here is measured by metrics such as sales, revenue per user, and transaction fees generated.

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Again, I’ll draw your attention to the dual vertical axes which masks Ethereum’s dominance but is important to highlight the difference between Bitcoin and Tezos where recent revenue trends have moved in opposite directions. This chart also provides a stark illustration of how reflexivity in network effects is wonderful during periods of growth but can lead to economic collapse when activity slows. 

The native digital assets of Layer 1 blockchains provide a unique lens into the valuation impacts associated with network effects. As more users look to transact on-chain, they will need to purchase the token to pay gas fees, which provides a natural buoyancy to the price when positive network effects are at play. However, this bid disappears when the cycle turns and activity levels slow. Speculators add to the momentum in both directions. The result is a market-based approach to valuing the underlying networks, which is exacerbated by animal spirits, but might still have some explanatory power. 

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In the analysis above, Ethereum comes out as a leader in many respects, but the latest rates of change favor Bitcoin. The five-year token price performance of ETH and BTC has been almost identical, while the latter carries a market cap twice as large. Having said that, the gap between the two has shrunk substantially in recent years. 

Tezos hasn’t been around quite as long as the peers discussed in this note. Even still, the chain has struggled to leverage its network effects sufficiently. Since July of 2018, when XTZ was first launched, the token is down about 45%, while BTC and ETH are both up more than 4x. Tezos continues to carry a market cap of nearly $1B, which is a small fraction of the value ascribed to Bitcoin or Ethereum but is not insignificant given its seeming inability to scale up. 

It’s fascinating to see how highly correlated the assets trade despite the clear difference in their underlying metrics. This suggests an interconnectedness across the broader digital asset space. Could it be the case that what’s good/bad for one blockchain is also good/bad for other Layer 1s? This was less feasible until recently, but the Lightning Network provides an interesting way for Bitcoin to scale and there are numerous new smart contracts being deployed on the network. It seems unlikely that this development would have come about if it weren’t for Ethereum’s success in DeFi, social, and gaming dApps. Bridges and other interoperability innovations are facilitating technological diversity. It’s helpful to examine the variation in network effects across Layer 1s. However, given the interconnectedness, perhaps the broader blockchain ecosystem could also be contemplated as one large network of networks. In fact, Andrew Chen’s employer, a16z, published an analysis to this effect recently

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