Bridger Destinations

    Q5. Where do people go when they bridge to Polygon from Ethereum? What are the 10 most popular first destinations for Polygon addresses that have just bridged from Ethereum?

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    Introduction

    This dashboard consists of three main parts:

    1. I will first investigate what users do when they bridge out of Ethereum - which labels are interacted with the most.
    2. As Hop Bridge is the bridge used mostly on Ethereum, I will then look at the daily metrics for this bridge: the daily number of unique users, the daily number of transactions and the daily amount of USD bridged - all coloured by the token type.
    3. Finally, I will focus on the destinations that users choose after they bridge to Polygon: what label types, subtypes and address names are interacted with the most as soon as users reach their destination, Polygon.
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    I first began my analysis by looking at the top 10 destinations when users bridge to Polygon from Ethereum. My first thought was to look at the dim labels table and filter out the required transactions, however, I quickly came to the realisation that this is not the right way to filter out only Polygon transactions, and therefore the pie chart on the left shows bridging destinations when users are leaving Ethereum (and are going to layer 2 networks). In order to get a clearer analysis, I had to filter the data out using certain contracts, which is shown in the later section of this dashboard.


    The most insightful aspect that we can see here is that Hop Protocol is the bridge used the most by users who are leaving Ethereum. The other destinations are nowhere close to the USDT Hop Bridge contract, which at the time of writing has over 135M transactions! In the next part of this dashboard, I will focus only on Hop, since it is the most used bridge by Ethereum users - but this time, I will look specifically at the Ethereum → Polygon bridging transactions.

    Hop Bridge: Ethereum → Polygon Analysis

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    Key points:

    • The count of unique users tells us that users are mostly bridging MATIC to Polygon, which makes a lot of sense conceptually. High fees on Ethereum mean that users don’t want to be swapping/transferring MATIC on Ethereum, and therefore bridging it to Polygon, given that it is its native token is a very wise choice.
    • The count of transactions also tells us that USDC is being bridged a lot, followed by USDT which accounts for just over 10% of the total number of bridging transactions.
    • The total amount of USDC bridged is the largest sum from all of the tokens bridged, with the total sum being almost $95M - that’s a lot of money bridged!
    • The scatter chart can be used to visualise the correlation between the count of transactions and of how much USD is being bridged on a daily basis. We can see some points where this correlation is very strong, where a big number of transactions signifies a big amount bridged - but also points of no correlation. Those points imply that there are days where a lot of money is bridged in a few transactions, which in turn could signify the presence of whales in the ecosystem, who bridge very large sums in fairly few transactions.

    What do users do after they bridge to Polygon?

    The next step is to deep dive into what are some of the first transactions users conduct once they reach their destination - Polygon.

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    Key points:

    • Quite surprisingly to me, we can see that a lot of users bridge to Polygon to use SushiSwap, possibly to use Kashi markets or swap for certain assets. I have written a dashboard that analyses the growth of Polygon thanks to Sushi, which is quite relevant here - as we can see that a big number of users bridges to Polygon to use Sushi!
    • Label type tells us that users mostly bridge to use DeFi and ‘token’ - which could signify swapping for different assets without the need to spend a lot on fees, which are present on Ethereum.
    • Lastly, the most interesting aspect that we can grasp from these pie charts is the fact that a lot of users use the USDC and WETH contracts, which could mean that they bridge tokens such as MATIC or USDC to Polygon to then swap for WETH (MATIC, USDC → WETH) or for USDC (MATIC → USDC).

    Conclusion

    This dashboard has investigated two major aspects: the overall briding behaviour, what happens when users leave Ethereum by looking at the labels table, as well as the bridging metrics, such as the unique users, daily transactions and amount of USD bridged, all coloured by the token type. The final part of this dashboard focused on what users do once they bridge to Polygon - what contracts they interact with the most, what labels have seen the most interactions. We have seen that a lot of users bridge to Polygon to avoid high swap fees on Ethereum, as well as to use SushiSwap and Aave.

    This dashboard has been written by Nat. 💙