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Story Time with HyperArc

No more static dashboards. Tell stories.

HyperArcAnalytics
February 15, 2024
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Zuye ZhengCTO, Co-founder
February 15, 2024
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A dashboard with numbers going up is cool, but it’s far more useful to be able to ask, "Why?" and, "What’s next?". To do that you need to be able to tell a story with your data. Our DataApps allow you to do just that, to discover and tell your story and share it with the world (or just your team).

Storytelling with Dashboards

The ability to discover and tell your own stories with our dashboards is why we branded them DataApps (and we were being a bit extra). Currently, the ubiquitous dashboard in Web3 only presents a frozen slice of the blockchain — sometimes with a few prescribed parameters. But we believe dashboards can be much more.

We wanted to make sure our dashboard creators could build reusable apps for their users to discover and tell their own stories. And we wanted to make this as simple as possible without code and parameterizing SQL.

In HyperArc, all you have to do is compose queries about the different facets of the story you want to tell in a dashboard. Since our queries are built and stored as semantic ArcQL* — as opposed to SQL — interactions are automatically configured (some might even call this AI).

(* ArcQL is just marketing for the metadata representation we use to capture your intent when you use our query builder.)

Let’s start with a query trending monthly active wallets and add another about total transactions across projects. Without doing anything more, this DataApp allows me to build a story about the interactions between these two facets. I can select a subset of projects to compare, which filters down the monthly active wallets to those specific projects. I can then select individual projects on anomalous days and see their impact on the total transactions above. Every interaction is a real-time query of the blockchain through our engine, and gone are the days of stale and cached data and having to manually refresh a dashboard.

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From here you can keep adding to the depth of the stories you can tell with more queries. We extended what we had to build a full DataApp around wallet analysis to understand the acquisition and retention of wallets segmented by cohorts of age. Using the same simple interaction from above, we can now compare ParaSwap, SushiSwap, and ShibaSwap for wallet acquisition and retention.

We see in the bottom chart that although ShibaSwap is not the strongest in wallet acquisition (last among the 3), it’s actually one of the strongest in wallet retention. Whereas ParaSwap has the best wallet acquisition, it starts to lose market share month over month as the wallets age, while ShibaSwap increases its overall percentage.

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Delving further by selecting the bars for month 0, we see a median monthly transfer for new wallets of $26 — a trend that is also decreasing.

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Selecting the bars for month 24, we can compare it to wallets that are 2 years old and still using the protocols, to see a median transfer of $420 (nice!) — a trend that has been much more stable.

From a quickly composed DataApp, we’ve discovered and can now tell the story of the value of wallet retention in DeFi.

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This DataApp can then be forked to add facets for a sequel — maybe we want to explore a story around transfer amounts or the type of users signing up through wallet age at acquisition.

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Customize Your Story

The default interactions we infer from the semantics of ArcQL might need to be tweaked a bit, but this is all possible in the dashboard builder. You can customize how each query interacts with every other query with emit and receive all the way down to how global filters are applied and merged. You can even go more advanced in our interactions builder and define how things should work across datasets in each dashboard. All of these interaction customizations are explained in app as you build so just click around!

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Cast Your Story

Now you’re ready to tell your story, and HyperArc Stories will help you do that. From any DataApp you can use our Story Builder to narrate a story with data that can be shared anywhere with your team or the world, from Slack to Farcaster as an interactive Frame.

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Check out this cast (and accompanying blog post) on the impact of Farcaster Frames on Base and Optimism from our very own David Zhou.

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Next Steps