Empowering on-chain data to remove barriers of information
Before going into who I think will use our platform, I’d like to first introduce our team and background.
We’re a team of serial internet entrepreneurs. We always loved working with data. We started with blockchain in 2017.
At the beginning of this year, we developed our first DeFi app, and we wanted to track data, such as the number of users participating in different pools, TVL, growth trends, yield, etc.
As crypto investors, we’re no strangers to running into problems due to a lack of data. For example, we’ve lost money because we couldn’t keep track of the flow of funds.
We’ve missed out when looking for new investment opportunities due to the lack of information. Without understanding invested funds, there is no way to calculate APY.
So, we needed tools to help us understand our investments better, to get objective and accurate analyses to optimize our strategy.
Our efforts towards this
We tried several data analysis platforms, namely Nansen and Dune. But as time went on, our needs changed.
Nansen focused on token and address analysis. Dune had more data, but the data was too low-level and required writing code to get it, making it very difficult to use.
That’s when we recognized an enormous opportunity in the market for a tool for the majority of people interested in or working in DeFi.
There’s a ton of data out there, but no way for the retail investor or newfound crypto enthusiast to dive in.
As the center of gravity of the finance world shifts to DeFi, we realized somebody had to do this, and we believe we have the tools and resources to meet this challenge.
And that’s how Footprint Analytics happened! We launched it officially in August 2021.
If you use the platform, you should get a sense that we’re trying to build it to be easy to use. You can start making blockchain and crypto analysis dashboards in a few minutes.
Also, it’s not only for creators and analysts, but their viewers/friends/clients/etc. We’ve included many features that make it easy to share charts and dashboards.
We imagine that many people will start by exploring different charts and dashboards. Then, they will get curious to try and become contributors themselves.
Some examples of data that users can explore in Footprint are TVL, market cap, revenue, token distribution. There are transaction data like volume, slippage, gas fees, etc.
Finally, we have pool or pair data, such as interest, fees, revenue APY, etc.
Why is data analysis essential in the blockchain? And how can we use this data?
Our team comes from a securities background, doing data analytics for major traditional financial institutions.
In that world, it is tough to interoperate data between different exchanges, institutions, and individuals, but there are many highly sophisticated firms that try.
Because of user privacy and compliance regulations, it’s tough to obtain data. Data owned by the institution itself is the barrier, and the data analysis tools are just an accessory.
It is challenging and highly costly for ordinary people or institutions to break this barrier. It’s impossible to get some very essential information.
With DeFi, the problem is reversed. There’s tons of data on the blockchain. Most of it is decentralized and open, and anyone can access it.
Therefore, compared to traditional industries, we—as crypto and blockchain investors and developers—have some advantages.
We make more objective and reasonable judgments and decisions based on more accurate and comprehensive data.
But people have a hard time gathering and understanding all of this data.
Each chain has an underlying consensus. Also, each platform has another contractual mechanism. Users do not have enough capacity or resources to achieve the “comprehensiveness” and “accuracy” mentioned earlier.
Data analytics platforms can help people solve this problem.
Wallet analysis is another area with a lot of potential for blockchain investors. However, wallets are distributed in different places, along with investments, across lending and yield farming platforms.
Users need a good platform for data parsing, integration, and application.
Footprint is a data aggregation container that dismantles data from different chains, platforms, and pools and then presents it to the user conveniently and visually.
Users can go to Footprint and see real-time as well as historical data from the address and pool view. We want Footprint to be a reliable, usable, and dependable analytics tool for our users.
Where does Footprint’s data come from?
Is it just from chain analysis, or are the data sources crawled from various platforms? Is there any crowdsourcing?
Our data technology is our huge advantage over everyone else in the industry and it requires some explaining to understand.
The short answer is:
We get our data from on-chain data parsing. We develop models to parse data automatically to generate basic metrics. Based on the basic metrics, we use our automatic calculation model to generate derived metrics. We also use open-source data plus parsing to accelerate our data aggregation.
Here’s the long version:
The data on the blockchain is open and traceable. All blockchain records include all the information necessary to track its origin and trajectory.
For example, which address initiated the transaction when it occurred, the amount of the asset transferred, which address received the asset, and how much fee was incurred.
While all data is traceable, cross-chain and cross-platform data, with different developers, also makes the same meaningful data “personal”—i.e. adding their own unique touches to the data.
This leads to data cleansing becoming more difficult.
As mentioned earlier, data parsing is like the room where the sausage is made. It’s hard, it’s messy. When we started Footprint, there were already some platforms ahead of us.
We were in the process of catching up with others, trying to find ways to improve our efficiency and overtake them. In just two months, we iterated on 10+ standard models for data parsing.
The models we have built so far are the flow parsing model, the contract parsing model, and the event parsing model.
Rather than just piling up manpower and developers, we have built unique, highly automated, efficient, and intelligent tools which are our superweapons.
For example, if a new platform emerges, it probably takes others 1-3 weeks to interpret and analyze the platform. Our automated tools can parse and analyze it and produce hundreds of metric calculations within one day.
In terms of technical solutions, we believe in digging deep and building platforms from day one. This is not just about looking far ahead, but about taking LEGO thinking and open source to the extreme. Gradually, we want to leverage the power of the open-source community to fill resource and technical shortcomings, as well as motivate users and developers to contribute data and reports to the platform. This is the only way we’ll be able to come out of a smooth iteration curve, and to realize our goals. That is: a faster platform, faster new models, faster coverage.
What are your strengths compared to competitors like Nansen and Dune?
Our data sources and technical solutions are our main strengths.
It’s a bit like what Elon Musk said about Tesla—that Tesla’s long-term competitive advantage will be in manufacturing.
We think about our business in the same way. We want to build the tools that build the tools.
Footprint Analytics is like our Gigafactory. On the basis of that, we will be able to create investment tools that can directly help people get better returns on their crypto and blockchain investments.
We hope to become a data analysis community in the future, not just a data portal. We believe that in blockchain, tools should also be decentralized. The tools will be created by users themselves, and our first project, Footprint, will enable that.
When it comes to Dune, we appreciate their idea of crowdsourcing tagging and table making, but we have an edge in terms of UX. To put it bluntly, our platform is much more user-friendly.
Without intermediate tables, analysts need to understand SQL to use Dune. Our solution is drag-and-drop, you can make a table in minutes. This low barrier to entry is why hundreds of users have created thousands of dashboards last month alone.
Do people need any skills when using the Footprint platform for data analysis? What advice do you have for people who don’t know data analysis?
The Footprint platform has the following features.
- Customizable reports. Drag-and-drop, easy to use, no code required
- Forkable reports. Easy to modify and ready to use, with one-click sharing support
- Cross-chain, multi-platform data support
- Drill-down analysis tools that support multi-dimensional analysis.
For users who do not have a background in data analysis, I recommend using pre-built templates. We have a strong team of analysts who are constantly producing and updating analysis templates on different topics.
In the future, we will also incentivize our community to create their own projects. This will greatly increase the scope of what’s available.
At the end of the day, never forget that data analysis is a tool, not an end in itself. You’re trying to solve real investment problems. We believe that learning blockchain analytics is an incredibly valuable and rewarding skill for the future. However, it’s OK to ask others for help. That’s why both the “tool” and “community” aspects are important for us.
Will you be tracking specific NFTs projects? Or maybe NFT deals?
NFTs are something that we’re super excited for.
Our team isn’t driven by trends, but by data. And the data suggests that NFTs are going to be a major segment of the blockchain world.
Wherever there is demand from our users, we shall go. (And you can believe there’s a lot of demand here.)
NFTs actually have extensive data development and parsing groundwork for data analysis tools, so we are setting up a new team to enter this vertical independently. We hope to make our big release in October.
Note: Any interested people, teams or investors—we welcome your interest, don’t hesitate to get in touch.
At the same time, we are also applying for some project side grants that can help us as a startup team to speed up development.
What do you think about the GameFi space?
We’re keeping a close eye on this. It’s exciting to see what Axie has done with its whole ecosystem.
I mean, the potential is obvious. On the internet, as we know it, gaming has always been a huge market. GameFi allows game data to be overlaid with financial attributes so that games are connected to real life. Let’s just say we’re very optimistic about the future of GameFi.
Did you know that one sandbox plot of land sold for $863,000?
This July, the growth of active Gamefi wallets grew by 121%, with over 800,000 users participating in blockchain games.
With these kinds of numbers, we owe it to our community and users to stay ahead of GameFi developments.
Where do you think DeFi and NFT are headed? Will they replace CEXs?
We believe traditional finance is an excellent springboard to enter the world of digital finance investing—after all, that’s how we got started.
Having our feet in both worlds, we believe that “symbiosis” will be a better way to describe the relationship between CEXs and DeFi, not “replacement”.
E-commerce did not replace traditional offline marketing, but rather they now compete with each other, both developing in tandem in innovative ways.
“Symbiosis” also seems to be more in line with DeFi’s Lego-like qualities. Different projects and developments exist on top of each other and create new and more exciting objects (I’m inclined to think of NFTs as one example of this DeFi Lego.)
DeFi is still at a very early stage of development, and I believe it has a long way to go before becoming as convenient for most users as CEX. I’m talking about transaction depth, fees, speed, etc.
What’s Footprint’s future roadmap?
In the previous two months, version 1.0 became a powerful and easy-to-use analytics tool for discovering and visualizing blockchain data.
Since then, we’ve been working on more data access, better (and more) visual charts and deeper insights into derived data. In the next two months, Footprint plans to provide more metrics by accessing real-time data from ETH and BSC. Footprint will also support Pool analytics.
Then, there’s also our NFT plan—stay tuned for that.
Going forward, we will continue to expand our pool of data by extending data from the Polygon and Solana chains and tracking return on investment data for wallet addresses, among other things.
We believe that Footprint’s potential is more than just as an analytics platform, but also as a pool of aggregated data, the value of which can be mined for investment (funds, private equity, etc.), industry insights (VCs, consultants), and platform operations (i.e. the financial institution’s own internal operations).
But at the end of the day, great products are user-driven, and what you think about us is more important than what we think. So, we welcome you to use and experience the platform, and we are grateful for all feedback. Our team looks through ALL the suggestions we get—we take it very seriously—and adjust our product accordingly.
Finally, how do you see the future development of data analytics in blockchain?
Let’s look at a set of figures: Of the world’s 7.8 billion people, 4.6 billion are internet users, and 100 million are crypto users. DeFi users are just over 3 million, and crypto users account for about 2% of the population compared to internet users, which is a tiny percentage. DeFi users are up 800% year-on-year, which is a very high growth rate.
And as we talked about earlier, we believe that, as a complete ecosystem, the future space of blockchain is enormous. In such an ecosystem, infrastructure building is crucial, including public chains, exchanges, data analysis platforms, etc.
There is still a lot of room for infrastructure. The overall industry size is proportional to the network scale effect (for example, as the number of addresses increases, transfer transaction pairs grow exponentially.)
Unlike with traditional finance tools, where the users themselves are secondary to the data, a decentralized ecosystem puts community at the center. The data analysis industry needs to think about how to organically combine foundational data (accurate, timely, comprehensive), data application (scalability, convenience), and community (decentralized characteristics).
Finally, regardless of whether it is a centralized or decentralized data analytics tool, data has to be transformed into action to solve real problems. We are very excited to see several analytics tools being built around analytics scenarios. The field is booming, to keep it short, and we expect Footprint to have a place.
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