SimpleID has, since its very first prototype, walked a line between Web3 analytics platform and Web3 communications platform. We believe that both go hand-in-hand. You can’t communicate properly without understanding who to reach out to and when. But what about the why? We, as builders, tend to think we know the why. Why should we be reaching out to users now? Why this message? The why is the variable in most cases, and when you don’t solve for that variable, you are essentially flying blind. This applies doubly when making product decisions.
Analytics platforms in Web2 have long helped companies make feature and company decisions. Web3 is lagging behind here. There are some good blockchain analytics platforms out there, but most are designed to provide information to the general public or to create user-facing dashboards that provide insights into HOW something works not WHETHER OR NOT it is working.
SimpleID will soon be rolling out a new “Insights” feature that solves both problems. Understanding the why before reaching out to users will become significantly easier, and making product decisions will feel like you’ve opened your eyes for the first time. Here’s a glimpse into how it all works.
Streaming Data
In our first iteration of SimpleID, data flowed one-way. An action within the interface would trigger a process that would eventually result in the data being returned. This could be updates to segments, creation of new segments, refreshes to the dashboard and more. This worked fine when we were just starting, but as we’ve grown, we’ve recognized the need not only to be able to stream data in one direction but to stream it in multiple dimensions.
We are currently building a custom listening service that will constantly update our entire system on Ethereum block updates. Every customer will have their segments updated automatically. No more refreshing. No more waiting.
We will also be able to deliver the results of this constant flow of data not just to our client application but to other places. This creates a significant opportunity to build systems that haven’t existed in Web3. “If this then that” statements can be built from the underlying work we are doing now. It creates a flexibility that will allow you to supercharge your applications and user experience.
Parsing Hidden Data
It’s no secret that there is a lot of information encoded into transactions within a block. A single transaction against a smart contract may contain multiple events emitted from that transaction and may have kicked off multiple internal transactions. The rise of smart wallets and proxy contracts have only increased the data complexity.
Fortunately, we can parse this. Whether it’s creating insights around methods called on a particular smart contract or better understanding of how proxy contracts tie back to actual users, we are building the tools to make this easy.
These new insights can be leveraged in the form of a dashboard, segmentation, and as the mechanisms by which you communicate with users. The last point brings us to the third big area Insights enables.
Custom Monitoring
Triggers are popular among the no-code enthusiasts. With the rise of no-code and low-code solutions, being able to connect systems and fire off actions based on events has been a game-changer. Zapier, IFTTT, and others have made it easy for people to create no-code event triggers. For the developers in the world, this has always looked like event listeners. Set up an event listener, and when said event is triggered, take action.
Within SimpleID, these events will be blockchain-based, of course. We will allow you to monitor addresses for specific events and criteria. When the event or criteria is met, you can use that information to send emails, in-app notifications, or update your own internal systems with the new data.
As an added benefit, we will allow companies to pipe in non-blockchain data to help enhance this event monitoring. A concrete example of where this becomes beneficial is in collateral debt positions. An event would be fired when the CDP is opened. A company could then mix in price feed data. With those two things combined, automated messages could be created to alert users when their collateralization rate has dropped too low.
