Professional-Grade Intelligence
The Power of Messari Pro and Enterprise
As a student of Data Engineering, you’ll appreciate that Messari isn’t just a blog—it’s a data platform. This article focuses on the “Pro” tools that allow researchers to build their own investment frameworks using Messari’s institutional-grade data.
1. Advanced Screening and Asset Filtering
Messari Pro provides a “Bloomberg Terminal” experience for crypto. It allows you to filter thousands of assets based on custom, high-fidelity criteria.
- The Asset Screener: How to build custom filters that find projects with specific criteria, such as “High Revenue with Low Price-to-Sales Ratio.”
- Watchlist Intelligence: Setting up automated alerts that trigger when a project’s treasury moves or when a major governance proposal is submitted.
- Key Performance Indicators (KPIs): Moving beyond price to track the metrics that actually matter for a protocol’s long-term survival.
2. Governance and Treasury Tracking
In the world of DAOs (Decentralized Autonomous Organizations), staying informed is a full-time job. Messari’s “Governor” tool centralizes this chaos.
- Consolidated Voting Dashboards: How to track and participate in governance votes across hundreds of different protocols from a single interface.
- Treasury Health Audits: Monitoring the “runway” of major projects to see if they have enough capital to survive a multi-year bear market.
- Voter Apathy Analysis: Identifying protocols where a few “whales” control all the power, which can be a significant risk factor for decentralization.
3. Clean Data for Developers and Quant Researchers
For those who want to build their own models, Messari provides some of the cleanest APIs in the industry.
- The Messari API Stack: A look at how developers can pull historical pricing, on-chain metrics, and project metadata directly into their Python or R environments.
- Data Normalization: Understanding how Messari cleans “messy” blockchain data to ensure that metrics like “Active Addresses” are accurate across different chains.
- Quantitative Backtesting: Using Messari’s historical data to test investment strategies and see how they would have performed in previous market cycles.