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Token Terminal Launches Methodologies: Transparent Onchain Metrics for Crypto Investors

Token Terminal Launches Methodologies: Transparent Onchain Metrics for Crypto Investors

If you've ever wondered how those slick onchain metrics for your favorite crypto projects are actually calculated, you're not alone. Token Terminal, a go-to platform for crypto fundamentals, just dropped a game-changer: Methodologies. This new feature peels back the curtain on the entire process, from raw blockchain data to polished financial and usage stats. No more guessing—it's all laid out for anyone to audit.

Token Terminal Methodologies launch screenshot featuring Aave protocol metrics

The Challenge with Onchain Data

Let's face it, blockchain data is a beast. Raw transactions, smart contract events, and function calls don't magically turn into revenue figures or user activity stats. As Token Terminal points out in their announcement thread, there are layers of processing involved. To get accurate metrics, you need a deep dive into each protocol's business model and how it logs activity onchain.

For instance, think about a DeFi lending protocol like Aave. Calculating its revenue isn't just summing up fees— it involves tracking specific contracts across multiple chains and versions. Without transparency, investors are left in the dark, unable to verify or compare numbers across projects.

Illustration of the problem with multiple processing layers in onchain data

Traditional methodologies often boil down to a single vague sentence, which doesn't cut it for serious analysis. Token Terminal highlights how this lack of detail hinders benchmarking and auditing, especially as crypto goes mainstream.

Diagram showing contracts, events, and raw data included in metric calculations

How Methodologies Solves It

Enter Methodologies: an AI-powered tool that documents every step with precision. It's not just a static doc—it's continuously updated and verified by Token Terminal's research team. Each metric breaks down into three parts:

  1. Overview: What the metric actually measures. For example, revenue for Aave includes fees from various streams like lending interest and protocol fees.

  2. Data Sources: The exact blockchain elements used, such as transaction logs from Ethereum, Avalanche, or other chains, plus specific events like deposits or liquidations.

  3. Step-by-Step Calculation: How raw data gets aggregated, normalized, and turned into the final number.

This setup makes it easy for anyone— from casual traders to institutional investors— to understand and trust the data.

Critique of traditional one-sentence methodologies in crypto data

Why This Matters Now

Token Terminal's timing is spot on. With their robust data pipeline and AI agent, they can handle thousands of metrics across hundreds of projects without breaking a sweat. This isn't just for show; it's crucial as institutions like CF Benchmarks use these standardized methods for regulated products.

For meme token enthusiasts, this transparency could extend to understanding onchain activity in viral projects. Imagine auditing trading volumes or holder metrics for the next big meme coin with the same rigor applied to blue-chip protocols.

Overview of Token Terminal's AI-powered methodologies solution

Plus, project founders can now offer stakeholders the same level of reporting clarity, building trust in a space often plagued by hype over substance.

Structured sections of each methodology: overview, data sources, and calculations

Looking Forward

Token Terminal's vision is bold: making onchain data more reliable than traditional finance. With everything verifiable on the blockchain, this could set a new standard. And the cherry on top? Methodologies are free for all users—head over to their platform to check it out.

Explanation of why methodologies are launching now with advanced infrastructure

In a world where data drives decisions, tools like this empower everyone from blockchain newbies to seasoned pros. If you're diving into meme tokens or broader crypto, keeping an eye on verifiable metrics could be your edge.

Blend of data engineering and AI for precise metric documentation Growing need for verifiable onchain data in institutional crypto

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