Advanced Metrics for DeFi Project Analysis

Data is the best way to understand the past, present and future.

Data acquisition is relatively difficult with traditional finance. Meanwhile, blockchain has broken down barriers to data, giving everyone access to a huge ledger of information. However, the amount of data available caused another problem. Finding valuable information is complicated.

There are many tools out there to help people analyze DeFi Data with various indicators. However, these metrics are almost basic. This article presents the most useful metrics and more advanced data available in DeFi360, the next tool in Footprint Analytics.

Basic data

TVL is usually the first indicator people see and reflects the sum of all assets locked by the user. TVL growth is often used to determine if a project is on the rise.

TVL is measured in dollars. Cryptocurrency prices change so rapidly that it is difficult to determine whether a TVL rise or fall is due to a price change or an additional investment. Therefore, in addition to TVL, attention should be paid to tuned TVL.

For example, statistics from Footprint analysis Display the TVL in ETH Liquity (Lending program that can only lock ETH and lend stablecoin) is slightly lower in the black frame in the graph below, but TVL in US dollars is increasing. This is because the price of ETH is rising, creating the illusion that the project is on the rise.

Complex projects like Aave and Yearn that provide both locking and lending capabilities complicate the use of TVL as a metric and need to be combined with other projects.

Net liquidity refers to changes in inflows and outflows from the previous day or the previous month. Changes can be further analyzed in terms of both inflows and outflows, and whether the main source is a user’s entry or loss.

Swaps also generate revenue, so DEX-based protocols cannot be measured by TVL alone. The ultimate goal of these types of projects is to maximize profitability, and revenue reflects its performance.

Token data

Most platforms issue governance tokens, and some use two-token model. The token data reflects to some extent that the platform is accepted in the market.

Price is the most intuitive indicator, and rising and falling are closely related to supply and demand in the market. Price is also the fastest indicator to be affected when a significant event occurs. For example, Cream faced a second major attack on October 27, losing 130 million. This caused the price of CREAM to fall off the cliff.

When issuing the following dual tokens MakerDAO When LiquityYou can also reflect user participation by monitoring the number of DAIs and LUSDs created.

The market capitalization of tokens is the product of price and circular supply and reflects the market value of projects in the DeFi industry.

• Number of token holders and holding time

The number of token holders reflects the number of users who approve the platform’s token model. Of particular importance is the number of tokens bet to obtain governance rights. This reflects the status of the platform’s DAO.

Retention time indicates whether the project attracts speculators to more users who believe in the long-term value of the project.

Trading volume reflects the activity of tokens in the market, and the ratio of tokens to market capitalization is similar to turnover. High circulation reflects tokens with a high level of attention, and low circulation reflects tokens with a low level of attention.

The usefulness of tokens is also noteworthy. That is, is the mined token bet on the platform to use the governance token, or is it deposited on another external protocol to earn revenue?

For example, 61% of Liquity’s stablecoin LUSD is deposited in the stability pool of its own platform. LUSD does not serve as a stablecoin in circulation compared to DAI’s utilities.

Advanced metrics

Since the TVL of every DeFi project is made up of pools, finding the reason behind the metric means looking at the pool structure of a particular project. Example: Change pool size, TVL, and volume.

Projects are always user-centric, and accurate capture of the target user is central to project development. User data classification and stratified analysis allow you to target quality users more quickly.

Overall users can be subdivided into new and active users. New users reflect the expansion of the market and active users reflect the potential for continued growth of the project.

By analyzing changes in transaction amount, holding amount, and period per user, you can understand the average quality of users.

The average allows you to observe general trends in user behavior, but it is still lacking as a basis for project implementation. Averages often dilute important data and require a deeper user layer to find real problems and create appropriate action plans.

Whales create the greatest value for the platform and developers need to prevent these users from being agitated. By reordering users, you can create portraits of users and focus on large accounts.

Gaining insight into your investment preferences gives you a deeper understanding of your users and reveals potential user groups by analyzing all the DeFi platforms invested by your target users.

Cross analysis

Cross-analysis is a comparative analysis of multiple indicators together... Analysts and developers can use it to find correlations between metrics and create business hypotheses.

For example, if you compare APY to user count or TVL, you can analyze the results to see if the increase in APY is attracting more users.

In another example, analysts can compare the price of a project to the price of BTC to determine if the price fluctuations are due to changes in the intrinsic value of the project or due to larger market forces. increase.

Don’t miss the Lego attributes of DeFi. Closely related project indicators are often an important factor in movement. For example, Convex helped drive the growth of Curve’s TVL.

Overview

There are many analytical tools on the market, but they usually stop at the surface level metric.

In order for stakeholders to make data-driven decisions, it is important to dig deeper and apply advanced analytics to blockchain data.

Date and author: February 9, 2022, Simon

Source: Footprint analysis

What is Footprint Analytics?

Footprint Analytics is an all-in-one analytics platform for visualizing blockchain data and discovering insights. Clean up and integrate on-chain data so users of all experience levels can quickly start exploring tokens, projects, and protocols. With over 1000 dashboard templates and a drag-and-drop interface, anyone can create their own customized charts in minutes. Reveal blockchain data and invest smarter with Footprint.