In-depth indicators that cannot be ignored in DeFi project analysis

Data can be considered the most important asset of any project, and the analysis of data can understand the past, the present, and even predict the future. However, in traditional industries, the difficulty often encountered in data analysis is that data sources are lacking or difficult to obtain.

The world of blockchain breaks the barriers of data sources. It is like a “big ledger” spread on the desktop for you to read, and the data is completely open and transparent. But it is obviously more difficult to find valuable information in the huge amount of obscure data.

There are countless tools for data analysis of DeFi projects on the market   , and there are many kinds of indicators. This article uses the indicators involved in Footprint Analytics’ upcoming DeFi 360 to summarize the overall situation of the project, and from which angles to dig into the reasons behind the data.

What: the current indicator category

The past and present performance of the project can be quickly understood through the general indicator overview. Understand the project situation and trend changes through indicators such as time-point value, increment, and rate of change.


Project Overview

I. Operational Data

  • TVL

TVL stands for Total Value Locked, which is usually the first indicator of a project’s attention. It reflects the total value of the assets mortgaged by all users. People often use the growth of TVL to judge whether the project is in an upward trend.


TVL Trend

TVL is measured in U.S. dollars, but in the world of cryptocurrencies, currency prices are changing rapidly, and it is difficult to see whether TVL’s rise or fall is caused by changes in currency prices, or more investment. Therefore, in addition to the TVL in the conventional sense, it is also necessary to pay attention to the TVL of the currency standard.

For example,  according to  the statistics of Footprint Analytics , Liquity  (a lending project that can only pledge ETH to lend stablecoins) has a slight decline in the TVL in ETH in the black box part of the figure below, while the TVL in US dollars is rising. Originated from the rise in the price of ETH. This creates the illusion that the project is going up.



After complex projects such as Aave and Yearn appear to provide both lock-up and lending functions, this also makes it more difficult for simple TVL to be used as a single indicator for measuring projects, so it is necessary to combine more indicators for evaluation.

  • Net Liquidity

Net Liquidity finds changes from the previous day by subtracting inflow and outflow data. It can be further analyzed from the two sides of inflow and outflow that the change mainly comes from the user’s entry or loss.

  • Revenue 

For example, for DEX-based agreements, the situation of the platform cannot be judged by TVL alone, and swap will also generate income for the platform. The ultimate goal of the project is to maximize profits. Revenue allows operators to understand profitability and reflect project operating results.



II. Token number setting

Most platforms will issue their governance  tokens , and some platforms will use a dual-token model. The data of token reflects the market’s recognition of the platform to a certain extent.

  • basic situation

The currency price is the most intuitive indicator. When a major event occurs, the currency price is the fastest affected indicator. The rise and fall of the currency price are also closely related to the market supply and demand. For example, Cream was attacked again on October 27, with a loss of 130 million, and the price of the currency fell.


Token Price – CREAM

For dual-tokens such as  MakerDAO and Liquity  , the amount of DAI and LUSD minted by the monitoring platform can also reflect the degree of user participation.

The market value of Token is the product of the currency price and the issuance, which reflects the market value of a project in the DeFi industry.

  • Number of holders and holding time

The number of people holding tokens reflects how many users recognize the token model of the platform, especially the data on the governance rights obtained by staking tokens reflects the situation of the platform DAO.

The time of holding the token can be seen whether it attracts more users who agree with the value of the platform or whether the proportion of speculative users is too high.

  • Application

The transaction volume data can reflect the circulation heat of the token in the market, and the ratio to the market value is similar to the turnover rate. Higher circulation reflects that the token has a certain popularity, and lower circulation is a token with insufficient attention.


MKR Volume

In addition to transactions, the use cases of tokens are also worthy of attention. Whether the tokens obtained by users’ mining are used as platform pledges to play the role of governance tokens, or are they deposited into other external protocols to capture profits.

For example, 61% of the stablecoin LUSD issued by Liquity is still stored in the Stability Pool of its own platform, and has not played its role as a stablecoin, which is far from the use case of DAI.

Why: The reason behind mining data

Once you understand how your project has performed in the past and now, you need to look for reasons for presenting the data. By drilling down on the data, we can dig deeper into the pool and users of the platform. Cross-analysis of the data can also uncover some hidden correlates.

I. Pool

In the final analysis, the overall operation data of the platform is composed of many pools. To find the reasons for data changes, you must drill down to the pool dimension and find the objects that have the greatest impact on the data. According to the ranking, the most popular pools can be found, and the future development strategy of the platform can be adjusted.


Pools Overview

II. User Metrics

Projects always revolve around users, and accurately capturing target users is the core of project development. Data classification and hierarchical analysis of users can target high-quality users faster.

  • User portrait

The overall users of the project can be subdivided into new users and active users for analysis. New users reflect the pace of platform market expansion, and active users reflect the potential for continued growth of the project.


Address Overview

The average user quality can be understood by analyzing the changes in the per capita transaction amount, holding amount and time of users.


Active Address

Although the general trend of user behavior can be observed through the average, it is still lacking as a basis for project execution. Averages tend to dilute important data, and deeper user stratification can find the real problem and develop the correct execution plan.


Trading Volume Distribution

  • User churn

“Big Whale” users are high-quality users who generate value for the platform, and preventing user loss is a required course for the project. By sorting the distribution of the proportion of users, the analysis of user portraits further focuses on large users.

Gaining insight into users’ investment preferences can gain a deeper understanding of platform users, and discover potential user groups by analyzing all DeFi platforms invested by target users.


Address Investment Protocols Distribution

III. Crossover Analysis

Drilling down into the data found the underlying metrics that affected the changes in the data, but it was still confusing why these changes were caused. Finding correlations through cross-analysis can sometimes provide evidence for the cause.

For example, compare and analyze TVL and the number of users with APY, observe the trend changes of the two, and speculate whether the increase in APY attracts more users to participate.

For another example, since most token changes are related to BTC, the analysis of price changes needs to pay attention to whether the intrinsic value of the project itself changes or is affected by the market.


Token Price (MKR vs BTC)

Or, the comparison with industry competitors can understand the competitiveness of the project in the market, and the reduction of TVL may be due to the strong attack of competitors.

The LEGO properties of DeFi cannot be ignored, and indicators that are closely related to projects are often an important factor affecting changes. For example,  Curve  TVL’s growth   has also helped Convex .


Curve VS Convex in TVL


At present, there are many analytical tools on the market, but they can only analyze the surface, and it is difficult to achieve deeper attribution. Whether the project party wants to make decisions through data, or investors do analysis, they can only obtain indicators that present results, and it is difficult to easily obtain attributable data.

The blockchain world has put data in front of us. As an operator who wants to quickly interpret data through visualization tools, he urgently needs a one-stop solution that requires no code and can obtain powerful analysis functions with just one click.

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