Learn the “Data Quantitative Analysis Framework” and “Research Qualitative Analysis Logic”, you can basically discover and capture the value of NFT and its tokens in the NFT industry, and effectively identify the various opportunities in new NFT projects .
Original title: “How to invest in NFT track through data? 》
Written by: NFT Labs
Nowadays, NFT is experiencing explosive growth, but while users are paying attention to this track, they always feel that the information in the NFT world is relatively scattered, such as hundreds of domestic and foreign NFT exchanges on different chains. This makes it difficult for people who have just entered the NFT field to have a macro understanding of it immediately, so it is very important to understand the comprehensive data of the track.
At present, CoinMarketCap and CoinGecko have become an entrance to find NFT-related data, knowledge and essential information. This form of platform is usually called “Data Aggregator”. “Aggregation” can help users directly capture The vast majority of content value.
Therefore, for any enthusiast who wants to learn more about NFT, they can form a clear thinking framework for the NFT industry through data framework and qualitative analysis.
Data quantitative analysis framework
Horizontal data-time dimension
In the horizontal dimension of data, it is divided into historical data, recent data and current data . For example, the historical NFT market trends in 7D/30D/90D and the latest NFT market performance. By observing the time axis, it is important to understand the corresponding data fluctuations. In addition, some cumulative data, such as each project and total cumulative transaction volume, total holders and other data are also worthy of reference.
Longitudinal data-like comparison
In the vertical dimension, the comparison between NFT types/items is also very important . In terms of project types, investors also need to understand the market share of different NFT fields, such as the current market share of various NFT types such as trading cards, artworks, collectibles, and virtual worlds. The proportion of transaction volume of specific NFT projects is also worthy of attention, and even the total transaction volume of some top projects will exceed half. Through these data, users can easily determine whether the project is currently in the first echelon or the second echelon. The weekly turnover is also worth paying attention to, such as whether it is more than 100,000 US dollars or more than 10,000 US dollars.
Particle data-subdivision indicators
In addition to the macro market data, we also need subdivision data to understand NFT projects more specifically.
For example , the number of visits to the project details page, the frequency of the search results, the number of traders, the number of transactions, the number of NFT holders, and the activity of the community . For a certain NFT asset, users can also learn about historical transaction prices, purchasers or sellers, etc. through historical transaction data.
With the support of these data, investors can more easily hold, manage and invest in NFT assets. For example, in the recently popular Bored Ape Yacht Club, the issue price of each monkey is 0.08 ETH, and their subsequent price fluctuations and changes.
We can also judge the potential of specific NFTs based on market transaction records. In the NFT market, we can find past transaction data. Although historical data may not predict the future, it can be used as a reference standard for pricing when selling and buying .
In addition, the number of visits to the project details page, the frequency of the search results, the number of traders, the number of transactions, the number of NFT holders, and the activity of the community can also be used as influencing factors to help you make better investment decisions.
Token Data-Investment Opportunities
In terms of NFT tokens, it is necessary to understand its market value, transaction volume, market situation, project ecology, community construction, etc., which projects have greater potential, how much the project’s rate of return, how big the average increase, and how In the time dimension, which items have the largest increase and so on.
Study qualitative analysis logic
In addition to analyzing NFT data, what other aspects do we need to judge the investment value of NFT? There are the following three aspects for reference.
Practicality
The first is practicality. The practical value depends on how the NFT is used . The two main categories with high utility value are game assets and tickets. Another aspect of practicality is the ability to use NFTs in different applications. Imagine that if you can use the same asset in different games, then the value of this type of NFT will be relatively higher.
Ownership history
Second is the ownership history. The value of the NFT depends on the identity of the issuer and previous owner of the NFT . NFTs with high historical value of ownership are usually created or issued by well-known artists or companies with strong brands. You can find the address of the whale holder and list the other NFTs they own as an indicator reference.
fluidity
The third is liquidity. High liquidity means higher value of NFT . Liquidity is one of the factors that measure whether NFT has higher value. NFTs that meet ERC-721 or ERC-1155 standards can easily be traded with anyone holding ETH in the secondary market, which increases the number of potential buyers to a certain extent. Investors may be more inclined to invest in the NFT category with large trading volume, because liquidity reduces the risk of holding NFTs. In the extreme case where NFTs lose their practical value after the relevant platforms are closed, as long as someone is willing to buy and sell, high-liquid NFTs still have value. On the other hand, NFT standards that are not based on Ethereum are affected by lack of liquidity, and the value of NFTs created on these platforms is often discounted.
Discover value, capture value
Let’s take the data on NFTGO as an example to further analyze several key points of the dimensions of the data.
First of all, we need to pay attention to the NFT market data of the whole network . This includes real-time network-wide NFT transaction and asset data, including NFT market value, total transaction volume, total transaction volume, and the number of NFTs and their holders, which are used to determine the overall market trend and popularity of NFTs.
Second, you can look at the market data trends of the past 7 days/30 days/90 days, as well as the buyer and seller market ratios, and use these macro data to judge market supply and demand.
As mentioned above, NFT liquidity, which reflects the turnover rate of NFT to some extent, is a very important indicator. This concept is also relatively common in the stock market, and the turnover rate is usually used to measure the liquidity of a stock. The higher the turnover rate , the more active the trading of the stock, the higher the overall quality, and the more investment value.
The concept of liquidity is similar to this, and the ability of NFT to be smoothly realized at a reasonable price can be measured based on this indicator. Especially for those who do not plan to hold NFT for a long time and want to obtain income through NFT trading, liquidity indicators are indeed one of the data that must be paid attention to.
The current NFT market distribution and popular projects are one of the important data dimensions, so as to intuitively understand the hottest NFT subdivision areas and projects in the current market. Whether it’s a novice who just understands NFT or an investor, these data can help quickly establish a basic understanding of the NFT world. At the same time, by checking the proportion changes, you can quickly find popular items and perceive the changes in the NFT market trend .
NFT leaderboard
Most of the above-mentioned data are in some macroscopic dimensions, and granular data on the micro-level also need attention. What are high-value projects and assets? Who are the NFT giant whales? What is the investment value of NFT and NFT Token?
The most typical is the ranking of NFT projects, including the value ranking of NFT, the ranking of the fastest value-added projects, and the ranking of asset value.
In terms of sorting dimensions and methods, in addition to the dimensions of market value/growth/number of transactions/trading volume, the liquidity indicators mentioned earlier. Through sorting, you can basically quickly find the NFT projects with the highest market liquidity at present, and capture potential investment opportunities.
In addition, it is worth mentioning that the giant whale rankings. In addition to quickly knowing the number and value of the giant whale’s NFT holdings, it can also spy on the specific NFT held by the giant whale and buying trends. Some friends around will indeed choose to follow the pace of the giant whale and understand the whereabouts of important players in the market. This is also a key part of exploring market trends.
Although this does not constitute a scientific basis for investment, by understanding which NFTs the giant whale holds and which NFTs have been purchased or sold, you may be able to discover some investment opportunities .
NFT metadata / natural language search
Metadata is also called Metadata. Each NFT pass will have its own Metadata URl, which defines some more detailed information about the NFT, such as the name and description of the NFT, the URL of the picture, and special attributes. Take Bored Ape Yacht Club as an example. Each ape has a different color, shape, name, etc. Searching through metadata can help users quickly locate the target NFT range.
For example, by entering “Bored” in the search box, you can view the Bored Ape assets of the entire network. For a large number of search results, you can further subdivide and filter the dimensions in the left column, and further refine the search results from the three dimensions of category/project/blockchain. At the same time, it can also be sorted by current price/creation time/transaction time.
Click in a single NFT asset, you can know its basic properties and understand all historical transaction information, including the number of transactions, transaction time, historical prices, historical holders, etc. When making an NFT purchase decision, you can use the historical information of the NFT, especially historical holders. It is worth mentioning that whether an NFT has ever been held by a giant whale or a celebrity may also be a key decision basis for NFT valuation.
After talking about data dimensions, let’s talk about data depth. We need to understand the basic information of the project and the current market performance, such as market value, transaction volume, number of issued NFTs, holders, and liquidity.
In short, market data is the core of all modeling and analysis tools, not only for understanding the market, but also for correlation analysis between various products, such as NFT+Layer2, NFT+DeFi, etc.
Finally, it is crucial to understand what gives the value of NFTs and their tokens. Regardless of the field, assessing risks from different perspectives and thinking, and identifying various opportunities in new NFT projects, is a kind of ability, but also requires better tools.
