What Is an NFT Floor Price?
The most simple definition of an NFT floor price is that it is the lowest price for any NFT in a given collection.
In this article, you’ll learn:
- What an NFT floor price is meant to achieve.
- The simplest way to calculate an NFT floor price.
- Additional factors in NFT floor pricing.
- Advanced ways to calculate NFT floor prices.
- How standardized NFT floor prices can bring DeFi and NFTs closer together.
NFT Floor Price Meaning
Generally speaking, NFT floor prices are an attempt for market participants to glean insight into the fair market value of an NFT project at the collection level. This helps focus an NFT buyer’s decision-making process and analysis by stripping away in-collection factors such as rarity, traits, and more.
The easiest way to calculate an NFT floor price is to take the lowest-priced NFT in a collection. For example, on Opensea, the Bored Ape Yacht Club (BAYC) NFT collection has a floor price of 72.69 ETH because that is the lowest listed price for a BAYC NFT on the marketplace.
How NFT Floor Prices are Calculated
There are a variety of ways to calculate NFT floor prices. The most straightforward way is to take the lowest value of an individual NFT in a collection, as mentioned above.
Let’s say the lowest price for a random NFT collection is \$20. This makes \$20 the de-facto floor price. If someone buys the NFT, the next lowest-priced NFT (an NFT priced at \$30, for example) represents the new floor price, and the floor price increases to \$30. If someone lists an NFT below \$20, the floor price decreases to the price set by that NFT.
Expanding Past Basic NFT Floor Pricing
An NFT collection’s floor price might initially seem like a simple and effective indicator of the lowest possible value any given NFT holds. However, there are a variety of additional factors to consider when attempting to truly gauge an NFT collection’s floor price.
NFT marketplaces often have different floor prices specific to the NFTs listed on their platforms. In the screenshot of LooksRare’s BAYC collection page below, the floor price is listed as 72.69 ETH. However, additional information shows that LooksRare is matching Opensea’s floor price, and the platform’s floor price is actually 73.88 ETH. Thus, calculating a more accurate NFT floor price necessitates scouring multiple platforms to account for marketplace fragmentation differences.
Liquidity is a widely used financial term that refers to how easy it is to exchange an asset. With NFTs, liquidity refers to how easy it is to sell an NFT and exchange it for a token.
For example, consider liquid assets such as tokens and stocks. If an exchange displays a digital asset’s price, anyone can likely sell it instantly at, or close to, that price. The same is not true for most NFTs. A good NFT floor price model should account for differing levels of liquidity. One of the best ways to do this is to factor in recent NFT sales, which provide insight into both the real price and frequency of NFT sales in a collection.
Basic NFT floor pricing is easily manipulated by outliers. For example, consider a situation in which 99% of an NFT collection is trading at 10 ETH, but there is an influx of multiple NFTs listed at 3 ETH.
The NFT floor price immediately drops to 3 ETH, which, while technically true when considering how NFT floor prices are often calculated, doesn’t accurately represent the general floor price for the NFT collection. Gaining a more accurate NFT floor pricing model requires removing outliers from calculations, as they tend to divert the floor price from what it’s intended for—giving a broad view into the fair market value of an NFT collection.
Some NFT collections, often those which are low-priced, can be subject to price manipulation in the form of mass buying. Referred to as “sweeping the floor” in NFT communities, groups or wealthy individuals can make a concentrated effort to raise the floor price. In this scenario, the floor price is defined as the lowest-priced NFT in a collection as priced by marketplaces.
Another way to manipulate the price is through wash trading, where an individual trades their own NFTs. Simply put, a group or individual with enough NFTs can manipulate the price by listing their own NFTs on a marketplace for a more expensive price, and then buying them to artificially inflate the price.
Both of these methods intentionally mislead prospective NFT buyers into believing that the fair market value of an NFT is the new floor price when in reality the price is not a result of natural demand. This is harder to factor in compared to other NFT floor price factors, and requires NFT buyers to do their due diligence on NFT ownership metrics, market sales, project community, and more.
Advanced NFT Floor Pricing
Given the number of factors relevant to an NFT’s actual floor price compared to the traditional method, a number of NFT analytics projects aim to provide users with more reliable and accurate NFT floor price data.
The most common methods are listed below. These techniques are not used on their own, but are combined in various ways by different NFT data analytics projects. Thus, how projects employ these methods is important to understand.
NFT data analytics projects that provide floor prices usually aggregate data across notable NFT marketplaces to maximize the number of data points available to reliably calculate NFT floor prices.
A key consideration for marketplace aggregation is quality. Marketplaces with low liquidity, and by association low adoption, are often omitted from calculations. Low-liquidity marketplaces provide less reliable data, which can dilute the high-quality data coming from established marketplaces during the aggregation process.
Generally speaking, historical averages take past NFT sales from a set period (one month, one year, etc.) and compute the data to estimate the NFT floor price in the present and future. For example, a historical average-based floor price can take the average of the 5% lowest-priced NFT sales in the past 30 days. The average can then be combined with other methods to arrive at a final floor price, which is made available to users.
Key considerations for historical averages are time period frequencies, data points available during the period, average calculation methodology, and more. Each of these has a significant impact on a floor price’s reliability, especially in volatile market conditions.
Outliers and Wash Trading Filters
NFT data analytics projects filter out outliers and wash trading. The most important aspect of doing this is to accurately identify and separate genuine market activity from illegitimate transactions.
The Need for an NFT Floor Price Standard
The fast-growing NFT ecosystem is constantly producing novel frameworks for NFT floor pricing. However, in today’s environment, users and developers must navigate a variety of NFT data analytics projects, each with their own way of calculating NFT floor prices. There’s little to no standardization on which NFT floor pricing methodology is the best to use.
The lack of an NFT floor price standard inhibits innovation. For example, NFT lending and borrowing, where an NFT holder locks up their NFT as collateral to borrow fungible tokens, requires that the NFT collateral is secured by a widely adopted floor price, necessary to power reliable liquidations that protect the lender.
A standardized NFT floor price feed will become core infrastructure for the Web3 ecosystem, powering NFT derivatives, lending and borrowing protocols, efficient NFT pricing, NFT comparables, and more.
Achieving NFT Price Standardization With Chainlink
Chainlink provides seamless, time-tested, and trust-minimized data infrastructure necessary for any NFT floor price feed to reach the crucial inflection point for adoption. Much like how Chainlink Price Feeds have become the most widely adopted standard for price data in the DeFi ecosystem, projects aiming to bring about a new era of NFT pricing are encouraged to leverage Chainlink and its inherently blockchain-agnostic design to expand the scope of their data offerings and reach projects and users across the multi-chain ecosystem.
Using Chainlink, projects building NFT floor price feeds can monetize their data by making it available to thousands of developers, join high-quality NFT price floor data providers on the Chainlink Network like Coinbase Cloud, and bootstrap widespread adoption for their NFT floor price data. If you’re a data provider looking for new markets, or an emerging NFT data analytics firm aiming to get your data product in front of developers, talk to an expert today.