OpenSea revises its NFT rarity ranking protocol OpenRarity, launched on Sept. 21, after community controversial feedback. Some community members argued that the new rarity ranking protocol disrupts the market-driven rarity structure for some NFT collections. Meanwhile, CoinShares launch its own experimental AI bot to determine a fair price for some NFTs; however, some users appear not happy with lower-than-expected prices.
Although giving rarity ranks to NFTs on a marketplace may help collectors decide on whether to purchase NFTs, some argue that ranking NFTs may do more harm than good.
An NFT investor noted in a tweet some issues with OpenRarity, the new rarity ranking protocol implemented by OpenSea. Putting “rank” in the NFT listing with no mention of “rarity” anywhere could be misleading, the community member said.
For example, the NFT collector argued that since the Moonbirds NFT collection enabled the OpenRarity ranking protocol, it destroyed its own market-driven rarity structure, making every single NFT a “floor Moonbird.” The community member also called out Proof CEO Kevin Rose, the creator of Moonbird, to turn off the OpenRarity ranking function for the collection.
Soon after the feedback, the NFT marketplace made some revisions to the ranking system. Now, NFT listings show “rarity rank” instead of just the rank. Furthermore, the NFT marketplace has added a trait count within the ranking methodology and a way to sort items with unique attributes before applying any additional information that elevates its rank.
Following the changes, OpenSea has revealed that it will enable the rarity ranking feature to eligible collections across all blockchains starting Oct. 25. The most consistent feedback that they have received is from people asking how they could get access, the NFT marketplace said. To include more collections, OpenSea said it will be implementing the feature to all their supported blockchains.
The NFT marketplace launched the OpenRarity protocol on Sept. 21, seeking to provide a reliable rarity ranking for collectors. As a collaboration between NFT entities, the protocol aims to standardize the rarity methodology across NFT platforms.
Meanwhile, Europe-based digital asset management platform CoinShares launched an experimental artificial intelligence (AI) bot on Oct. 20 to help traders determine a fair price for some NFTs.
The experimental project, called CoinSharesNFTAI, aggregates different sets of data to provide a user with what it determines is a fair price for a rotating list of top NFT collections on OpenSea. To interact with the bot, you need to grab the OpenSea link for a particular NFT of interest and tweet this to the bot. In turn, the bot will respond with an estimated value.
The digital asset management platform said the new tool aggregates different data sets to determine how much an NFT on OpenSea might be worth. But some users weren’t happy with lower-than-expected numbers.
CoinShares says the bot runs an algorithm every week to calculate the prices of “the freshest collections.” For the week of Oct. 10-16, this includes blue chip projects such as CryptoPunks, Bored Ape Yacht Club, Clonex, Moonbirds, Doodles, Azuki, and 44 others. In the future, the bot will have permanent collections that it returns prices on, but as of Thursday, it did not list any NFT projects as a “permanent collection.”
The bot’s research paper said the algorithm builds upon the hedonic model to construct a price index from “thousands of NFT transaction records.” Its data focuses on Ethereum NFTs and uses Opensea’s official API to download the properties and past sales of certain NFT collections.
After the launch, a number of people said that the bot spitting out numbers, which in some cases were much lower than the current best offers on OpenSea. Several users expressed skepticism of the tool’s accuracy, as the estimated value of their owned NFTs turned out lower than expected.
A spokesperson for CoinShares said that while NFT pricing might seem mysterious, its prices are driven by “many factors” such as hype, rarity traits, and real-world utility.