NFTGo on data accuracy
8.4/ 35% of the score
Publishes wash-trade adjustments and its rarity methodology; figures reconcile to on-chain sales for covered collections.
Journalism for the digital-asset economy
Best NFT & AI Tools · Rank 07 of 8
Collection-level analytics with rarity and whale tracking in one view
Last verified August 16, 20264 scored axes
Documented, with gaps
NFTGo scores 8.1 out of 10 and ranks #7 of 8 in the best nft & ai tools table, strongest on data accuracy (8.4) and weakest on lock-in (7.6).
A well-organised analytics suite combining rarity, holder distribution and whale activity with a usable free tier. Coverage skews to Ethereum and the larger collections.
4 axes, weighted as published in the table’s methodology. Each score below is read from the fact printed under it.
8.4/ 35% of the score
Publishes wash-trade adjustments and its rarity methodology; figures reconcile to on-chain sales for covered collections.
8.0/ 25% of the score
Coverage skews to Ethereum and larger collections, with smaller collections indexed inconsistently.
8.0/ 20% of the score
Usable free tier with paid limits published.
7.6/ 20% of the score
Exports available on paid plans; saved analytics stay on the platform.
Rarity, holder distribution and whale activity in a single interface, with wash-trade adjustments and rarity methodology published rather than asserted. For a collector doing due diligence on one collection, that combination answers most questions without opening four tabs.
It skews to Ethereum and larger collections, and smaller collections are indexed inconsistently — which is exactly where a collector most needs help, since the blue chips are well covered everywhere. Check that your collection is properly indexed before trusting a figure from it.
A usable free tier with paid limits published, and exports available on paid plans. Saved analytics stay on the platform, which is a mild lock-in rather than a serious one.
Collectors and small funds working mainly on Ethereum who want adjusted numbers and rarity without writing SQL. Anyone needing coverage of small or new collections should verify indexing first.
Verify your collection is indexed properly before trusting a floor or holder figure, then use the rarity and holder views together — concentration among a few wallets says more about a collection's floor than rarity does.
No wallet labelling and no forensic layer, so pair it with a free adjusted-sales source when the question is market size rather than one collection.
Yes, with published adjustments, and its figures reconcile to on-chain sales for the collections it covers properly.
There is a usable free tier with paid limits published. Exports and deeper analytics sit in paid plans.
It is weighted towards Ethereum and larger collections; smaller or newer collections are indexed inconsistently, so verify before relying on a figure.
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