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Use Case

Find Smart Money Activity

A research group verified 40 leaderboard wallets and kept only 11, turning a noisy signal source into a usable research queue.

2 min readupdated 2026-09-02

/ quick answer

A small research group pulled 40 'smart money' wallets from analytics leaderboards and tried to follow all of them, drowning in activity with no way to judge which wallets were actually skilled. A research group verified 40 leaderboard wallets and kept only 11, turning a noisy signal source into a usable research queue.

A research group verified 40 leaderboard wallets and kept only 11, turning a noisy signal source into a usable research queue. A small research group pulled 40 'smart money' wallets from analytics leaderboards and tried to follow all of them, drowning in activity with no way to judge which wallets were actually skilled. Outcome: 29 of the 40 wallets showed profit concentrated in one or two positions, or patterns consistent with launch access — both non-replicable. The remaining 11 produced roughly 8 researchable events per week instead of 200+, and every event now arrives with liquidity context attached. This use case node is part of the Onexial knowledge graph and links to related concepts, workflows and tools below.
Situation
A small research group pulled 40 'smart money' wallets from analytics leaderboards and tried to follow all of them, drowning in activity with no way to judge which wallets were actually skilled.
Workflow Applied
Outcome
29 of the 40 wallets showed profit concentrated in one or two positions, or patterns consistent with launch access — both non-replicable. The remaining 11 produced roughly 8 researchable events per week instead of 200+, and every event now arrives with liquidity context attached.
/ frequently asked

What is the Find Smart Money Activity use case?

A small research group pulled 40 'smart money' wallets from analytics leaderboards and tried to follow all of them, drowning in activity with no way to judge which wallets were actually skilled.

What was the outcome?

29 of the 40 wallets showed profit concentrated in one or two positions, or patterns consistent with launch access — both non-replicable. The remaining 11 produced roughly 8 researchable events per week instead of 200+, and every event now arrives with liquidity context attached.

Which tools were used?

Nansen — wallet PnL and labels, Dune — custom concentration queries per wallet, Claude — behavioural profiling from normalised transaction exports, Make — filtered alerts to a shared channel.

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Related concepts

The vocabulary this page depends on.

  • Smart Money

    Smart money is a label for wallets with a documented history of profitable, early positioning — a research filter, not a signal to copy blindly.

  • On-chain Data

    On-chain data is the public record of every transaction, balance and contract call — the raw material for wallet tracking and market research.

  • Whale Wallet

    A whale wallet holds a position large enough that its trades move price or signal intent — which makes it worth watching and easy to misread.

  • Wallet Tracking

    Wallet tracking is the practice of monitoring specific addresses and getting notified when they trade, transfer or interact with contracts.

all dictionary

Related workflows

Turn this into a repeatable process.

  • Smart Money Tracking Workflow

    Build a curated wallet watchlist, monitor it for meaningful trades, and use alerts as research triggers rather than buy signals.

  • Analyze A Wallet With AI

    Turn a raw transaction history into a readable profile: strategy, holding periods, risk behaviour and realised performance.

  • AI Crypto Research Workflow

    A repeatable research loop: turn a question into market data, on-chain evidence and a written risk view before any position is considered.

  • AI Token Research Workflow

    Screen a token in under 30 minutes: contract facts, liquidity structure, holder concentration and a written risk verdict.

all workflows

Related tool stacks

The tools that run it in production.

  • On-chain Research Stack

    Explorer, indexer and analytics layers combined so wallet and token questions get answered with verifiable data.

  • Smart Money Stack

    Wallet tracker, on-chain analytics, alert delivery and an AI layer that turns raw wallet events into researchable signals.

  • AI Research & Knowledge Stack

    Default toolset for analysts, founders and creators doing deep research with AI.

all tool stacks

Related prompts

Reusable prompts for this job.

  • Smart Money Analysis Prompt

    Tests whether a group of 'smart money' wallets is genuinely informative or a survivorship-biased label.

  • Wallet Analysis Prompt

    Turns a transaction export into a behavioural profile: strategy type, timeframes, risk pattern and whether the wallet is worth watching.

  • Token Research Prompt

    Structures a full token due-diligence pass: mechanics, liquidity, concentration, bear case and unverifiable claims flagged explicitly.

  • Whale Tracking Prompt

    Interprets a large transfer correctly by classifying counterparties before concluding anything about buying or selling.

all prompts

Related use cases

How people apply it, and what came out.

  • Research A Token With AI

    A structured AI research pass cut token screening from three hours to 35 minutes and produced documented passes instead of impulse entries.

  • Create An On-chain Alert System

    A purpose-built alert pipeline with enrichment and deduplication achieved a 30% action rate, versus near-zero for off-the-shelf feeds.

  • Track A Whale Wallet

    A trader replaced noisy whale alerts with a labelled watchlist and counterparty classification, cutting alerts by 94% while keeping the useful ones.

  • Analyze Wallets With AI

    AI profiling of 60 candidate wallets cut a week of manual review to an afternoon and identified 4 worth monitoring.

all use cases

Comparisons & alternatives

Pick between the options.

all comparisons