Analytics¶

DeFi protocols operate almost entirely blind. They can see transaction volumes and TVL, but they know nothing about the wallets behind those numbers — who they are, how experienced they are, what they want, or what they're likely to do next.

ChainAware changes that. By analysing 14M+ wallet profiles across 8 blockchains, ChainAware gives protocols genuine intelligence about their user base — the kind of understanding that allows for better product decisions, smarter risk management, and more effective growth.

14M+
Wallet Profiles

8
Blockchains

1.3B+
Data Points

<100ms
Real-time profiling

Wallet Behavioural Profiling¶

Every wallet that interacts with your protocol can be profiled in real time across multiple dimensions:

Experience Level¶

An integer score (0–100) representing on-chain maturity — from a wallet that has just completed its first few transactions to a veteran DeFi power user with years of multi-protocol activity. Use this to route users appropriately and calibrate product complexity.

Range	Tier	What It Means
0–25	Beginner	New to DeFi — needs guidance and simple entry points
26–50	Intermediate	Some DeFi history — responds to educational messaging
51–75	Experienced	Multi-protocol user — comfortable with complex products
76–100	Expert	Power user — skip onboarding, surface advanced features

Behavioural Categories¶

Classification of a wallet's primary on-chain activity patterns — Active Trader, Yield Farmer, DeFi Lender, NFT Collector, Bridge User, Governance Participant. A single wallet may carry multiple categories with relative weights, reflecting its full activity history.

Intent Signals¶

Predicted probability of the wallet's next on-chain action:

Prob_Trade — likelihood of executing a swap or trade
Prob_Stake — likelihood of staking or providing liquidity
Prob_Bridge — likelihood of cross-chain activity
Prob_NFT_Buy — likelihood of NFT purchase activity

Protocol Usage History¶

Which DeFi protocols a wallet actively uses, with interaction counts. Understand whether your users also use Aave, Uniswap, Compound, or competing protocols — and tailor your positioning accordingly.

Risk Profile¶

Behavioural risk classification (conservative through high-risk) based on leverage usage, liquidation history, and portfolio management patterns. Essential context for lending protocols setting collateral requirements and interest rate tiers.

User Segmentation (ABC Model)¶

ChainAware's segmentation model classifies wallets using the ABC framework from traditional finance — adapted for on-chain behaviour:

Segment	Share	Behaviour
A	~10% of wallets	Highest activity, volume, and protocol engagement. Generate the majority of revenue.
B	~20% of wallets	Moderate activity. Profitable but not consistently high-value.
C	~70% of wallets	Low activity, low transaction value, high churn likelihood. Often cost more than they generate in incentivised protocols.

In practice: for every 100 wallets that connect, around 10 are your most valuable future users — but without segmentation data, they're indistinguishable from the other 90 at the moment of connection.

The segmentation API also returns a walletQuality integer (0–100) for finer-grained ranking within segments — use it to prioritise waiting lists, tier access, or allocate incentives.

User Segmentation API →

Credit Intelligence¶

For lending protocols, ChainAware's credit scoring adds a fourth analytical dimension beyond experience, behaviour, and risk: creditworthiness.

The credit score synthesises:

Repayment history — prior DeFi borrowing and repayment track record
Cash flow consistency — income patterns from staking, yield, and vesting
Portfolio quality — asset holdings and liquidation history
Fraud risk — fraud probability from the same models powering the compliance stack

The result is an integer credit score that enables genuine credit differentiation — lending protocols can offer undercollateralised products to high-score wallets, dynamic collateral requirements based on individual risk, and risk-adjusted interest rates instead of a flat protocol-wide rate.

Credit Scoring API →

Token Community Analytics¶

ChainAware's TokenRank analyses every holder of a token and ranks it based on the aggregate quality of its holder community — not market cap, price, or social activity.

token_rank_list¶

Discover the strongest tokens in a category (AI, DeFi, RWA, DePIN, DeFAI) by holder community quality. Useful for:
- Research and due diligence before investment
- DEX and aggregator curation — surface quality tokens by holder strength rather than volume
- Competitive intelligence — understand which tokens are attracting the best wallets

token_rank_single¶

Deep-dive into a specific token: community rank, total holders, and full wallet-level intelligence on its top holders — balance, wallet age, transaction count, and global rank within ChainAware's 14M+ wallet network.

TokenRank Documentation →

Web3 User Analytics Dashboard¶

A real-time view of your connected wallet audience:

Segment distribution — what mix of A/B/C wallets is connecting to your protocol?
Experience level histogram — how sophisticated is your current user base?
Conversion by segment — which wallet types transact? Which don't?
Intent signal analysis — what are your users most likely to do next?
Fraud and bot proportion — what share of connections are non-human or high-risk?
Cohort retention — track which segments return and which churn

This dashboard provides the foundation for every growth and compliance decision — knowing exactly who is using your protocol before building campaigns around assumptions.

Integration¶

All analytics capabilities are available via:

REST API — programmatic access to wallet segment, credit score, behavioural profile, and token rank data
Prediction MCP — six tools for any MCP-compatible AI agent, including predictive_behaviour, predictive_fraud, credit_score, token_rank_list, and token_rank_single
Google Tag Manager — no-code integration for frontend wallet profiling at connect

Enterprise API → Prediction MCP →