Blockchain analytics is the discipline of analyzing public blockchain data to extract intelligence about transaction patterns, address ownership, and fund flows. Unlike traditional financial analytics, which relies on private bank records, blockchain analytics works entirely from publicly accessible data: every transaction on Ethereum and Bitcoin is permanently recorded and readable by anyone. The challenge is not accessing the data — it is making sense of it at scale. The core techniques in blockchain analytics are transaction tracing, address clustering, and entity labelling. Transaction tracing follows the flow of funds through a chain of transactions: given an address of interest, trace which addresses sent it funds, which addresses those received from, and how far back the chain extends. This allows analysts to identify whether funds in a wallet ultimately originated from a known bad actor, even if they passed through multiple intermediate addresses. Address clustering groups multiple wallet addresses that are likely controlled by the same entity, based on behavioral patterns in their transactions — common input ownership in Bitcoin, or consistent gas payment patterns in Ethereum. Entity labelling maps specific wallet addresses or clusters to known organizations: exchanges, DeFi protocols, bridges, mixers, and flagged entities. These labels come from a combination of public information (exchange deposit addresses are published in blockchain explorers), voluntary disclosure (companies sharing their addresses for compliance purposes), and intelligence gathering (addresses identified from darknet monitoring, law enforcement data sharing, and user reports). The output of blockchain analytics — a risk score, a list of flagged counterparties, a fund flow diagram — is what exchange compliance systems use to decide whether to accept or investigate a deposit. Understanding how this works helps you understand why your wallet might be flagged even if you believe your activity is entirely legitimate.