Lately, I keep seeing people use “tags + clustering” to build profiles of addresses. To put it simply, they bundle a bunch of addresses that look related, and then slap on labels like “institution/whale/smart money.” It’s practical—I look at it myself, especially on the L2 side, where addresses constantly come and go and once batch transfers become frequent, without clustering you really can’t make sense of how the funds are routing around.

But the problems are also pretty clear: the moment an exchange’s hot/cold wallet moves, or a large on-chain transfer goes out, it gets interpreted as “smart money is doing something.” In reality, a lot of the time it’s just risk control swapping wallets, consolidating funds, moving positions for market making, or even noise generated by scheduled scripts… One wrong label, and your later inference is completely off, and you end up getting more and more confident the longer you look.

Anyway, these days I only treat address profiling as “clues,” and then I cross-check details like timing, the counterparty of interactions, and whether it’s the same set of gas habits, and so on. That’s it.