What 78,181 scanned followers told us about Web3 community
The first production scan and what the numbers actually meant. Bot-Kill rates, archetype mix, and why "5,806 real community members" is the metric that matters.
Read the post →Methodology write-ups, position pieces, and operator notes — the cornerstone set, built on real production numbers, not hand-waving.
The first production scan and what the numbers actually meant. Bot-Kill rates, archetype mix, and why "5,806 real community members" is the metric that matters.
Read the post →The math of rented reach versus owned activation. Why one $50,000 KOL post will always lose to a $5,000 community activation spend on the same audience.
Read the post →Reproducibility, audit trails, cost structure. The case for rules-based archetype classification in a category that has decided language models are the answer to everything.
Read the post →Three is too few to differentiate; five collapses into noise. The full reasoning behind the archetype set, including the candidates we considered and rejected.
Read the post →Activity floor, follower-to-following imbalance, posting-burst patterns, and linguistic uniformity. The four signals that explain how 90.96 percent of the Mintlayer follower list got filtered.
Read the post →What gets verified, what does not, and how the verified-only ledger compounds into reporting your client's CFO will actually trust.
Read the post →The method, step by step: filter the bots, score real accounts on reach and conviction, rank the queue, and verify. How to surface the few hundred who actually matter.
Read the post →The four tiers of follower tooling, the two features most tools still skip (bot filtering and reproducible scoring), and how to run the evaluation on your real list.
Read the post →An operator's playbook: work the ranked queue, match the ask to the archetype, send personal outreach, verify every completion. Ten a day, no automated mass-DMs.
Read the post →Four categories that share a word but do different jobs — listening, quests, sales intel, community intelligence. How to pick by outcome instead of feature list.
Read the post →Why finance dismisses community reporting, and how to build the version that survives the room: verified actions over real members, evidence per line, cost against outcomes.
Read the post →Community work is treated as overhead because its output cannot be checked. How to reframe it as a priced, verified, defensible line item — with cascade economics.
Read the post →New posts land at the top of this list. Subscribe via @communityxos on X for the post drop.
The cornerstone list is opinionated, not exhaustive. Tell us what you would want to read about community intelligence; we will write it.