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Metrics and attribution

Metrics are on the campaign page, under the workflows. This page is about what the numbers there actually are, because a metrics panel that flatters itself is worse than no metrics panel.

Three sources, in order of how much they cost you

Section titled “Three sources, in order of how much they cost you”

Activity metrics need nothing at all. They are derived from things that happened in CommandChain: a campaign moving to active records one campaigns.launched, an asset publishing records one content.published. Every tenant has these from day one.

Self-reported attribution needs a form field. Post each answer to “how did you hear about us?” to the attribution endpoint with the campaign it belongs to, and it lands as one observation carrying the answer text.

Engagement metrics need an analytics binding. With one connected and verified, a collector runs every six hours over your published assets and pulls what the provider will give it: pageviews and sessions for pages, engagement counts for social posts, opens and clicks for email. Without a binding, nothing is collected and nothing is invented.

Each metric is a card, and the headline number means one of two things.

  • Counters (posts published, campaigns launched, self-reported answers) show the running total, with the number of observations under it. Each event is one observation of value 1, so a “latest” reading would always be 1 and would tell you nothing.
  • Windowed readings (pageviews, sessions, opens) show the latest collection, with the sum across every collection under it.

Self-reported answers also get a breakdown: each distinct answer with how many people gave it, most-given first. That list is the actual output of attribution, and the count above it is only how many people answered.

The waitlist campaign's metrics: seven self-reported answers with their breakdown, and the campaign launch the loop recorded itself.

Attribution here is self-reported source only. Someone tells you where they heard about you, and the answer is recorded against a campaign.

There is no pipeline attribution, no revenue attribution, and no multi-touch model. A number in this panel is a count of something observed, never a share of credit assigned by a model.

This is the “learn” leg of the loop, and it has a deliberately high bar.

  1. Each new observation is compared against the trailing mean of the previous observations for the same metric and scope. Fewer than five prior readings and nothing happens at all.
  2. A reading more than 50 percent away from that baseline, in either direction, is recorded as evidence with the numbers written into it.
  3. Activity counters and self-reported answers are excluded from this, because a counter that only goes up is not evidence of anything.
  4. A review runs weekly. It reads the current strategy, the evidence, and the raw numbers, and drafts at most three marketing proposals per project.
  5. Inconclusive data produces no proposals. The system does not invent a learning to have something to say.

Nothing in that chain changes your strategy. It ends at a proposal you accept or reject.