> For the complete documentation index, see [llms.txt](https://docs.aloop.icustomer.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aloop.icustomer.ai/using-audience-loop/explorer/fire-scoring.md).

# FIRE scoring

FIRE is how the system rates every audience so the Harness knows who to act on, and why. Four dimensions combine into one score and a tier — Hot, Warm, or Cool:

* **Fit** — how well an account matches your ICP (static).
* **Intent** — buying signals like demo or pricing activity.
* **Recency** — how fresh that activity is, decaying over time.
* **Engagement** — clicks, visits, and other interactions.

Strong signals can override the tier outright: a demo request, for example, adds Intent and can flip an account straight to Hot. FIRE is the "why now" behind every decision — the Score step of [the loop](/how-it-works/how-the-loop-works.md) — and it leans directly on your [Audience context](/how-it-works/overview/audience-context.md).


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