target-account-listlisted

# Target Account List Score and tier accounts by how well they fit the ICP, so the team spends its time on the deals most likely to close. ## When to use When building an outbound or ABM list, when there are far more possible accounts than time to work them, or when reps are chasing logos at random instead of by fit. ## Before you start 1. **Read the brand/product context first.** Pull the ICP and its predictive signals — the firmographic, technographic, and intent signals that separate good deals from bad — from `.agents/product-marketing.md`. If the ICP isn't defined, run `brand-product-context` (and `persona-builder` for depth) first; this scores *against* the ICP, it doesn't invent it. 2. **Gather inputs:** a list of candidate accounts carrying those attributes. 3. **Confirm the objective:** a prioritized list the team can work top-down. ## Method Turn the ICP's fit criteria into weighted, checkable signals, weight each by how strongly it predicts a good deal (use win-loss evidence where you have it, not gut), then score every account. Calibrate against known-good customers: if great-fit logos don't score as A-tier, the weights are wrong. ## Workflow 1. **Turn ICP criteria into weighted signals** (industry match, employee-count band, uses a complementary tool, recent funding, hiring for a relevant role). 2. **Weight by predictiveness**, using `win-loss-analysis` evidence if available. 3. **Score with the engine** (see Run the tool) — it returns a 0–100 fit score