Problem solving / root cause analysis
Fit-criteria scorecard
Fit-criteria scorecard is licensed CC BY 4.0. Attribution: Katafacts (katafacts.com).
Customise with AISkill file ↓1 · What it is
What it is
A fit-criteria scorecard is the operational, repeatable counterpart to the ICP canvas's definitional, built-once profile — the same weighted decision matrix discipline, pointed at real prospect accounts instead of a generic decision. Score each account 1 to 5 against firmographic fit, technographic fit, trigger strength, and buying-committee access, weighted by how much each one actually predicts a fast, clean win in your own deal history — not split evenly by default. The composite score and priority/consider/deprioritize tier are computed from those weights and scores, so the account worth calling next is a defensible answer, not a hunch.
2 · When to use it
When to use it — and when not to
Use it when
- You have a real list of named prospect accounts (from a TAM coverage map, an inbound queue, or an outbound list) and need to decide which ones actually deserve outreach effort next.
- You've already built an ICP canvas and know which signals — a specific trigger, an exec sponsor, a specific tech stack — actually predict a fast, clean win in your own deal history, not just in theory.
- You want to say plainly that some tracked accounts aren't worth chasing yet, not flatter every account on the list with a similar-looking score.
Not when
- You don't have a real ICP canvas yet — build that first; this tool scores accounts against criteria the canvas should already have defined, not invents them here.
- You're evaluating a single account in depth for a live deal — a deal A3 or a value hypothesis is the right depth for a deal already in motion, not a comparative score against other accounts.
- Every criterion in your ICP genuinely matters equally — an even split is a real, defensible weighting choice, but check that it's actually true rather than the path of least resistance.
3 · How to fill it in
How to fill it in
- Decision
- Which accounts are being prioritized, and against what list or segment?
- Criteria and weights
- Pull straight from your ICP canvas's sections — firmographic fit, technographic fit, trigger strength, buying-committee access — weighted by how much each one actually predicts a win in your own deal history, not split evenly by default.
- Options, scored
- For each account, score it 1 (weakest) to 5 (strongest) against every criterion — your own honest read of the account, never AI-scored. The composite score and tier are computed, never entered directly.
- Narrative
- Drafted from the computed ranking, naming which account deserves the next call and why.
4 · What good looks like
What good looks like
The example below scores three of a TAM coverage map's own tracked mid-market logistics accounts — including that map's own 'dark account' with zero contacts, which scores lowest here rather than being flattered by an even-handed score.
Same example, as a downloadable xlsx workbook.
Weighted decision matrix
Beacon Analytics — mid-market logistics fit-criteria scorecard
Prioritizing which of the TAM coverage map's tracked mid-market logistics accounts to invest further outreach in next, ahead of the segment's other 30 untracked accounts.
Sam Cole, Sales Enablement · 2027-02-17
Decision
Prioritizing which of the TAM coverage map's tracked mid-market logistics accounts to invest further outreach in next, ahead of the segment's other 30 untracked accounts.
Criteria and weights
- Buying-committee access30%
- Trigger strength30%
- Firmographic fit20%
- Technographic fit20%
Options, scored
Summit Carriers
76/100 · PriorityBuying-committee access: 3/5 · Trigger strength: 5/5 · Firmographic fit: 3/5 · Technographic fit: 4/5
Meridian Logistics
68/100 · ConsiderBuying-committee access: 3/5 · Trigger strength: 3/5 · Firmographic fit: 4/5 · Technographic fit: 4/5
Apex Distribution
32/100 · DeprioritizeBuying-committee access: 1/5 · Trigger strength: 1/5 · Firmographic fit: 3/5 · Technographic fit: 2/5
Narrative
Summit Carriers is the vital-few priority account, at 76/100 — its enterprise size runs slightly larger than the ICP canvas's mid-market sweet spot, but a real board-level forecast-accuracy trigger and an identified economic buyer outweigh that firmographic mismatch under this weighting. Meridian Logistics sits at 68, a real consider: solid firmographic and technographic fit with both a champion and an economic buyer identified, but no confirmed trigger yet — worth a discovery call to test for one before committing more time. Apex Distribution — the coverage map's own dark account, with no contact at all — scores 32 and belongs at the back of the queue: no evidence of a trigger and no buying-committee access make it the wrong account to invest further outreach in until some real signal shows up.
5 · Common mistakes
Common mistakes
Weighting every criterion evenly by default instead of checking which ones actually predict a win.
Real deal history usually shows one or two signals (an exec sponsor engaged early, a specific trigger) matter far more than the others — an even split throws that evidence away.
Scoring firmographic fit generously just because the account is a named target on a list.
Being on a target list means an account was addressable, not that it's actually a strong fit — conflating the two defeats the reason to score it at all.
Letting a strong score on one criterion (usually firmographic fit) override a weak trigger or no buying-committee access.
The exact failure this tool exists to prevent — a composite score should be able to rank a smaller, better-fit account below a larger one with a real trigger and real access, not the other way around.
6 · What it connects to
What it connects to
upstream
Ideal customer profile (ICP) canvas
The ICP canvas defines the criteria this scorecard weighs — firmographics, technographics, triggers, and buying-committee roles — as a one-time definitional exercise; this scorecard applies them repeatedly to real accounts.
Total addressable market (TAM) coverage map
The TAM coverage map surfaces which accounts are even tracked and how much contact access exists at each; a fit-criteria scorecard is how you decide which of those tracked accounts to invest further outreach in next.
downstream
Once a fit-criteria scorecard names an account worth pursuing, a value hypothesis is where the real discovery work on that specific account begins.
Part of these playbooks
- Ideal Customer Profile (ICP) Definition — 6 katas in the order they are used
- Sales Funnel Management Katas — 13 katas in the order they are used
7 · Where AI helps
Where AI helps
Judgement — stays yours
- Deciding the real weight each ICP criterion deserves, based on actual deal history
- Deciding an honest fit score for each account against each criterion
Analysis — AI helps
- Drafting the narrative from the ranking actually computed, naming which account deserves the next call and why
Drudgery — automated
- Computing each account's composite score from its weights and scores, every time one changes
- Sorting accounts into priority, consider, and deprioritize tiers
- Exporting to xlsx in the house format
9 · Rate this kata