Focus a broad prospect universe
Ranks accounts by fit and revenue potential, producing clear priority tiers that help sales teams concentrate effort on commercially relevant prospects.
— Sales & Growth
ICP refinement & account prioritisation
Scores your whole account universe on firmographic, technographic and intent fit, prioritises by fit against ARR potential, and corrects the ICP itself using what your best customers look like.
- Sales & Growth
- Traceable reasoning
- Runs anywhere
2–3 weeks → ~40 minutes
For a full population, not a sample
No coding required
- Input
- Stated ideal customer profile and target-market criteria
- Output
- Tiered target account list with priority scores
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~2–3 weeks per run
— USE CASES
What people use ICP refinement & account prioritisation for
Challenge an inherited customer profile
Compares the stated ideal customer profile with the existing customer base to expose mismatches. Provides a refined definition grounded in observed customer characteristics.
Support a growth strategy review
Provides a defensible view of target account priorities, with fit assessments and revenue potential supporting the rationale for where to focus sales capacity.
Align account selection across teams
Applies consistent criteria across the account universe, giving sales and advisory teams a shared basis for discussing account quality and priority.
What it works from
- Stated ideal customer profile and target-market criteria
- Account universe with account names, industries, employee counts and revenues
- Account technology stacks and buying-intent signals
- Account status and estimated annual recurring revenue potential per account drawn from available account records or supplied estimates and assumptions agreed for the assessment
What you get back
- Tiered target account list with priority scores
- Account-level assessments of firmographic, technographic and intent fit
- Priority rationale linking customer fit to annual recurring revenue potential
- Comparison of the stated profile with existing customer characteristics and status information available in the account universe or supplied customer records for the assessment of profile mismatches and commercially relevant segments to consider within the refined definition of the ideal customer profile for future account selection and targeting decisions
— HOW IT BEHAVES
How ICP refinement & account prioritisation produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Every row of the pipeline in scope
Each row of your export is processed on the same basis, so no account is skipped however long the table is.
The pattern charted
Movement across the pipeline in scope is visualised from the computed data, so the trend is legible at a glance.
Composed as work product
Findings on the pipeline in scope are written up as a document that reads like professional output, with each claim tied back to a account.
Each account enriched in place
Derived columns are added row by row, keeping your source data and the judgement about each account side by side.
Roll-up alongside account-level detail
Detail rows are summarised into the grouped view of the pipeline in scope without losing the underlying accounts.
Why this is expensive by hand
An ideal customer profile can reflect assumptions rather than the customers that actually generate value. In practice it shows up as focus a broad prospect universe: ranks accounts by fit and revenue potential, producing clear priority tiers that help sales teams concentrate effort on commercially relevant prospects. It is the kind of work that decides whether a recommendation survives scrutiny — and the kind that quietly eats 2–3 weeks of senior time whenever it comes round.
How this Skill produces it
Here the same job runs as a Skill. Your material goes in; tiered target account list with priority scores comes out, alongside account-level assessments of firmographic, technographic and intent fit. The criteria, ordering and review points that make the answer trustworthy are encoded in the Skill itself — which is the difference between a structured method and a prompt someone pastes in. Net effect: 2–3 weeks down to ~40 minutes, no drift between runs, and every conclusion traceable back to the evidence behind it.
Who it's for
- Revenue and commercial leaders
- Sales operations and enablement teams
- Customer success and account management leads
- Consultants advising on go-to-market
Run it in Skillsize — or export it anywhere
ICP refinement & account prioritisation exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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