Score Every LeadAgainst Your Ideal Customer
Describe the customer you want in plain English, set what each dimension is worth, and every lead comes back with a number from 0 to 100 and a written reason next to it.
Weights
- Company fit40%
- Prospect fit30%
- Geographic fit20%
- Researched signals10%
Threshold
- 70+ routes to the priority queue
- 94Naomi Osei · Kestrel Analytics210 staff, B2B software, Toronto. Head of Revenue Operations is the exact buyer.
- 88Marcus Vale · Northwind LogisticsVP Sales, 340 staff, Chicago. Right seniority, and logistics sits just outside the named verticals.
- 66Yuki Tanaka · Halyard SystemsDirector of Demand Gen, 120 staff, Seattle. One rung below the economic buyer.
- 51Tom Okafor · Corvid Labs18 staff, under the headcount floor. No revenue operations function yet.
- 38Ines Delacroix · Bellhaven HealthParis. Outside the named regions, and healthcare is a deprioritised vertical.
- 17Ben Trask · Lumen FreightOwner-operator, 4 staff. Nothing in the profile matches except the country.
A sample run.
- 0–100score on every row, with its reason
- 18targeting criteria across three dimensions
- 2,000+teams signed up
What ICP scoring is,and how a run works.
ICP scoring is AI that creates ICP-based scoring models to automatically rank every lead in your pipeline against your ideal customer profile. Cleanlist uses AI for scoring prospects based on ICP fit, evaluating firmographic signals (company size, headcount, industry), demographic attributes (job title, seniority), and geographic alignment, alongside AI columns that research each account on the open web. Each lead receives a score from 0 to 100 so your sales team can instantly identify best-fit accounts and stop wasting time on prospects that will never close.
Define the profile
Set target industries and headcount bands, the job titles and seniority levels you sell to, and the regions you can actually service. Multiple profiles are supported, so a PLG motion and an enterprise motion can each have their own.
Set the weights
Decide how much company fit, prospect fit, geography and researched signals each move the number, and set the threshold that counts as good. What a high score means is your definition rather than ours.
Score the list
Run it as a Smart Agent column on any lead list or as a step inside a Playbook. Every row gets a number from 0 to 100 and a written reason next to it, with the matching and missing criteria named.
Route on the number
Filter by score band, send the leads above your threshold to a priority queue or a CRM stage, and leave the rest where a rep can reach them later rather than deleting them.
ICP Scoring Criteria Explained
ICP scoring criteria are the specific data points used to measure how closely a lead matches your ideal customer profile. Rather than relying on gut instinct or basic demographic filters, modern ICP scoring evaluates prospects across multiple dimensions simultaneously, assigning weighted scores that reflect real buying potential. Here are the most common criteria categories.
Company size and revenue
Employee count is the foundational firmographic signal, and revenue scale is the common companion to it. A company with 200 employees behaves differently than a 10-person startup. ICP scoring lets you define exact headcount bands and assign higher scores to the ones that match your sweet spot, with revenue indicators researched by AI columns where they matter.
Industry and vertical
Not every industry converts equally for your product. ICP scoring criteria weight target industries (e.g., SaaS, financial services, healthcare) higher while deprioritizing verticals with low historical win rates, so reps focus on sectors where you already have product-market fit.
Technology stack
Which tools a company already runs is a strong fit signal. Cleanlist has no technographic database behind this criterion: an AI column researches the open web for evidence of the stack, so you can score prospects higher when the tools your product integrates with show up, or flag a rival product for a displacement play.
Job title and seniority
Reaching the right person matters as much as reaching the right company. ICP scoring evaluates title keywords (VP Sales, Head of Revenue Ops, CRO) and seniority level (C-Suite, Director, Manager) to ensure you are engaging decision-makers, not gatekeepers.
Geography and timezone
Territory alignment, language requirements, and regulatory considerations make geography a key criterion. Score prospects higher when they are in your core markets and lower when they fall outside serviceable regions or compliance boundaries.
Growth and behavioural signals
Hiring, recent funding, and new product launches suggest a company is actively investing. There is no intent feed behind these in Cleanlist: an AI column researches each account on the open web and writes back what it finds, so dynamic signals can complement the static firmographic criteria.
What decides a score is how the criteria are weighted against each other. Cleanlist lets you assign custom weights to each dimension so the final 0 to 100 score reflects your sales motion. A PLG company might weight company size and industry at 60% while an enterprise team weights seniority and headcount at 70%. The criteria stay the same and the model adapts.
Eighteen criteria, across three dimensions
Company
- Industries
- Company size
- Revenue signals (researched by AI)
- Technologies (researched by AI)
- Business models
- Company age
- Growth indicators (researched by AI)
Prospect
- Job titles
- Departments
- Seniority levels
- Years of experience
- Skills
- Certifications
Geography
- Countries
- States and regions
- Cities
- Timezone alignment
- Exclusions
It is a column, or it is a step.
As a Smart Agent column
Add an ICP Fit Analysis column to any lead list. Every row is scored against the profile you pick, with the matching and missing criteria named in the cell. Learn about Smart Agents.
As a Playbook step
Put scoring inside an automated workflow so leads are scored as they arrive and routed on the number, into a priority sequence or a CRM stage. Learn about Playbooks.
Watch the agent score a real list.
Questions teams ask before they score anything
What is ICP scoring?
ICP scoring is an AI-driven method that automatically ranks every lead in your pipeline against your ideal customer profile. Cleanlist evaluates each prospect across firmographic criteria (company size, headcount, industry), demographic attributes (job title, seniority), and geographic fit, then assigns a composite score from 0 to 100. The result is a prioritized list where your sales team can instantly see which accounts are worth pursuing.
What criteria does ICP scoring use?
ICP scoring criteria are the data points used to measure prospect fit. In Cleanlist they include company size (employee count), industry vertical, business model, company age, job title, seniority level, years of experience, skills, and geographic location, all drawn from enriched firmographic and contact data. Softer signals like tech stack, growth, and recent funding come from AI columns that research each account on the open web rather than from a purchased intent or technographic feed. Criteria sit across company, prospect, and geographic dimensions, each with customizable weights.
How does AI improve ICP scoring?
Traditional lead scoring relies on static rules that sales ops must manually maintain. AI-powered ICP scoring analyzes patterns across all your criteria simultaneously, handles missing data gracefully, and surfaces non-obvious correlations, for example, that mid-market SaaS companies in the Pacific timezone with a specific tech stack convert 3x better for your product. Cleanlist's AI creates ICP-based scoring models that adapt to your data rather than requiring you to hard-code every rule.
How accurate is Cleanlist's ICP scoring?
Cleanlist scores leads on company fit, prospect fit, and geographic fit, plus whatever an AI column researches about the account, using verified data from waterfall enrichment across 25+ providers. Because scores are based on enriched firmographic and contact data rather than self-reported form fills, they reflect real buying potential. Weights are configurable per profile, so each sales motion sets its own good-fit threshold.
Can I create multiple ICP profiles?
Yes. Create separate ICP profiles for different products, market segments, or sales motions. Score the same lead list against each profile to find the best fit for each offering. Each profile supports independent scoring weights, threshold settings, and criteria selection, so your enterprise sales team and your PLG motion can each have a tailored scoring model.
How does ICP scoring integrate with enrichment workflows?
ICP scoring works natively as a Smart Agent column or a Playbook Builder step. Enrich contacts with waterfall enrichment to fill in firmographic and contact data, then score them against your ICP in a single automated workflow. High-scoring leads can be automatically routed to priority sequences, CRM stages, or outbound tools.
Point it at the listyour reps are ignoring.
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