Most ICPs are wishful thinking dressed up as strategy. "Enterprise companies in tech" isn't an ICP - it's a vague aspiration that doesn't help sales prioritize or marketing target.
A real ICP is specific enough to be actionable. It tells your team exactly which accounts to pursue and which to deprioritize. It predicts conversion probability based on observable characteristics.
This guide shows you how to build an ICP from actual data - not assumptions.
What an ICP Actually Is (And Isn't)
An ICP is: A detailed description of the companies most likely to become your best customers, based on characteristics you can identify before they buy.
An ICP is not: A description of companies you wish would buy, or a list of your biggest logos.
The distinction matters. Your biggest customer might be an outlier. They bought despite not fitting your typical profile. Building your strategy around outliers leads to chasing accounts you can't consistently win.
A good ICP answers: "If we could only sell to 100 companies, which 100 would have the highest win rate and lifetime value?"
Why Most ICPs Fail
Common ICP mistakes:
Too broad: "B2B SaaS companies" describes 50,000+ companies. That's not targeting, that's everyone.
Based on assumptions: "We think enterprise is better" without data to support it.
Static: Built once, never updated as you learn from wins and losses.
Ignores negative signals: Focuses only on what good customers have, not what bad customers have.
Can't be measured: Criteria like "innovative culture" that you can't actually observe or score.
The result? Sales wastes time on wrong accounts. Marketing targets wrong segments. Pipeline looks full but doesn't close.
Step 1: Analyze Your Best Customers
Start with data, not intuition.
Define "best customer"
Not just any customer - your best customers. Criteria:
- Highest lifetime value (LTV)
- Shortest sales cycle
- Highest expansion rate
- Lowest churn
- Best NPS/satisfaction scores
Export a list of your top 20% of customers by these criteria.
Find common characteristics
For each best customer, document:
Firmographics:
- Industry (specific, not just "tech")
- Company size (employee count ranges)
- Revenue range
- Geography
- Business model (B2B, B2C, marketplace, SaaS)
Technographics:
- Tech stack (what tools do they use?)
- CRM platform
- Marketing automation
- Key technologies indicating sophistication
Situational:
- Growth stage (startup, growth, mature)
- Recent funding?
- Hiring aggressively?
- Recent leadership changes?
Engagement:
- How did they find you?
- What content did they consume?
- How long was the sales cycle?
Sample Size
You need at least 20-30 customers to identify patterns. Fewer than that, and you're finding coincidences, not correlations.
Identify patterns
Look for characteristics that appear in 60%+ of your best customers:
- "80% are B2B SaaS companies"
- "75% have 50-500 employees"
- "70% use Salesforce"
- "65% are in growth stage (Series A-C)"
These become your ICP criteria.
Step 2: Validate Against Losses
Your ICP should also explain why deals didn't close.
Analyze lost deals
Pull deals from the last 12 months that:
- Made it past discovery but didn't close
- Closed but churned within 12 months
- Had unusually long sales cycles
Find anti-patterns
What characteristics do lost/churned customers have that winners don't?
- "We lose 80% of deals at companies under 20 employees"
- "Customers without a dedicated RevOps person churn 3x more"
- "Companies using [competitor] rarely switch"
These become your ICP exclusion criteria.
Calculate win rates by segment
| Segment | Win Rate | Avg Deal Size | Sales Cycle |
|---|---|---|---|
| 50-200 employees | 35% | $25K | 45 days |
| 200-500 employees | 42% | $50K | 60 days |
| 500-1000 employees | 28% | $75K | 90 days |
| 1000+ employees | 15% | $100K | 180 days |
This data shows where you win most efficiently - not just where you occasionally land big deals.
Step 3: Define Your ICP Framework
Now synthesize into a usable framework.
Company-Level ICP
Define the ideal company:
Must-haves (required to be ICP):
- Industry: B2B SaaS, FinTech, or MarTech
- Size: 50-500 employees
- Revenue: $5M-$100M
- Geography: US, Canada, UK
- Growth signals: Hiring sales/marketing roles
Nice-to-haves (improve fit score):
- Recently raised funding
- Uses Salesforce or HubSpot
- Has dedicated RevOps function
- Growing headcount 20%+ YoY
Disqualifiers (automatic exclusion):
- Under 30 employees
- No sales team
- Heavy regulated industry (healthcare, government)
- Uses [incompatible tool]
Buyer Persona ICP
Define the ideal buyer within ideal companies:
Primary buyer:
- Title: VP/Director of Sales, RevOps, or Growth
- Department: Sales or Revenue Operations
- Seniority: Director level or above
- Reports to: CRO, VP Sales, or CEO
Secondary buyers (influencers):
- SDR/BDR Manager
- Marketing Operations
- Sales Enablement
Anti-personas (deprioritize):
- Individual contributors without budget
- IT (unless they own sales tools)
- Procurement (too early in process)
Step 4: Build a Scoring Model
Turn your ICP into a quantitative score.
Assign point values
| Criterion | Points | Weight |
|---|---|---|
| Industry match | 0-20 | High |
| Company size match | 0-20 | High |
| Revenue range match | 0-15 | Medium |
| Geography match | 0-10 | Medium |
| Tech stack match | 0-15 | Medium |
| Growth signals | 0-10 | Low |
| Contact seniority match | 0-10 | Low |
Total possible: 100 points
Define score thresholds
- 90-100: Perfect ICP fit. Prioritize immediately.
- 70-89: Strong fit. Include in primary outreach.
- 50-69: Moderate fit. Nurture but don't prioritize.
- Below 50: Poor fit. Deprioritize or exclude.
Automate scoring
Use ICP Scoring to automatically score every lead against your criteria. New leads get scored on entry. Existing leads re-score as you enrich more data.
Pro Tip
Score at the account level and the contact level. A perfect contact at a poor-fit company is still a poor lead. A poor contact at a perfect company is worth finding the right person.
Step 5: Operationalize Your ICP
An ICP only works if teams use it.
For Sales
- Lead routing: Route high-ICP-score leads to top reps
- Prioritization: Work 90+ scores before 70-89 before 50-69
- Qualification: Use ICP criteria in discovery questions
- Pipeline review: Flag deals that don't match ICP
For Marketing
- Audience building: Target ads at ICP firmographics
- Content strategy: Create content for ICP pain points
- ABM lists: Build account lists matching ICP criteria
- Lead qualification: Pass only ICP-qualified leads to sales
For RevOps
- Scoring automation: Implement ICP scoring in CRM
- Data enrichment: Enrich records to enable accurate scoring
- Reporting: Track win rates by ICP score
- Feedback loop: Update ICP based on new data
Step 6: Iterate Based on Results
Your ICP isn't static. Update it quarterly based on new data.
Track ICP effectiveness
| Metric | How to Measure | Target |
|---|---|---|
| ICP accuracy | Win rate of high-score leads | 2x average |
| False positives | High scores that don't convert | Under 30% |
| False negatives | Low scores that do convert | Under 10% |
| Score distribution | % of pipeline that's high-score | Over 60% |
Refine criteria
If high-ICP-score deals aren't converting better:
- Your criteria may not predict success
- Your scoring weights may be off
- You may be missing key criteria
Interview recent wins and losses. What characteristics did you miss?
Update quarterly
Every quarter:
- Recalculate win rates by ICP segment
- Interview 5 recent wins about their buying journey
- Interview 5 recent losses about why they didn't choose you
- Adjust criteria and weights based on findings
How to Build Your ICP in Cleanlist
The framework above works on paper. Here's how to operationalize it inside Cleanlist so your ICP scores leads automatically.
Step 1: Create an ICP Profile
In Cleanlist, go to ICP Scoring and create a new profile. You'll define three layers of targeting:
Company targeting — set the firmographic filters that match your ideal accounts:
| Field | What to set | Example |
|---|---|---|
| Industries | Specific verticals with sub-categories | SaaS, FinTech, MarTech |
| Company size | Employee count range | 51-200, 201-500 |
| Revenue range | Annual revenue bracket | $5M-$50M, $50M-$100M |
| Technologies | Tech stack signals | Salesforce, HubSpot, Outreach |
| Business models | How they sell | B2B, SaaS, Marketplace |
| Company age | Years in business | 3-15 years |
| Growth indicators | Momentum signals | Hiring, recently funded |
Prospect targeting — define who you want to reach inside those companies:
| Field | What to set | Example |
|---|---|---|
| Job titles | Specific role titles | VP Sales, Head of RevOps, SDR Manager |
| Departments | Functional areas | Sales, Marketing, Revenue Operations |
| Seniority levels | Decision-maker tier | C-Suite, VP, Director |
| Years of experience | Min/max range | 5-20 years |
| Skills | Key competencies | Salesforce admin, demand gen, ABM |
Geographic targeting — narrow by location:
| Field | What to set | Example |
|---|---|---|
| Countries | Target markets | United States, Canada, United Kingdom |
| States/provinces | Regional focus | California, New York, Texas |
| Cities | Metro targeting | San Francisco, New York, Austin |
| Timezones | Outreach windows | EST, PST, GMT |
You can also set exclude rules — specific companies, locations, or segments you never want to target.
Step 2: Enrich Your List
Your ICP is only as good as the data behind it. Upload your lead list and run waterfall enrichment to fill in the gaps. Cleanlist queries 15+ data providers in sequence, so you get:
- Verified work emails with deliverability status (valid, risky, catch-all)
- Direct phone numbers
- Current job title, company, and seniority
- Full firmographics (industry, size, revenue, location)
- LinkedIn profile URL
Without enrichment, you're scoring on incomplete data. A lead might look like a poor fit simply because you're missing their company size or current title.
Step 3: Score Automatically
Once your ICP profile is set and your data is enriched, Cleanlist scores every lead against your criteria. Each lead gets a fit analysis you can use to:
- Prioritize outreach — work high-fit leads first
- Route leads — send top scores to your best reps
- Filter lists — segment by company size, seniority, industry, or any combination
- Track accuracy — see how many high-fit leads convert vs. low-fit
Step 4: Use Smart Columns for Deeper Signals
For signals that go beyond structured data, use Smart Agents to run AI analysis on each lead:
- ICP Fit Analysis — detailed scoring with reasoning for each lead
- LinkedIn Research — pull recent activity, posts, and engagement signals
- Website Analysis — analyze the prospect's company site for tech stack, messaging, and growth signals
- Find Similar Companies — once you identify a great-fit account, find lookalikes automatically
From Framework to Workflow
The ICP framework in this guide maps directly to Cleanlist's targeting fields. Define your criteria once, enrich your data, and every lead gets scored on entry. No spreadsheets, no manual research.
ICP Template
Use this template to document your ICP:
## [Company Name] Ideal Customer Profile
### Company Criteria
- Industry: [Specific industries]
- Size: [Employee range]
- Revenue: [Revenue range]
- Geography: [Regions/countries]
- Business model: [B2B, B2C, SaaS, etc.]
- Growth signals: [Funding, hiring, etc.]
### Technology Criteria
- Required: [Must-have tools]
- Preferred: [Nice-to-have tools]
- Disqualifying: [Incompatible tools]
### Buyer Persona
- Primary: [Title, department, seniority]
- Secondary: [Influencer titles]
- Anti-persona: [Titles to avoid]
### Scoring Thresholds
- Tier 1 (prioritize): [Score range]
- Tier 2 (work): [Score range]
- Tier 3 (nurture): [Score range]
- Disqualified: [Score range]
### Disqualifiers
- [List of automatic exclusions]
### Last Updated: [Date]
### Next Review: [Date]
Frequently Asked Questions
How specific should my ICP be?
Specific enough that sales can identify ICP accounts in 30 seconds. If your ICP requires research to determine fit, it's too vague. Use observable criteria like employee count, industry, and tech stack.
What if I don't have enough customer data?
Start with your best 10 customers and hypothesize. Then validate quickly - run targeted outreach to hypothetical ICP accounts and measure response rates. Refine based on early results.
Should I have multiple ICPs?
Only if you have genuinely different products or motions for different segments. Multiple ICPs often indicate unclear positioning. Start with one, prove it works, then consider expanding.
How do I get firmographic data for scoring?
Enrich your leads with firmographic data (company size, industry, revenue) so you can score automatically. Without enrichment, you're scoring on incomplete data.
What's the difference between ICP and buyer persona?
ICP defines the ideal company. Buyer persona defines the ideal person within that company. You need both - the right person at the wrong company is still a bad lead.
A good ICP isn't a document that sits in a folder. It's an operational tool that helps every team prioritize. Build it from data, automate scoring with ICP Scoring, and iterate based on results.