Superlead ICP Scorer

Score leads against your Ideal Customer Profile using AI. Get fit scores (0-100), band labels, and plain-English explanations for every lead in your list.

What does Superlead ICP Scorer do?

Superlead ICP Scorer uses AI to evaluate sales leads against your Ideal Customer Profile (ICP) description. It reads any JSON lead data — company, title, industry, employee count, funding stage, or any other fields — and returns a numeric fit score with an explanation.

• Scores each lead 0-100 with band labels (excellent, good, fair, poor)
• Plain-English summaries explain why each lead scored the way it did
• Confidence ratings based on data completeness
• Works with any lead format — just pass JSON objects with whatever fields you have
• Instant API mode — Score single leads via Standby HTTP server

What else can Superlead do?

For the most accurate scoring, clean your lead data before scoring:

• Superclean Company Names — Clean company names for consistent matching
• Superclean Job Titles — Normalize job titles for accurate seniority matching
• Superclean Person Names — Clean person names for CRM deduplication
• Superclean Places — Normalize locations for geography-based ICP criteria
• Superclean URLs — Clean and normalize URLs from lead data

Enrich your leads with network intelligence:

• Supernet Domain Health — Check email domain reputation before outreach
• Supernet DNS Lookup — Resolve DNS records for any domain

Why score leads against your ICP?

Nobody wants their SDRs spending hours on leads that will never close:

"We reached out to 500 leads last quarter, but 80% weren't even in our target market."

When every lead gets the same priority:

"Our top reps are wasting cycles on interns at Fortune 500s instead of VPs at mid-market SaaS companies."

ICP scoring fixes this. Here's what you can do with scored leads:

• Prioritize outreach — Focus your team's time on leads that score 80+ (excellent fit). Stop wasting cycles on leads that score below 40.
• Consistent qualification — Every lead is evaluated against the same criteria. No more variation between reps on what counts as a "good fit."
• Enrich lead lists at scale — Score thousands of leads in minutes. Manual qualification doesn't scale past a few hundred.
• Segment campaigns — Route excellent-fit leads to your top reps, good-fit leads to nurture sequences, and poor-fit leads to disqualification.

How to use Superlead ICP Scorer

1. Paste your leads as a JSON array into the Leads field (any fields work)
2. Write your ICP description in plain English in the ICP field
3. Click Start and download your scored results

Writing your ICP description

The ICP description is plain English. Include any criteria that matter to your sales process:

B2B SaaS companies with 50-500 employees. Series A to C funding. Decision makers: VP or above in Engineering or Product. North America. Prefer companies using modern tech stacks.

Tips:

• Be specific about company size, industry, and geography
• Include seniority/title requirements
• Mention funding stage, revenue, or growth signals if relevant
• The more detail you provide, the more accurate the scoring

Score bands

Band	Score	Meaning
Excellent	80-100	Strong ICP match — prioritize for outreach
Good	60-79	Solid fit with minor gaps
Fair	40-59	Partial fit — worth reviewing
Poor	0-39	Does not match ICP

Standby mode (instant API)

Standby mode keeps a warm container running so you get instant lead scoring without cold-start delays. Instead of starting a full Actor run, you make a simple HTTP GET request and get results in seconds.

This is ideal for:

• Clay enrichment steps — single-lead scoring inline
• Make / n8n HTTP modules — real-time lead qualification in workflows
• MCP agents — AI tools that need instant lead scoring data

Standby URL

https://superlativetech--superlead-icp-scorer.apify.actor?token=YOUR_API_TOKEN

Or use a Bearer token in the Authorization header instead of the token query parameter.

Score a lead

$curl "https://superlativetech--superlead-icp-scorer.apify.actor?token=YOUR_API_TOKEN&lead=%7B%22company%22%3A%22Acme%22%2C%22title%22%3A%22VP+Engineering%22%2C%22industry%22%3A%22SaaS%22%7D&icp=B2B+SaaS+50-500+employees"

With your own OpenRouter key (BYOK)

curl -H "X-OpenRouter-Key: sk-or-..." \
  "https://superlativetech--superlead-icp-scorer.apify.actor?token=YOUR_API_TOKEN&lead=%7B%22company%22%3A%22Acme%22%7D&icp=B2B+SaaS+50-500+employees"

Query parameters

Parameter	Required	Description
lead	Yes	Lead object as a JSON string
icp	Yes	Your Ideal Customer Profile description
model	No	LLM model (default: openrouter/auto)

Headers

Header	Required	Description
X-OpenRouter-Key	No	Your OpenRouter API key for BYOK

Response format

{
  "id": 1,
  "input": {"company": "Acme", "title": "VP Engineering", "industry": "SaaS"},
  "label": "VP Engineering at Acme",
  "score": 85,
  "band": "excellent",
  "summary": "Strong fit: VP-level decision maker at SaaS company within target size range.",
  "confidence": 0.9
}

Error responses

Code	Cause
400	Missing lead or icp parameter, or invalid JSON in lead
405	Non-GET request
500	Unexpected server error

How many leads can you score?

There's no limit. Process as many leads as you need — from a handful to thousands. The Actor scales automatically.

For best performance, batch your requests. Processing 1,000 leads at once is more efficient than 10 separate runs of 100 leads each. For batches over 5,000 leads, increase the timeout in Settings → Run configuration (e.g., 1800 seconds for 10K leads).

How much will it cost you?

This Actor uses pay-per-result pricing:

Leads	Cost
1,000	$1.00
10,000	$10.00
100,000	$100.00

Volume discounts apply automatically:

• Bronze (100+ leads): $0.0009/lead
• Silver (1,000+ leads): $0.0008/lead
• Gold (10,000+ leads): $0.0007/lead

AI model costs

This Actor uses the Apify OpenRouter integration for AI processing. Token costs are billed to your Apify account at OpenRouter rates.

The default model (openrouter/auto) automatically selects the most cost-effective option, typically adding less than $0.05 per 1,000 leads.

Bring your own key

You can bring your own OpenRouter API key instead of using the built-in Apify integration. This routes AI requests directly through your OpenRouter account, so token costs are billed there instead of your Apify account.

To use your own key, paste it into the OpenRouter API key field in the Advanced section. The key is encrypted and never logged.

Input parameters

Parameter	Type	Description
leads	array	Array of lead objects to score (any JSON structure)
lead	object	Single lead object — API shorthand for integration callers (Clay, Make, n8n). If both lead and leads are provided, lead is prepended to the list
icp	string	Your Ideal Customer Profile description (required)
model	string	AI model to use (default: openrouter/auto). Set a specific model for higher-quality scoring. Browse models
openRouterApiKey	string	Optional. Your own OpenRouter API key for direct API access (encrypted)

Input example

{
  "leads": [
    {"company": "Acme Corp", "title": "VP of Engineering", "industry": "SaaS", "employees": 150},
    {"company": "MegaRetail Inc", "title": "Marketing Intern", "industry": "Retail", "employees": 50000}
  ],
  "icp": "B2B SaaS companies with 50-500 employees. Decision makers: VP or above in Engineering or Product."
}

leads also accepts wrapped objects, which is useful for API and MCP integrations:

{
  "leads": [
    {"input": {"company": "Acme Corp", "title": "VP of Engineering"}},
    {"input": {"company": "MegaRetail Inc", "title": "Marketing Intern"}}
  ],
  "icp": "B2B SaaS companies with 50-500 employees."
}

For API and integration callers who want to score a single lead without wrapping it in an array, use the lead shorthand:

{
  "lead": {"company": "Acme Corp", "title": "VP of Engineering", "industry": "SaaS"},
  "icp": "B2B SaaS companies with 50-500 employees."
}

During the Actor run

The Actor processes leads in batches for efficiency. You'll see progress updates as each batch completes.

If you provide invalid input (e.g., missing ICP description or no leads), the Actor will stop immediately with an error message explaining what went wrong.

Results are available in real-time — you can start reviewing scored leads before the full run completes.

Output format

Results are saved to the default dataset. Each scored lead is a separate item.

You can export results as JSON, CSV, Excel, or other formats directly from Apify Console. Or access them programmatically via the API.

Output example

[
  {
    "id": 1,
    "input": {"company": "Acme Corp", "title": "VP of Engineering", "industry": "SaaS", "employees": 150},
    "label": "VP of Engineering at Acme Corp",
    "score": 85,
    "band": "excellent",
    "summary": "Strong fit: VP-level decision maker at mid-size SaaS company within target employee range.",
    "confidence": 0.9
  },
  {
    "id": 2,
    "input": {"company": "MegaRetail Inc", "title": "Marketing Intern", "industry": "Retail", "employees": 50000},
    "label": "Marketing Intern at MegaRetail Inc",
    "score": 12,
    "band": "poor",
    "summary": "Poor fit: Junior role at large retail company, does not match SaaS or seniority criteria.",
    "confidence": 0.85
  }
]

Field	Description
id	Row number (1-based, matches Apify's displayed row numbers)
input	Original lead data as submitted (for matching back to your source data)
label	Auto-generated lead summary (e.g., "VP Engineering at Acme Corp")
score	ICP fit score from 0 to 100
band	Score band: excellent (80+), good (60-79), fair (40-59), poor (0-39)
summary	Plain-English explanation of the score
confidence	Data completeness confidence from 0 to 1 (lower scores mean the lead had sparse data)

Integrations

Superlead ICP Scorer works with any tool that can call Apify Actors:

• Clay — Add as an enrichment step in your Clay tables
• Make — Use the Apify module to run the Actor
• Zapier — Trigger runs and retrieve results automatically
• n8n — Self-hosted workflow automation

You can also use webhooks to trigger actions when a run completes — for example, send a Slack notification or automatically import scored leads into your CRM.

Using Superlead ICP Scorer with the Apify API

The Apify API gives you programmatic access to run Actors, retrieve results, and manage datasets.

Node.js:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('superlativetech/superlead-icp-scorer').call({
  leads: [
    { company: 'Acme Corp', title: 'VP of Engineering', industry: 'SaaS', employees: 150 },
    { company: 'MegaRetail Inc', title: 'Marketing Intern', industry: 'Retail', employees: 50000 }
  ],
  icp: 'B2B SaaS companies with 50-500 employees. Decision makers: VP or above.'
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python:

from apify_client import ApifyClient

client = ApifyClient('YOUR_API_TOKEN')

run = client.actor('superlativetech/superlead-icp-scorer').call(run_input={
    'leads': [
        {'company': 'Acme Corp', 'title': 'VP of Engineering', 'industry': 'SaaS', 'employees': 150},
        {'company': 'MegaRetail Inc', 'title': 'Marketing Intern', 'industry': 'Retail', 'employees': 50000}
    ],
    'icp': 'B2B SaaS companies with 50-500 employees. Decision makers: VP or above.'
})

items = client.dataset(run['defaultDatasetId']).list_items().items
print(items)

Check out the Apify API reference for full details, or click the API tab above for more code examples.

Your feedback

We're always improving Superlead Actors. If you have feature requests, find a bug, or need help with a specific use case, please open an issue in the Actor's Issues tab.

When Apify asks to share your run data with us, we encourage you to opt in — it's the fastest way for us to spot edge cases and improve results. Sharing is completely optional (you can toggle it anytime under Account Settings → Privacy), and shared runs are automatically deleted by Apify based on your plan's data retention period. We only use shared data to debug issues and improve this Actor.

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If Superlead ICP Scorer saves you time or improves your outreach, please leave a review. Your feedback helps other users discover the tool and helps us understand what's working well.

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