AI Lead Enrichment — Firmographics, ICP Score & Outreach
Pricing
from $50.00 / 1,000 lead enricheds
AI Lead Enrichment — Firmographics, ICP Score & Outreach
Enrich a list of companies, domains, or people with firmographics, role data, an ICP-fit score, and a personalized outreach line — powered by an LLM with live web search. Turn raw lists into sales-ready leads.
Pricing
from $50.00 / 1,000 lead enricheds
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Muhammad Afzal
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Turn a raw list of companies, domains, or people into sales-ready leads. Give the actor your list and it uses an LLM with live web search to fill in firmographics (industry, size, HQ, founded year), role/seniority, a concise summary, an ICP-fit score against your ideal customer profile, and a personalized outreach opener for each lead.
Export results, run via API, schedule and monitor runs, or integrate with your CRM and outbound tools.
What you get per lead
| Field | Example |
|---|---|
company_name, domain | Apify, apify.com |
industry, company_size, hq_location, founded_year | Web scraping & automation, 51-200, Prague, 2015 |
company_description | Full-stack web scraping and automation platform. |
person_name, role_title, seniority | Jane Doe, VP of Sales, VP |
summary | Mid-size scraping platform; strong fit for proxy cost savings. |
icp_fit_score (0-100) + icp_fit_reasons | 85 — matches industry, headcount in range |
personalized_opener | "Saw Apify scaled its proxy fleet—we cut similar costs 40% for data teams." |
citations, confidence | source URLs, high/medium/low |
Input
| Field | Type | Description |
|---|---|---|
leads | array | Objects with any of company, domain, fullName, role, location, notes. |
icpDescription | string | Your ideal customer profile — used to score each lead's fit. |
offerContext | string | What you're selling — used to write the personalized opener. |
model | string | OpenRouter model slug (default openai/gpt-4o-mini). |
useWebSearch | boolean | Ground enrichment in live web results (recommended). |
webSearchResults | integer | Web results per lead (1–10). |
maxLeads | integer | Cap on leads per run (cost control). |
Example input
{"leads": [{ "company": "Apify", "domain": "apify.com" },{ "fullName": "Jane Doe", "company": "Acme", "role": "VP Sales" }],"icpDescription": "B2B SaaS, 50-1000 employees, data/AI teams","offerContext": "Managed proxy + data pipeline that cuts scraping costs 40%","model": "openai/gpt-4o-mini","useWebSearch": true}
API key (required)
Enrichment runs through OpenRouter — set a single environment variable on the actor (Console → Settings → Environment variables, mark as Secret):
OPENROUTER_API_KEY = sk-or-...
Pick any model via model. You pay OpenRouter directly for model + web-search usage; the actor's PPE events cover the enrichment layer.
Pricing (Pay Per Event)
| Event | When |
|---|---|
actor-start | Once per run |
lead-enriched | Each lead successfully enriched |
Leads that fail (missing key, model error) are not charged — but still appear in the dataset with an error so you know which ones to retry.
Use cases
- Outbound sales — enrich a prospect list and get tailored openers in one run.
- CRM hygiene — fill missing firmographics on existing records.
- Lead scoring / routing — rank inbound leads by ICP fit before they hit a rep.
- Agent pipelines — call via the Apify MCP server to enrich leads on demand.
Tips
- More input context (domain + role + notes) → better, higher-confidence enrichment.
- Write a specific
icpDescription— vague profiles produce vague scores. - For large lists, raise
maxLeadsand schedule runs; keepwebSearchResultslow to control cost.