Domain Lead Scoring and ICP Enrichment
Pricing
Pay per usage
Domain Lead Scoring and ICP Enrichment
Score company websites against an ideal customer profile and return structured lead qualification data. Built for AI sales agents: fit score, fit band, reasons, disqualifiers, evidence, company profile, and next action.
Pricing
Pay per usage
Rating
0.0
(0)
Developer
Pete Mientkiewicz
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
2 days ago
Last modified
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Domain Lead Scoring and ICP Enrichment scores company websites against your ideal customer profile and returns agent-ready lead qualification data. It is built for AI sales agents, prospecting workflows, CRM enrichment, and outbound prioritisation when you have domains but need fit scores, reasons, disqualifiers, website evidence, and a recommended next action.
Use cases
- Score a list of domains before importing leads into a CRM.
- Prioritise outbound lists by ICP fit.
- Give an AI sales agent structured lead qualification context.
- Add evidence-backed fit reasons and disqualifiers to prospect records.
- Build a lightweight enrichment step before deeper paid enrichment.
Use this Actor when
Use this Actor when you already have one or more company domains and a short ICP description, and you want a first-pass lead score with transparent reasons.
Do not use this Actor when
Do not use it as the sole source of truth for buying intent, revenue, headcount, funding, or private company facts. It scores public website signals only.
Input
{"domains": ["https://scaleupsystems.co"],"icpDescription": "B2B companies selling services or software, with clear growth or lead generation needs.","maxPagesPerDomain": 2}
Output
The Actor writes one record per domain to the default dataset. Typical fields include:
domainOrUrlfitScorefitBandreasonsdisqualifierssuggestedNextActionprofileprofile.evidencePagesprofile.contactPathsprofile.confidence
Agent workflow
- Pass a small batch of domains and an ICP description.
- Read scored records from the default dataset.
- Route
highfit leads to outreach,mediumfit leads to manual review, andlowfit leads to deprioritisation. - Use
reasonsanddisqualifiersto explain the decision in downstream automations.
Limitations
- Scoring is based on website text and visible contact/conversion paths.
- Thin or blocked websites can produce low-confidence results.
- The score should guide prioritisation, not replace human sales judgement.
Pricing and runtime
This MVP uses bounded website fetches and compact JSON output. Keep batches small for agent workflows; increase only after validating result quality.