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The ABM Intake Pipeline allows you to seamlessly bring external target account lists into SignalArk, instantly turning static spreadsheets into monitored, intelligence-rich entities.

Intake Modes

You can initiate a new intake batch using one of three modes:
  1. CSV Upload: Map your existing spreadsheets (supports flexible header detection for domains, names, and LinkedIn URLs).
  2. Paste Domains: Rapidly paste a list of up to 1,000 domains.
  3. Manual Entry: Build a quick list right in the UI before submitting.

Multi-Tier Resolution Matching

SignalArk doesn’t just blindly create duplicate records. The Intake Engine uses a multi-tier resolution system to match your imports against the existing database, preventing duplicates and preserving historical signal context.
Match TierConfidence ScoreDescription
Exact Domain1.00Perfect match on the company’s primary website domain.
LinkedIn URL0.85Perfect match on the normalized LinkedIn Company URL.
Domain-Derived Name0.65Fuzzy match comparing the stripped domain to the company name.
Exact Name0.55Perfect match on the raw company name string.
Create NewN/ANo match found; a net-new account is created.
Matches with a confidence score below 0.70 are flagged with a needs_review status, allowing your operators to manually verify the match before merging.

Staged Enrichment Tiers

To help you manage credit consumption, the intake process offers four selectable enrichment tiers:
  1. Resolve Only (Free): Maps accounts to the DB and normalizes data. Consumes 0 credits.
  2. Resolve & Enrich: Fetches missing firmographic data via TheCompaniesAPI (TCA) and PDL. Consumes 1 credit per net-new or stale account.
  3. Resolve, Enrich & Score: Includes full ICP scoring and intent calibration post-enrichment.
  4. Full Pipeline: Runs the complete stack, including auto-detecting GTME Plays immediately after import.

Signal Hydration

The magic of the ABM Intake engine happens immediately after resolution. The Signal Hydration step scans SignalArk’s vast historical index and instantly attaches any past market signals or social interactions to your newly imported accounts. Your batch history view provides detailed visibility into this, showing exactly how many accounts in your spreadsheet suddenly have actionable signals attached to them.