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ProspectLayer
Normalize and dedupe messy results into canonical Prospects | ProspectLayer

ProspectLayer

Normalize and dedupe messy results into canonical Prospects

Collapse duplicates automatically using website, phone, name+address, and geo proximity rules to produce one clean record per business.

Dedupe keys configuration
Website, phone, name+address, geo proximity
Canonical prospect view with sources
Canonical record with provenance

Overview

Collapse duplicates automatically using website, phone, name+address, and geo proximity rules to produce one clean record per business.

Problem

Raw listings are messy: duplicates, inconsistent formatting, missing fields, and slight name/address variations create wasted outreach and unreliable segmentation.

Solution

ProspectLayer normalizes and dedupes results into a canonical Prospect model with provenance (sources) and configurable strict/relaxed dedupe modes.

How it works

As results are saved, ProspectLayer normalizes phones, websites, and address components, then applies dedupe keys in order (website → phone → name+address → optional geo proximity threshold). Strict mode favors fewer duplicates; relaxed mode increases coverage. Lists reference canonical Prospects so the same business doesn’t fragment across workflows.

Who is this for

Sales Ops / RevOps Agencies Growth Ops

Expected outcomes

  • Cleaner lists with fewer duplicates
  • More reliable exports and downstream activation

Key metrics

Duplicate rate in saved lists

Baseline

15 %

Target

2 %

Prospects with normalized website/phone

Baseline

55 %

Target

95 %

Gallery

Dedupe keys configuration
Website, phone, name+address, geo proximity
Canonical prospect view with sources
Canonical record with provenance

Downloads & templates

Security impact

  • Canonical prospect records + source snapshots (short TTL where configured) · PII: business contact info

Compliance

  • GDPR
  • SOC2

Availability & next steps

Starter Growth Enterprise