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Lead enrichment automatically appends valuable data to captured leads, giving your sales team the context they need to close deals.
Updated in v2.8: New domain-resolution pre-stage, verified billing addresses with alternate-address review, needs_review workflow, duplicate detection, and automatic phone-number lookup with built-in fallback. See Release Notes for details.

What Gets Enriched

Contact Data

FieldDescription
TitleJob title (e.g., “VP of Operations”)
DepartmentFunction (Sales, Engineering, etc.)
LinkedInLinkedIn profile URL
Direct PhoneDirect dial number
Personal EmailAdditional email addresses

Company Data

FieldDescription
Company NameOfficial company name
DomainCompany website
IndustryIndustry classification
Employee CountCompany size
RevenueEstimated annual revenue
LocationHeadquarters location
TechnologiesTech stack used
FundingRecent funding info
Verified AddressStreet, city, state, postal code, and country
SegmentSpecific business classification (e.g., “Mid-market manufacturer of structural steel”)

Enrichment Triggers

Enrich immediately when leads are captured:
  • on_capture: Enrich as soon as lead is created
  • on_qualify: Enrich only when lead meets criteria

Manual

Enrich on demand:
  1. Go to lead detail page
  2. Click Enrich
  3. Wait for data to populate

Batch — Selection-Driven Enrich Button

The Enrich button at the top of the Leads (and Accounts) table retargets based on what’s selected:
Selection stateButton labelWhat gets enriched
Nothing selectedEnrich First 50 of N FilteredFirst 50 rows of the current filtered page
1–50 rows checkedEnrich N SelectedExactly those rows
51+ rows checkedEnrich First 50 of N SelectedFirst 50 of the checked set
Select-all-across-pages onEnrich First 50 of N SelectedFirst 50 across the whole session, minus any rows you’ve excluded
Server-side BATCH_LIMIT = 50 is intentional — pick the 50 highest-priority rows and run again rather than raising the cap. The button is disabled while any visible row is already queued or enriching.

Per-Column Fill

You don’t have to re-run the whole pipeline to refresh a single value. Each enrichable column has its own Fill action — an icon next to the column header (and a per-row variant where available) that re-fills just that field for the targeted rows. Four pipelines share the registry; each owns a distinct slice:
PipelineFields it owns
Web researchindustry, revenue, employees, founded, segment, funding
Company resolver (Claude 4.6 fallback)domain, website, companyName, address
GPTwhyThisAccount, whyNow, priorityAction (intelligence explanations)
Contact lookupprimaryContact (name / email / phone discovered together)
Each cell tracks its own lifecycle state (<field>_fill_status = queuedfillingNULL) and shows a Queued… or Filling… badge live. “Fill domain” never touches website / name / address; “Fill industry” never touches revenue.

Prerequisite Check

Per-column Fill only runs when each row has enough input for the pipeline. The column-header button is disabled with a tooltip if any visible row is missing a prerequisite:
PipelineRequired input
Web researchCompany name or website/domain
Company resolverCompany name
GPT intelligenceCompany name
Contact lookupCompany name or website/domain
The tooltip names the missing field(s) so you can fix the gap or narrow the selection.
Use per-column Fill when only one field needs refreshing — re-enriching a whole row costs a full pipeline pass and overwrites nothing already set.

Hover for Source Citations

Enriched Revenue, Employees, and Industry cells carry per-field citations from the original lookup. Hover any of those cells to reveal a tooltip with the citation URL, page title, and the model’s confidence when reported. Rows enriched before the citations layer shipped keep the tooltip hidden — re-enriching (or per-column Fill) will populate citations going forward.

The Enrichment Pipeline

Each enrichment run flows through several stages.

Stage 0 — Domain Resolution

Before any lookup runs, an AI step resolves messy company strings — abbreviations, misspellings, customer-list short codes — into a canonical domain. This dramatically improves match rates downstream and lets enrichment work on rows that only have a company name.
Internal acronyms in your customer list (e.g., “DOFASC” → “Dofasco”) are auto-expanded during this stage so they match real company records.

Stage 1 — Decision-Maker Discovery

Searches the company for decision-makers and surfaces the most senior contact available. If a primary contact already exists on the lead or account, newly discovered contacts land as secondary contacts rather than overwriting the primary. Phone-only primaries created from import are preserved.

Stage 2 — Company Data

Populates verified company data including industry, employee count, revenue, technologies, headquarters address, and a specific segment classification.

Stage 3 — Phone Reveal

Requests a direct mobile number for the primary contact. If the initial lookup doesn’t return a number quickly, the system automatically falls back to a secondary source so the Mobile column populates reliably.

Stage 4 — CRM Sync, Intelligence & Embeddings

The pipeline finishes with CRM sync (if a CRM is connected), AI intelligence scoring — fit score, timing signal, and priority actions — and vector embeddings that power natural-language semantic search on both leads and accounts.

Estimated Run Time

Enrichment runs in batches of up to 100 leads or accounts at a time, with the actual batch size adjusted in real time based on available resources. This applies to all enrichment — auto-enrichment on import, manual single-row enrichment, and bulk re-enrichment. Plan for roughly 12 minutes per batch end-to-end. Rows that match an existing record (duplicates) are skipped by auto-enrichment but can be enriched manually.

Revenue Formatting

Revenue is stored as a raw integer and rendered everywhere through formatRevenue:
Raw valueDisplayed
1_500_000_000$1.5B
50_000_000$50M
250_000$250K
999$999
0, negative, or null
The web-research prompt is constrained to return a clean integer (no $, no K/M/B, no ranges, no “approx”), and pre-EMA-263 rows with messy strings are normalized on read.

Overwrite Behavior

Enrichment never overwrites existing data. If a field already has a value, it’s preserved; if it’s empty, enrichment fills it in. This applies to every enriched field — name, email, phone, title, LinkedIn URL, company info, and so on. Addresses are handled with an extra layer: a verified billing address that differs from the existing one is stored as an alternate address for you to Accept or Keep Existing rather than being applied silently. Decision-maker contacts follow the same principle — newly discovered contacts land as secondary contacts when a primary already exists, and never replace the primary automatically.

Verified Addresses & Alternate Addresses

When enrichment returns a verified billing address that differs from the address already on the record, the new address is stored as an alternate instead of silently overwriting the existing one. The drawer’s Address section grows an Alternate Addresses card with Accept and Keep Existing buttons so you can promote or dismiss each candidate.
ActionEffect
AcceptPromotes the alternate to be the primary address; the previous primary is archived
Keep ExistingDismisses the alternate; the existing address remains

Enrichment Review

After a batch run completes, the Enrichment Review dialog highlights every row with discrepancies between previously stored data and the newly enriched values. Each row is tagged:
TagMeaning
matchExisting data matched the enrichment result — no action needed
auto_filledField was empty before; enrichment populated it
kept_existingExisting value was preserved (e.g., primary address protected)
mismatchExisting value disagrees with enrichment; review recommended
uncertainEnrichment could not establish high confidence
Synthetic alternate-address cards are surfaced inline so you can resolve them in a single review pass.

The needs_review Status

Rows that require human attention now move to a dedicated needs_review state — surfaced as an amber pill in the table and an N need review count badge next to the enrichment ETA. Filtering the status column shows friendly labels for each state. Common reasons a row enters needs_review:
  • Enrichment matched a domain already claimed by another lead or account (potential duplicate)
  • An alternate address was returned that disagrees with the existing primary
  • Confidence on a critical field is below threshold

Duplicate Detection

If enrichment resolves to a domain that’s already claimed by another row, the second row is flagged needs_review and the Duplicate Review dialog gives you three choices:
OptionEffect
Keep SeparateTreats both rows as distinct; clears the review flag
MergeFolds the new row into the existing record, preserving custom fields and tags
DeleteRemoves the duplicate row entirely
Duplicate detection runs on both leads and accounts, with parity in the review experience.

Enrichment Quality

Match Confidence

Enrichment results carry a confidence label that’s surfaced on alternate-address cards and contact matches:
LabelMeaning
HighStrong match — high reliability
MediumGood match — review recommended
LowUncertain — review before relying on the value

Handling Low Confidence

Low-confidence fields are tagged uncertain in the Enrichment Review dialog, and rows containing them move to the needs_review state so they’re easy to spot and action manually.

Monitoring Enrichment

Dashboard Metrics

MetricDescription
Enrichment Rate% of leads enriched
Match Rate% with high-confidence match
Needs ReviewRows flagged for manual attention
FailedEnrichment failures

Enrichment Status

StatusMeaning
PendingQueued for enrichment
ProcessingCurrently enriching
EnrichedSuccessfully completed
PartialSome fields populated
Needs ReviewRequires manual review (duplicate suspected, alternate address, or low-confidence field)
FailedCould not enrich
No MatchNo matching record found

Troubleshooting

  • Verify email address is correct
  • Check company name spelling
  • Try with different email domain
  • Lead may not be in the enrichment database
  • Enrichment data may be stale
  • Request re-enrichment
  • Report to the enrichment provider for update
  • Re-run enrichment from the row’s drawer or the Bulk Actions menu
  • Check the row’s status — needs_review rows require manual action before re-enrichment will help
  • If the failure persists across many rows, contact support

Best Practices

Enrich Strategically

Enrich leads that matter. Use ICP scoring to prioritize enrichment for high-potential leads.

Validate Before Enriching

Ensure email is valid before enriching:
  • Check format
  • Verify domain exists
  • Remove obvious test/fake emails

Monitor Quality

Regularly review enrichment quality:
  • Spot check enriched data
  • Track match rates and the needs_review count
  • Action needs_review rows promptly so the queue doesn’t pile up

Next Steps

ICP Scoring

Score enriched leads

CRM Sync

Push to CRM

Lead Capture

Capture configuration

Integrations

Other integrations