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Account enrichment automatically appends company data, decision-maker contacts, verified addresses, and AI intelligence scoring to each account — giving your team the context they need to prioritize outreach and 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.
The enrichment pipeline is shared with leads — same stages, same behavior, same review tools. This page describes it from the account perspective.
The Fit Score is produced by an LLM synthesis pass over five weighted insight categories. Each category gets its own 1–100 sub-score and short reasoning paragraph; the headline Fit Score is the synthesis output, not a hand-tuned linear formula.
Insight
What it measures
Firmographic Fit
Industry, employee count, revenue, growth stage vs your ICP
Recent Activity
Funding, hiring, product launches, news in the trailing window
Pain Points / Needs
Likely challenges inferred from industry, size, and tech stack
Decision-Maker Access
Who to contact, typical buying process for the account size
Re-running enrichment (or any per-column Fill that changes a firmographic input) recomputes the Fit Score on the next pipeline pass. You can also re-compute the three intelligence explanations individually via per-column Fill.
When importing accounts via the Import Wizard, the Auto-enrich imported accounts toggle on the Column Mapping step runs enrichment automatically as soon as rows land. Matched/duplicate rows are skipped — you can run enrichment on them manually if needed.
The Enrich button at the top of the Accounts (and Leads) table retargets based on what’s selected:
Selection state
Button label
What gets enriched
Nothing selected
Enrich First 50 of N Filtered
First 50 rows of the current filtered page (legacy default)
1–50 rows checked
Enrich N Selected
Exactly those rows
51+ rows checked
Enrich First 50 of N Selected
First 50 of the checked set
Select-all-across-pages on
Enrich First 50 of N Selected
First 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.
You don’t have to re-run the whole pipeline to refresh a single value. Each enrichable column on the Accounts and Leads tables 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:
Each cell tracks its own lifecycle state in the DB (<field>_fill_status = queued → filling → NULL) so the cell shows a Queued… or Filling… badge live without polling other columns. Each pipeline only asks for the slice it owns — “Fill domain” never touches website, name, or address; “Fill industry” never touches revenue.
Per-column Fill only runs when each row has enough input for the pipeline to ground the lookup. The column-header button is disabled with a tooltip if any visible row is missing a prerequisite:
Pipeline
Required input
Web research
Company name or website/domain
Company resolver
Company name
GPT intelligence
Company name
Contact lookup
Company 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 you only need one field refreshed — re-enriching a whole row costs a full pipeline pass and overwrites nothing that’s already set. Targeted Fill is also the right tool when a single provider returned — and you want to retry just that slice.
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 that grounded the value (typically a LinkedIn company page or industry profile)
The page title so you can confirm the source before clicking through
The model’s confidence when reported (high / medium / low)
If a row was enriched before the citations layer shipped, the tooltip stays hidden — there’s no “Sources unavailable” placeholder cluttering the cell. Re-enriching (or per-column Fill) will populate citations going forward.
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.
Searches the company for decision-makers and surfaces the most senior contact available, attaching them to the account’s Contacts tab.If a primary contact already exists on the account, newly discovered contacts land as secondary contacts rather than overwriting the primary. Phone-only primaries created from import are preserved.
Populates verified company data including industry, employee count, revenue, technologies, headquarters address, and a specific segment classification.
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.
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 across your account base.
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 is stored as a raw integer and rendered everywhere through a single formatRevenue helper:
Raw value
Displayed
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 Fill-revenue paths route through the same helper. Pre-EMA-263 rows with messy strings are normalized on read.
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.
When enrichment returns a verified billing address that differs from the address already on the account, 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.
Action
Effect
Accept
Promotes the alternate to be the primary address; the previous primary is archived
Keep Existing
Dismisses the alternate; the existing address remains
After a batch run completes, the Enrichment Review dialog highlights every account with discrepancies between previously stored data and the newly enriched values. Each row is tagged:
Tag
Meaning
match
Existing data matched the enrichment result — no action needed
auto_filled
Field was empty before; enrichment populated it
kept_existing
Existing value was preserved (e.g., primary address protected)
mismatch
Existing value disagrees with enrichment; review recommended
uncertain
Enrichment could not establish high confidence
Synthetic alternate-address cards are surfaced inline so you can resolve them in a single review pass.
Accounts that require human attention 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 an account enters needs_review:
Enrichment matched a domain already claimed by another account (potential duplicate)
An alternate address was returned that disagrees with the existing primary
If enrichment resolves to a domain that’s already claimed by another account, the second account is flagged needs_review and the Duplicate Review dialog gives you three choices:
Option
Effect
Keep Separate
Treats both accounts as distinct; clears the review flag
Merge
Folds the new account into the existing record, preserving custom fields, tags, and contacts
Delete
Removes the duplicate account entirely
Duplicate detection runs on both leads and accounts, with parity in the review experience.
Vector embeddings produced in Stage 4 power natural-language search across your account base. Type a query like “mid-market manufacturers in the Midwest hiring engineers” and the system returns the closest-matching accounts ranked by similarity.
Low-confidence fields are tagged uncertain in the Enrichment Review dialog, and accounts containing them move to the needs_review state so they’re easy to spot and action manually.
When enrichment surfaces alternate addresses, action them quickly so your account records reflect ground truth. Stale alternates can clutter the drawer and obscure what’s authoritative.
