skills/sixtysecondsapp/use60/Explorium Enrichment

Explorium Enrichment

SKILL.md

Available Context

@_platform-references/org-variables.md

Explorium Enrichment

Goal

Layer Explorium data onto an existing Ops table. Enrichment turns a raw list of companies or contacts into an actionable, data-rich prospect database — adding financials, intent signals, contact details, technographics, and more.

Credit Cost

Enrichment Type Platform Credits
firmographics 2 / row
financials 2 / row
funding 2 / row
technographics 2 / row
intent (Bombora) 4 / row
traffic 4 / row
workforce 4 / row
contact_details 10 / row
lookalikes 10 / row

Cache is used automatically — if a row was previously enriched with the same type, no credits are consumed. Use force_refresh: true to bypass cache.

Always confirm the estimated cost (row count × credit cost per type) before executing.

Required Capabilities

  • Explorium API: Enrichment endpoints via explorium-enrich edge function
  • Ops Tables: Read and write access to the target Ops table

Inputs

  • table_id: ID of the Ops table to enrich (required)
  • enrich_type: One of firmographics, financials, funding, technographics, intent, traffic, workforce, contact_details, lookalikes, custom
  • column_id: Target column to write into (optional — new column created if omitted)
  • force_refresh: Bypass cache for fresh data (default false)

Execution

  1. Identify the table and enrichment type. If not specified, ask which type to run.
  2. Calculate estimated cost: row_count × credit_cost_per_type
  3. Warn the user: "Enriching X rows with [type] will cost ~Y platform credits. Proceed?"
  4. On confirmation, call explorium-enrich edge function with provided parameters
  5. Report results: enriched count, cached rows, any failures

Enrichment Types — Details

firmographics

Adds company size, industry classification, founding year, headquarters, employee count, and company description. Ideal for companies missing CRM data.

financials

Adds estimated annual revenue, revenue growth rates, and financial health signals.

funding

Adds total funding raised, latest funding round (Series A/B/C etc.), key investors, and funding date. Best for identifying well-funded targets.

technographics

Adds the company's technology stack — CRM, marketing automation, data tools, cloud provider, etc. Useful for competitive displacement campaigns.

intent (Bombora)

Adds active Bombora intent topics and scores for each company — shows what subjects the company is actively researching. High-value signal for timing outreach.

traffic

Adds website traffic metrics — monthly visits, traffic sources, engagement rates, and growth trends.

workforce

Adds headcount trends, recent hiring signals, and department-level growth rates. Useful for identifying companies in a growth phase.

contact_details

Adds verified email addresses and direct phone numbers for each contact row. Highest credit cost — use selectively on best-fit prospects.

lookalikes

Finds companies similar to each row company based on their Explorium profile. Useful for expanding a target list from confirmed good-fit accounts.

custom

AI-powered enrichment with a custom prompt. Generates a column based on existing row data and your instructions.

Output Format

ENRICHMENT COMPLETE
  Table: ICP Prospects — Q1
  Type: contact_details
  Rows processed: 25
  Successfully enriched: 23
  Served from cache: 0
  Failed (no match): 2
  Credits consumed: 230

Error Handling

  • If table_id is missing, ask the user which table to enrich
  • If a row fails to match Explorium records, mark as "Not found" and skip — do not block the rest
  • If credits would exceed a large threshold (e.g. >500 credits), recommend enriching a filtered subset first
  • If enrichment is already running on the table, report current progress rather than starting again

Chaining

  • Typically used after explorium-company-search or explorium-people-search
  • Part of the seq-explorium-icp-discovery sequence — step 3 enriches contact details
  • For intent-based enrichment, explorium-intent-signals is a faster alternative for company search with intent pre-filtered
Weekly Installs
0
First Seen
Jan 1, 1970