Lead List Building.
An ICP brief goes in; a clean, deduped, verified lead list comes out. The AI employee converts your ideal-customer spec into Apollo search filters, pulls and paginates the raw universe, dedupes against your CRM, and delivers to a staging sheet for approval.
How the AI employee does it
(from the Research Analyst playbook)Convert the brief to filters — your ICP spec plus 5 dream customers and 5 bad fits become search filters and a scoring rubric, played back for approval
Pull the universe — paginated Apollo pulls assemble the raw list
Dedupe and suppress — matched against CRM records and suppression lists before delivery
Deliver to staging — a clean Sheet with a Slack summary; a human approves before any CRM upsert
Tools on the job
(official APIs)Apollo.ioGoogle SheetsHubSpotSlack
Full stack on the Research Analyst knowledge base.
Measured by
(the number that matters)Coverage rate — percentage of target records completed with valid contact data (waterfall benchmark ~80%+)
Every action logged and reviewable — how trust works here.
Related tasks
(the staff work together)Put this on someone's desk
(alpha)Rae (Ext. 108) handles lead list building as part of the Research Analyst seat — flat from $499/agent/mo, one agent per dedicated machine. Build the staffer.