Claude Cowork scores leads from social engagement
Montaldo reports using Cowork to extract and enrich social commenters, score customer fit and produce spreadsheets and tailored outreach drafts.
Original prompt
Shared by the source author. See source notes for context.
Enrich these people via Apollo. Add title, company, location, and email where available. Skip the company pages.
Reach people exploring AI agents
See placements →Evidence at a glance
Sourced account- Source author
- Pietro Montaldo
- Original account
- Read the source ↗
- Published
- Source link checked
- Reported result
- Montaldo reports using Cowork to extract and enrich social commenters, score customer fit and produce spreadsheets and tailored outreach drafts.
- Human involvement
- Montaldo selects the audience and offer and supplies customer context. Apollo requests approval before using credits; drafts still need review.
A linked account supports attribution. It does not mean we independently reproduced its result.
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How the agent did it
- Choose a relevant social post and extract commenters with Apify.
- Enrich individual profiles with Apollo after credit approval.
- Score records against the supplied customer profile and draft messages for strong fits.
Pietro Montaldo describes a lead research workflow he uses to promote events and offers. He gives Claude Cowork a social post relevant to his audience and has it collect the people who commented, including their profile links and comments. The agent chooses an Apify actor to perform the extraction.
Apollo then enriches the list with roles, companies, locations and available email addresses. Cowork compares those records with the author's ideal customer profile and ranks them from zero to five. The best fits receive draft messages that refer to their actual comment and the event or offer being promoted.
Montaldo turns the repeated process into a skill returning a spreadsheet, CSV and draft messages. The article reports response and signup figures, but provides no measurement records to establish attribution, so those figures are not treated as verified performance. The human supplies business context and selects the post and offer. The source also says Apollo asks before spending credits. This case records a working research-and-drafting process rather than assuming every discovered address is correct or every proposed message has been sent.
Prompt
Original prompt
Source: Blog · Pietro Montaldo
Frequently asked questions
What does Apify collect?
The described run collects commenters, their comments and their profile links.
How are prospects selected?
Cowork scores them against the author’s ideal customer profile and focuses drafts on scores of four or five.
When are enrichment costs approved?
The account says Apollo checks with the user before spending credits.
More details
Remaining steps
- Save the repeated workflow as a skill with spreadsheet and CSV outputs.
About this account
Cowork selected an Apify scraper, extracted commenters, enriched records through Apollo and scored leads against the supplied business context.
Firsthand account read. Original Substack article visibly dated Jul 08, 2026. Reported response and signup figures are not independently verified. Reported outcomes were not independently reproduced. Original prompt box contains an exact short excerpt of the published task prompt.
Credit: Pietro Montaldo
Source published
Added to Agents In Use
Source checked
Tools and topics
Claude Cowork · Apify · Apollo · Spreadsheet
Claude Cowork · Apify · Apollo
Editorial completeness: 100/100. Measures documented fields, not agent performance or verified outcomes.