Claude Code researches prospects from local criteria

A non-coder describes replacing a cumbersome prospecting setup with Claude Code and three services. A local text file defines the ideal customer profile: industry, headcount, funding stage and target personas. Claude reads that context before querying Crustdata for companies, matching people, hiring signals and recent social activity.

FullEnrich checks contact information through multiple providers, while Instantly supplies the delivery layer. Claude uses a contact's recent posts to draft an opener tied to a specific observation. Webhooks alert the operator to job changes or relevant hiring activity, prompting additional outreach preparation. The author reports constructing the system over a weekend and using it in place of the previous tool combination.

The practical failure was expensive API selection: the author initially used a real-time endpoint when cached data would usually suffice, consuming more credits. Personalisation still needed work, and some alerts triggered on irrelevant job postings. The post does not specify a human approval gate before every send, so readers should not infer one from the presence of drafted text. No reply-rate or revenue benchmark is supplied. The copyable detail is to make targeting criteria persistent and explicit, then separate structured retrieval, verified enrichment and evidence-based writing rather than relying on a free-form company search alone.

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Source: Reddit · u/Unspoken_Table on Reddit