Qualify scraped leads and draft custom openers

They used Claude Code to check scraped prospects against a list, pull in recent company news, and draft tailored opening lines.

Done with Claude Codeยท Intermediate

What they did
They gave Claude Code a prospect list along with fresh company updates so it could do the research work around outreach. From there, it filtered leads that met their criteria and wrote several opening-line options shaped by the company context. A human still checked the output before anything else happened.
How it went
The approach handled more context than ChatGPT, and the openers sounded less obviously machine-written. The main problem was invented details, so the output was useful but not something to trust without review.
Tips
Use it for research-heavy prospecting, but verify every company fact before using the text. Keep a person in the loop for anything that might rely on a made-up detail.

Try it yourself with Claude Code

I have a scraped lead list at [file or folder]. First, qualify each lead against [your criteria]. For the leads that pass, research recent company news and write [number] different opening lines for each one that weave in a real, specific detail from that news. Include the source link next to each opener, save everything to [output file], and pause for my approval before doing anything that sends, submits, deletes, or changes records. Then tell me how many leads qualified and flag any details you could not verify.

Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.

Read the original on reddit.com โ†—

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