Definition
Lead generation with Claude means teaching it your customer profile once, then running repeatable patterns that source and score prospects against it and qualify a raw list with reasons. A Harvard Business Review study of 2.24 million leads found within-an-hour response makes a lead nearly 7x more likely to qualify.
To generate and score leads with Claude, teach it your customer profile once, then run two repeatable patterns: one that sources and scores prospects against that profile, and one that gates a raw list and tells you why each lead is in or out. The output is a ranked shortlist with reasons, not a spreadsheet of 500 names.
Scoring matters because speed on the right leads decides the deal. A Harvard Business Review study of 2.24 million leads found firms that responded within an hour were nearly 7 times more likely to qualify a lead than those that waited even 60 minutes longer (Harvard Business Review, 2.24M-lead study). A score tells you which leads earn that fast response. This is one repeatable job inside Claude as a business operating system.
- Responding within an hour makes a lead nearly 7x more likely to qualify (Harvard Business Review).
- Lead scoring decides which leads earn the fast response, so the work goes where it pays.
- Two repeatable patterns cover it: source-and-score, and qualify-with-reasons.
- Both read your customer profile, so the score reflects your business, not a generic template.
Why Score Before You Chase?
Most lead lists are noise with a few real buyers hidden inside. Without a score, the team treats all of them the same, which means the best leads wait while someone works a dead one. A score against your actual customer profile sorts the list so the fast response lands on the leads that convert.
What Are The Two Patterns?
Once Claude knows your customer profile, these run on it.
| Pattern | What it does | Output |
|---|---|---|
| lead-research | Sources prospects that match your profile | A scored, tiered list (hot, warm, cold) |
| lead-qualify | Gates a raw list against your profile | Keep or cut, with a reason for each |
Can You Try It Without Installing?
Yes. Paste this into Claude to score a raw list now.
Here is my customer profile: [describe your best customers in 3 lines]. I will paste a list of leads. Score each from 0 to 100 on fit to that profile, sort hot, warm, and cold, and give one sentence on why each lead is in or out. Flag any I should not waste time on.
That gets you a scored list today. A repeatable pattern keeps your profile on file, verifies leads against live sources, and logs each run so the next list builds on the last.
How Should A Score Be Built?
A useful score reads three axes, not one. Fit: does the lead match your profile. Timing: is there a reason to act now. Accessibility: can you actually reach a decision-maker. A lead that is a perfect fit but unreachable is not a hot lead. Scoring all three stops the team from chasing names that will never close.
Methodology
The response-time figure is from the Harvard Business Review analysis of 2.24 million leads, linked above. The skill descriptions reflect public Conversion Skills patterns for lead research and qualification. Conversion System publishes no client outcome numbers, so none appear here. The point is to put the fast response on the leads that earn it.
Inspect the lead-scoring pattern
Conversion Skills shows how we structure repeatable AI work around profile, fit, timing, and review.
Explore Conversion SkillsRelated: Claude as a business operating system · AI lead scoring implementation · Lead scoring and qualification guide
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