Lookalike Customer Finder

Takes your best customers and finds 100+ companies that match the same profile using firmographic data, tech stack, growth signals, and a weighted similarity scoring model. The output is genuinely useful: you get ranked prospects with specific contact intelligence, recommended outreach approaches, and a three-tier targeting strategy. The scoring breakdown (industry match 25%, company size 20%, tech stack 15%) is transparent about what drives the recommendations. Good for building target account lists when you're expanding into new markets or need to replicate successful customer patterns. The tier system with expected response rates helps you prioritize outreach realistically instead of treating all lookalikes equally.

skills.sh installs: 339
GitHub stars: 422
last updated: Aug 21, 2026

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Install

$ npx -y skills add onewave-ai/claude-skills --skill lookalike-customer-finder --agent claude-code

Installs into .claude/skills of the current project.

Files

Lookalike Customer Finder

Analyze a company's best customers and find similar companies that match the same profile, producing a high-quality, ranked target account list.

references/scoring-model.md - Profile dimensions, weighted scoring model, and score bands.
references/output-template.md - Full Markdown report structure (ICP, ranked lookalikes, market insights, targeting strategy, action plan).
references/data-sources.md - Recommended enrichment tools and data points to gather.
references/examples.md - Best practices, trigger phrases, and an example request.