Summary
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.
Install to Claude Code
npx -y skills add onewave-ai/claude-skills --skill lookalike-customer-finder --agent claude-codeInstalls into .claude/skills of the current project.
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Files
SKILL.mdView on GitHub
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.
Contents
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.
Workflow
- Collect the best customers provided. If none are given, ask for the top 5-10 accounts.
- Analyze common characteristics across them. See
references/scoring-model.mdfor the five profile dimensions. - Build the Ideal Customer Profile (ICP) from those shared traits.
- Search the market for companies matching the ICP. Pull firmographics, tech stack, growth signals, and contacts from the tools in
references/data-sources.md. - Score each candidate 0-100 using the weighted scoring model in
references/scoring-model.md. - Rank and tier the companies by score (Tier 1: top 10, Tier 2: next 40, Tier 3: next 50).
- Produce the report following
references/output-template.md, including market insights, a tiered targeting strategy, and a quick-start action plan. - Apply the best practices in
references/examples.mdthroughout: favor quality over quantity, weight growth signals, and enrich contacts before recommending outreach.
Featured
Plug Mailtrap into your AI workflow and let it handle the email.
Connect Mailtrap MCP →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →Make coding agent sessions - Searchable, Shareable, Vendor-neutral & Scored.
Try For Free →Your agent targets a perfect 10 Code Health score. Deterministic. Every commit.
Try For Free →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →belt cli automatically finds the best tools and skills for your agent. image, video, music, tts...
one prompt install →First SeenJun 3, 2026
