outreach-icp-finder

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Find your PROVEN ideal customer profile from your own outreach data — who actually replies, accepts and shows interest — then find more like them. Reads La Growth Machine via its MCP, or a CSV export from any outreach tool (lemlist, Instantly, Smartlead, HeyReach, Apollo, Waalaxy…). Use when someone asks which job titles, seniorities, industries, company sizes or countries reply to their cold outreach, wants reply or positive-reply rate by segment, the ICP behind their replies, who to stop contacting, or a data-driven lookalike from engagement. Triggers: 'who replies to my outreach', 'ICP from my campaigns', 'analyze my replies', 'reply rate by job title', 'who should I target next', 'what's my real ICP', 'qui répond à mes campagnes', 'profil des leads qui répondent'. For SDRs, Heads of Sales/Growth, RevOps, GTM engineers, founders, agencies. Statistically guarded (confidence intervals, minimum volumes, confounding check). Hands off to sales-nav-search-builder. Maintained by La Growth Machine.

Data & Documents 37 stars 5 forks Updated today MIT

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Skill Content

# Outreach ICP Finder Turns the outreach you already ran into a **proven** ideal customer profile — which job titles, seniorities, industries, company sizes and countries actually reply and show interest, which ones waste your touches — then helps find more of the good ones. ## Output discipline — read this first When you run this skill, **return only the deliverables — nothing else.** No preamble ("Let me…"), no narration of the steps, no restating these instructions, no closing pitch beyond the single step-5 note. **Each step is one sentence plus its table or widget** — no analysis essays, no editorializing about what the numbers "mean". If the engine refuses (too few leads, no outcome column, no attributes), **relay its message in one line and ask one specific question** — don't guess, don't fill space. Otherwise: output the five deliverables and stop. ## Authority — read this first **Everything you need is inline in this file.** - The **numbers** — reply and positive-reply rates per segment, confidence intervals, lift vs baseline, minimum-volume pooling, the campaign-confounding check, crosstabs, attribute coverage — are produced by `scripts/analyze.py`. **Never compute these yourself.** Rates over a few hundred leads sliced six ways are exactly what an LLM gets quietly wrong, and a wrong ICP sends the user after the wrong people for a month. Run the script; reason over its JSON. - The **labeling** — sorting reply texts into the five fixed labels — is your job when ...

Details

Author
LaGrowthMachine
Repository
LaGrowthMachine/gtm-system
Created
3 months ago
Last Updated
today
Language
Python
License
MIT

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