build-tam

Size Total Addressable Market by filtering ICP criteria across data providers.

49|11|Updated Feb 21, 2026
One-click install
npx skills add https://github.com/getaero-io/gtm-eng-skills --skill build-tam
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: build-tam
Source: https://github.com/getaero-io/gtm-eng-skills/tree/main/skills/build-tam
Command: npx skills add https://github.com/getaero-io/gtm-eng-skills --skill build-tam

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Size and prioritize your Total Addressable Market (TAM) by filtering ICP criteria across multiple data providers to identify true market scope.

Core Features & Use Cases

  • Size TAM virtually with per_page: 1 to validate ICP filters before full pulls.
  • Support both company-first and contact-first TAM workflows and translate signals into Apollo search parameters.
  • Post-pull enrichment and signal-driven prioritization to rank and refine target lists.

Quick Start

Describe your ICP and run the TAM sizing with the Deepline CLI to generate your initial TAM.

Frequently Asked Questions about build-tam

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I size my Total Addressable Market using ICP filters?

To size your Total Addressable Market (TAM), apply your Ideal Customer Profile (ICP) criteria across multiple data providers. The system validates filters virtually with per_page: 1 before executing full pulls to compile your lead lists.

Can I translate niche signal discovery output into Apollo search parameters?

Yes, you can translate niche signal discovery output into Apollo search parameters. This allows you to seamlessly transition from signal-driven prioritization to executing targeted lead generation workflows.

What is the difference between company-first and contact-first TAM workflows?

Company-first TAM workflows size market scope by filtering organizational criteria first, while contact-first workflows prioritize individual professional attributes. Both approaches validate filters and apply post-pull enrichment to rank target lists.

How do I validate ICP filters before executing a full market pull?

You validate ICP filters by running a virtual sizing check using per_page: 1. This lightweight query tests your criteria against data providers to ensure accuracy before executing full data pulls and post-pull enrichment.

Does this TAM sizing approach support post-pull enrichment for lead generation?

Yes, the TAM sizing approach supports post-pull enrichment. After executing full data pulls, it applies signal-driven prioritization to rank and refine your target lists, ensuring high-quality lead generation output.