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Ideal Customer Profile Skill for ChatGPT: Combine Interviews and Adoption Data

Combine customer research, adoption speed, and retention signals to define who is likely to get value. Capture the job, buying behavior, pain points, qualification criteria, and open hypotheses.

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Install in ChatGPT

Use an eligible ChatGPT workspace with permission to create skills and, for uploads, upload permission. The installation path for this text-only adaptation was checked against OpenAI documentation. Workspace runtime verification is pending.

  1. Download pm-go-to-market/skills/ideal-customer-profile/SKILL.md from the pinned GitHub source. Keep the name, description, and instructions for ideal-customer-profile together as a standalone text skill.
  2. In a ChatGPT workspace with skills and uploads enabled, open Plugins, Skills, Create, and Upload from your computer. Choose a skill package format accepted by the file picker. You can also choose Create with editor and enter the original name, description, and instructions.
  3. After the scan completes, check that ideal-customer-profile appears in Installed. Type @ in a new chat, select the skill, and use the fictional example on this page to check the output.

Example task

For a fictional scheduling tool, three of four small training centers launched a class within a week, while two large schools stayed in approval for over a month. Interviews say small centers care about substitute-teacher confirmation. Draft a preliminary ICP, evidence to validate, and a secondary segment.

What to check

The draft should prioritize small training centers tentatively, tie their job to substitute confirmation and show the adoption evidence. Flag the six-customer sample and note that approval length for large schools requires more validation.

Original SKILL.md on GitHub · Updated

Frequently asked question

Can I define the ICP with industry and company size alone?

Use industry and size as filters alongside the job, buying process, and signals of continuing value. Compare adoption and retention across segments to see what company size leaves unexplained.