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buyer-job-intent-analysis

Extract evidence-graded buyer jobs, forces, and language from customer and market sources.

663|47|Updated May 19, 2026
Search Tags:#customer research#prompt architecture#evidence grading#buyer intent#icp analysis#Jobs to Be Done#Market Research
One-click install
npx skills add https://github.com/elvisun/newsjack --skill buyer-job-intent-analysis
Or copy as Structured Prompt for Agentโ–ผ
Please help me install this Agent Skill.
Skill: buyer-job-intent-analysis
Source: https://github.com/elvisun/newsjack/tree/main/skills/buyer-job-intent-analysis
Command: npx skills add https://github.com/elvisun/newsjack --skill buyer-job-intent-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Teams often invent buyer demand from product features instead of real evidence. This Skill recovers source-bound buyer jobs, struggling moments, desired progress, and authentic customer language from interviews, reviews, search queries, and market evidence before designing an AI-visibility prompt architecture.

Core Features & Use Cases

  • Evidence-graded job extraction: Pulls struggling moments, desired progress, workarounds, push/pull/anxiety/habit forces, and decision criteria from supplied sources, grading each finding A through D by provenance.
  • Structured intent modeling: Classifies each job along independent axes of information act (explain, diagnose, compare, buy, etc.), journey state, and optional funnel stage without inferring intent from keywords.
  • Auditable output: Produces a human-readable Markdown report plus a schema-versioned buyer_jobs.json with source IDs, language samples, confidence levels, and a Gate 2 readiness decision.
  • Use Case: Given approved ICP hypotheses and a manifest of customer interviews, support tickets, and forum threads, generate a ranked set of buyer jobs with verbatim language samples to feed a downstream prompt-design step.

Quick Start

Analyze the approved ICP hypotheses and source manifest to extract evidence-graded buyer jobs and write buyer_jobs.json.

Frequently Asked Questions about buyer-job-intent-analysis

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

FAQPage Schema
How do I extract buyer jobs from customer interviews and reviews?โ–ผ

Supply approved ICP hypotheses and a source manifest containing your interviews, reviews, or support material. The skill extracts struggling moments, desired progress, workarounds, and forces, linking every component to source IDs with an evidence grade.

What evidence sources can I use for buyer intent analysis?โ–ผ

Supported sources include customer interviews, on-site search and support logs, paid-search and Search Console queries, public reviews, forums, RFPs, and procurement guides. Each source is graded A through D based on provenance and directness.

How does evidence grading work in buyer job analysis?โ–ผ

Evidence is graded A (direct verbatim customer language), B (credible public-market proxy), C (company assertion needing approval), or D (LLM expansion for discovery only). Only graded, source-linked findings enter the final buyer_jobs.json output.

Can I use LLM-generated queries as buyer demand evidence?โ–ผ

LLM expansions are allowed only as grade D rotating discovery material and must be marked hypothesis_only with low confidence. They cannot supply category prevalence, market frequency counts, or copied prompts.

What inputs are required before running buyer job intent analysis?โ–ผ

You need an approved icp_hypotheses.json file and a source_manifest.json with permission and provenance metadata. Without these, the gate status returns needs_research or stop_permission_failure instead of producing jobs.

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