nw-jtbd-analysis

Solid

JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring

AI & Automation 526 stars 55 forks Updated 1 weeks ago MIT

Install

View on GitHub

Quality Score: 92/100

Stars 20%
91
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# JTBD Analysis ## Core Principle A job is the progress a person is trying to make in a particular circumstance. Jobs are stable over time — technology changes, jobs don't. People hire products to make progress; they fire them when they fail. **The trap**: Feature requests describe a proposed solution, not the underlying job. Always extract the job first. --- ## Job Statement Format ``` When [situation/trigger], I want to [motivation/action], so I can [expected outcome] ``` **Examples (good)**: - "When I'm hosting a virtual networking event, I want to facilitate natural conversations between strangers, so I can create valuable connections that wouldn't happen otherwise." - "When I join an event as a participant, I want to quickly find relevant people to talk to, so I can maximize the value of my limited time." --- ## Job Types — Extract All Three | Type | Question | Example | |------|----------|---------| | Functional | What task is the user trying to accomplish? | Find someone with complementary expertise | | Emotional | How does the user want to feel? | Feel confident approaching strangers | | Social | How does the user want to be perceived? | Appear professional and well-connected | --- ## Abstraction Layers — Navigate to the Real Job Jobs usually live at strategic or physical level, not tactical. | Layer | Question | Example | |-------|----------|---------| | Tactical | How do we improve this interaction? | Better drag-and-drop for notes | | Operational | Wh...

Details

Author
nWave-ai
Repository
nWave-ai/nWave
Created
3 months ago
Last Updated
1 weeks ago
Language
Python
License
MIT

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Featured

jobs-to-be-done-analyst

One sentence - what this skill does and when to invoke it

39,350 Updated today
sickn33
Data & Documents Listed

jtbd-extractor

Turn raw research into Jobs-to-be-Done statements showing what users are really trying to accomplish. Use when: extract jobs, jtbd analysis, jobs to be done, what job is the user hiring, underlying user needs.

0 Updated today
varunk130
AI & Automation Listed

jtbd-analysis

Analyze customer motivations using Jobs-to-be-Done and Forces of Progress. Use when asked about jobs-to-be-done, why customers switch products, what job a product is hired for, or when analyzing the forces that drive or resist product adoption.

2 Updated today
AashutoshR2062
Data & Documents Listed

jobs-to-be-done-extractor

Extracts Jobs-to-be-Done (JTBD) statements (functional, emotional, social) from raw research - interviews, surveys, support tickets, sales calls - and produces a job map with progress measures and outcome statements. Use when reframing a product around customer outcomes, segmenting beyond demographics, building a competitive switching analysis, prioritizing features, or aligning product, marketing, and sales on the same job.

1 Updated today
varunk130
AI & Automation Listed

thinking-jobs-to-be-done

Understand what "job" users hire your product to do, focusing on progress users seek rather than features. Use for product development, feature prioritization, user research, and market positioning.

1 Updated today
babypochi06