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The Jobs-to-be-Done framework as applied product methodology. Job statements, struggling moments, hire and fire criteria, the difference between feature-thinking and job-thinking. Honest about where JTBD adds clarity (discovery, prioritization, positioning) and where it becomes performative ritual (job-statement workshops that do not drive decisions, persona-theater disguised as JTBD). Triggers on jobs-to-be-done, JTBD, job statements, struggling moments, hire criteria, fire criteria, switch triggers, functional emotional social jobs, outcome-driven innovation. Also triggers when a team is over-relying on feature-request lists or persona archetypes that do not drive product decisions, when a positioning conversation needs the framing JTBD provides, or when discovery is producing outputs that do not connect to product strategy.

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Structure customer research around what people want to accomplish, the difficulties they face, and the benefits they seek. Explore practical tasks, social perceptions, and emotions to clarify unmet needs and guide product positioning or priorities.

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• Uncovering needs behind feature requests
• Organizing findings from customer interviews
• Revisiting product positioning around customer goals

JTBD (Jobs to Be Done) v3.0 完整工具集。融合四大学派--Klement 进步力量、 Ulwick ODI 机会算法、Wunker Jobs Atlas 七维度、Kalbach Job Stories 整合-- 提供 13 项可执行能力和 15 篇方法论知识库。附带完整 Python API(JTBDSkill 统一入口), 覆盖访谈→问卷→评分→优先级→竞争→营销→增长→描述→Job Map→Outcome→Stories→障碍→Atlas 全流程,以及 CEO 决策视角的市场规模估算、优先级评分与商业化可行性分析。

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Review product roadmaps through six questions about customer needs, retention, priorities, and tradeoffs. Produce a recommendation on what to ship, refine, or stop, with measurable criteria for reassessing the decision after 90 days.

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• Reviewing a quarterly product roadmap
• Deciding whether to build or discontinue a feature
• Assessing product demand through retention

Explain why a specific customer group should choose a product using six parts: audience, problem, current situation, solution, improved outcome, and alternatives. Turn the analysis into a concise value proposition and a statement for marketing use.

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• Writing a value proposition for a specific customer group
• Clarifying changes before and after product use
• Explaining why customers should choose over alternatives

Summarize customer interview transcripts into a consistent Markdown document. Capture what customers want to accomplish, their current solutions, satisfaction and problems, notable findings, and follow-up actions with dates and owners when available.

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• Summarizing customer interview transcripts
• Organizing satisfaction and problems with current solutions
• Sharing findings from product discovery interviews

Analyze user feedback and usage data to identify at least three customer groups based on behavior, goals, and unmet needs. Build profiles covering pain points, product fit, and priorities for serving each group.

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• Finding customer groups within diverse user feedback
• Comparing needs across user groups
• Prioritizing product improvements by customer group

Break a feature into job stories that describe the user's situation, motivation, and desired outcome. Add six to eight observable acceptance criteria per story, defining how success will be checked, and include links to designs or prototypes.

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• Breaking a new feature into job stories
• Writing backlog items around user situations
• Defining acceptance criteria for desired outcomes

Identify three to five distinct customer groups for a product. Describe their characteristics, goals, problems, and existing alternatives, then assess product fit, market potential, and competition to help compare target audiences and explore opportunities.

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• Exploring potential customer groups for a product
• Comparing audiences to prioritize
• Assessing opportunities in a new market

Turn survey responses, interviews, and other research data into three distinct user personas. Each profile explains the outcome users seek, their main difficulties, desired benefits, an unexpected behavioral insight, and how well the product meets their needs.

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• Creating three personas from survey responses
• Grouping interview findings by user goals and behavior
• Comparing user needs to guide product decisions

Use customer research, surveys, and usage data to define an ideal customer profile: the customers most likely to gain value, stay, and expand. Summarize their characteristics, buying behavior, goals, needs, and fit criteria to guide sales and marketing priorities.

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• Defining ideal customers from surveys and interviews
• Finding patterns among customers who stay and expand
• Aligning sales and marketing priorities

Create a customer interview guide focused on past behavior, current problems, and desired outcomes. Adapt questions to research goals and available time, with follow-up prompts and a note-taking template to capture findings consistently.

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• Preparing a first customer interview
• Exploring current workflows and frustrations
• Adapting interview questions to a time limit

Jobs-to-Be-Done analysis — given a product, user descriptions, transcripts, or tickets, produce a JTBD job map with switching forces analysis and opportunity ranking. Use when asked to "find the JTBD", "what jobs are users hiring us for", "job mapping", "what are users really trying to do", "JTBD framework", or "why are users switching".

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Turn interviews, surveys, support conversations, and public reviews into evidence-based customer insights. Identify recurring problems, buying triggers, and customer language, then build research reports, quote collections, or personas and plan interviews or surveys to fill gaps.

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• Analyze customer interview transcripts
• Find recurring themes in reviews and support tickets
• Build customer personas from research evidence

Turn product or feature ideas into a concise product requirements document that helps teams decide what to build first. Connect target customers, customer value, success measures, and release scope, or review an existing document for gaps.

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• Drafting requirements for a new product or feature
• Agreeing on the scope of a first release
• Reviewing an existing product requirements document

Analyze reviews, surveys, and other user feedback by user group. Summarize satisfaction scores, recurring complaints, positive themes, and the goals users want to achieve, then recommend product improvements based on frequency, severity, and business impact.

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• Finding recurring themes across large volumes of user feedback
• Comparing satisfaction across user groups
• Prioritizing product improvements from customer complaints

Research audiences: personas, JTBD maps, RFM segments. One persona doc → audience-profile. "run a JTBD analysis"

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

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JTBD discovery techniques adapted for AI product owner context. Four Forces extraction, job dimension probing, question banks, and anti-patterns for interactive feature discovery conversations.

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Structured persona creation and JTBD analysis methodology - persona templates, ODI job step tables, pain point mapping, success metric quantification, and multi-persona segmentation

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JTBD opportunity scoring and prioritization - outcome statement format, opportunity algorithm, scoring interpretation, feature prioritization, and opportunity matrix template

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Translating JTBD analysis to BDD scenarios - job story to Given-When-Then patterns, forces-based test discovery, job-map-based test discovery, and property-shaped criteria

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JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes

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Core JTBD theory and job story format - job dimensions, job story template, job stories vs user stories, 8-step universal job map, outcome statements, and forces of progress

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