Results for “jtbd”

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.

The English summary is being prepared. Showing the original description.

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。

The English summary is being prepared. Showing the original description.

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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.

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

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".

The English summary is being prepared. Showing the original description.

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.

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

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.

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

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.

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

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

The English summary is being prepared. Showing the original description.

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

The English summary is being prepared. Showing the original description.

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

The English summary is being prepared. Showing the original description.

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

The English summary is being prepared. Showing the original description.

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

The English summary is being prepared. Showing the original description.

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.

The English summary is being prepared. Showing the original description.

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

The English summary is being prepared. Showing the original description.

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

The English summary is being prepared. Showing the original description.

产品设计 / UX 设计 (产品设计 / UX 设计 (Product Design / UX Design) — 数字产品的用户体验设计：从用户研究 → 信息架构 → 交互设计 → 视觉/UI → 可用性测试 → 设计系统的认知操作系统，面向 UX designer / product designer / interaction designer / UX researcher / design systems engineer / design lead，以及想入行、转岗、服务这行(设计外包、设计工具厂商、研究平台)的视角。覆盖: (a) 第一性张力 — **用户中心/研究驱动 (user-centered, 'you are not the user', research before pixels, observe behavior not opinions) ⇄ 商业目标/约束/交付 (business goals, north-star metrics, ship it, designer 服务于产品成功不是个人作品集)**; **设计直觉/品味/craft (taste, aesthetics, 'attractive things work better' — Norman 情感化设计) ⇄ 数据/实验/A-B 测试 (data-driven, metrics, experimentation, 'opinions are not data')**; **用户说的 (stated preference, 访谈里说喜欢) ⇄ 用户做的 (revealed behavior, 行为观察 > 自陈, usability test 看人真实卡在哪)**; **一致性/设计系统/规范 (consistency, design system, Jakob's law 用户带着别处的习惯来, 复用组件) ⇄ 创新/打破模式 (innovation, 该不该破规范)**; **减法/简化 (simplicity, Krug 'Don't Make Me Think', less but better — Dieter Rams) ⇄ 功能丰富/利益相关者塞需求 (feature creep, stakeholder pressure)**; **UX(体验/流程/研究) ⇄ UI(视觉/像素/组件)** 的职责之争, **designer 该不该写代码 (design engineer / 'should designers code')**; (b) 核心工作流 / pipeline (最标准、最易蒸高质量+CLI 化) — Double Diamond (发现 discover → 定义 define → 开发 develop → 交付 deliver) / Design Thinking (共情 empathize → 定义 → 构思 ideate → 原型 prototype → 测试 test) / Design Sprint (Jake Knapp 5 天冲刺); 完整链: 用户研究 (访谈/问卷/可用性测试/卡片分类) → persona / journey map / JTBD → 信息架构 IA + 用户流 user flow → 线框 wireframe (低保真) → 交互/原型 prototype (高保真) → 视觉 UI / 设计系统落地 → 可用性测试 usability testing → handoff 给开发 → 度量迭代 (北极星 / HEART 框架); (c) 工具栈 — 设计/原型 (Figma 绝对主导 / Sketch 衰退 / Adobe XD 已停更 / Framer 高保真+建站 / Penpot 开源 / Principle / ProtoPie 微交互); 协作白板 (FigJam / Miro / Mural); 用户研究 (Maze / UserTesting / Lookback / Dovetail 研究库 / Optimal Workshop 卡片分类树测试 / Hotjar / Microsoft Clarity 热图); 设计系统/交付 (Storybook / 蓝湖(中) / Zeplin / design tokens / Tokens Studio); 度量 (Amplitude / Mixpanel / 北极星指标); AI 新兴 (Figma AI / v0 by Vercel / Galileo AI / Uizard / Cursor 给 design engineer); (d) 知识正典 — Don Norman《The Design of Everyday Things》(affordance/signifier/mapping 圣经)、Steve Krug《Don't Make Me Think》(可用性入门)、Alan Cooper《About Face》《The Inmates Are Running the Asylum》(交互设计/persona 起源)、Jakob Nielsen 10 Usability Heuristics + NN/g 文章库、Jake Knapp《Sprint》、Jeff Gothelf《Lean UX》、Teresa Torres《Continuous Discovery Habits》、Erika Hall《Just Enough Research》、Julie Zhuo《The Making of a Manager》、《Refactoring UI》(Adam Wathan/Steve Schoger)、《Universal Principles of Design》、Laws of UX (Jon Yablonski)、《100 Things Every Designer Needs to Know About People》(Susan Weinschenk)、IDEO/Stanford d.school 设计思维材料; (e) figures/流派 — 认知心理/人因派 (Don Norman 认知科学奠基、Susan Weinschenk 行为心理、Kathryn Whitenton); 可用性工程派 (Jakob Nielsen 启发式/折扣可用性、Steve Krug、Jared Spool UIE); 交互设计/目标导向派 (Alan Cooper goal-directed/persona、Kim Goodwin); 设计思维派 (IDEO Tim Brown、David Kelley d.school); 精益/持续探索派 (Jeff Gothelf Lean UX、Teresa Torres continuous discovery、Marty Cagan《Inspired》产品发现); 设计系统/系统化派 (Brad Frost Atomic Design、Nathan Curtis design tokens、Alla Kholmatova); 视觉/UI craft 派 (Adam Wathan & Steve Schoger Refactoring UI、Dieter Rams 'less but better' 工业设计遗产); 设计领导/职业派 (Julie Zhuo、Aarron Walter 情感化设计、John Maeda); 移动优先 (Luke Wroblewski 'Mobile First'); (f) 行业话术/黑话 — affordance 可供性 / signifier 意符 / mental model 心智模型 / IA 信息架构 / heuristic evaluation 启发式评估 / usability 可用性 / a11y accessibility 无障碍 / WCAG / persona 用户画像 / journey map 用户旅程 / JTBD jobs-to-be-done / north-star metric 北极星 / HEART 框架 / wireframe 线框 / mockup / prototype 原型 / fidelity 保真度 (lo-fi/hi-fi) / design system 设计系统 / design token 设计令牌 / atomic design 原子设计 / component library 组件库 / handoff 交付 / red routes 关键路径 / dark pattern 暗黑模式 / Fitts's law / Hick's law / Jakob's law / Miller 7±2 / progressive disclosure 渐进披露 / above the fold / hamburger menu / skeuomorphism vs flat / micro-interaction / empty state / edge case / happy path / design debt 设计债 / dogfooding / dot voting / affinity mapping 亲和图 / card sorting 卡片分类 / tree testing / A/B test / NPS / SUS (System Usability Scale); (

The English summary is being prepared. Showing the original description.