pm-competitive-analysis
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ChineseCompetitive Analysis Skill
竞争分析 Skill
How this skill behaves (read first)
此 Skill 的行为方式（请先阅读）
This is a generative skill, and "do a competitive analysis" is where an AI assistant produces the most confident, least useful output: a flat feature-comparison table of the few obvious direct competitors, with invented specifics, no market context, no gaps identified, and no "so what." Two failure modes compound it — fabricated competitor facts (made-up features, pricing, or market share that read as authoritative) and no strategic conclusion (a report that lists but never decides). A real competitive analysis is scoped to a decision, grounded in honest public evidence, structured by the right framework, and ends in implications and a positioning choice. So this skill gates:
- Establish the research objective and the industry context — what decision this informs, and the market it sits in, so competitor moves are read in context rather than in a vacuum.
- Apply the always-true core — find all three competitor types, profile from real public sources, use the right framework, prioritize, and translate into strategic implications and a position.
- Surface the context-dependent decisions (which framework, primary vs. secondary research, competitor depth, positioning stance, expansion, AI's role) with trade-offs.
Then it hands off to (are the competitor facts, market-size estimates, and "gap exists" claims evidenced or assumed/hallucinated?) and (when it ranks opportunities or competitor tiers).
pm-assumption-rigor-auditpm-prioritization-rigor-auditScope: this skill owns the competitive/market analysis and the positioning conclusion that follows from it. It defers full product strategy to , pricing strategy to , go-to-market / market-entry timing to , the broader research process and ethics to , and problem framing to .
pm-vision-strategyux-pricingpm-gtm-planpm-discoverypm-problem-statement这是一个生成型 Skill，而“做竞争分析”恰恰是 AI 助手最容易产出看似最笃定、实则最无用结果的地方：一张只列出少数显而易见的直接竞争者的扁平功能对比表，其中充斥着臆造的具体信息，既缺乏市场背景，也没有识别出市场空白，更没有回答“所以呢”。两种失败模式会相互叠加——捏造竞争对手事实（编造功能、定价或市场份额，却写得像权威结论）和缺少战略结论（报告只做罗列，从不做决策）。真正有效的竞争分析应当围绕具体决策划定范围，以真实公开的证据为依据，由合适的框架加以组织，并以战略启示和定位选择收尾。因此，本 Skill 对以下环节进行把关：
- 确立研究目标和行业背景——明确分析要支持什么决策，以及产品所处的市场，从而结合背景解读竞争者的行动，而不是在真空中分析。
- 应用始终成立的核心原则——找出全部三类竞争者，依据真实公开来源对其进行分析，使用合适的框架，确定优先级，并将结论转化为战略启示和定位。
- 呈现依赖情境的决策（采用何种框架、一手研究还是二手研究、竞争者分析深度、定位立场、扩张方式、AI 的作用），同时说明各自的取舍。
随后，本 Skill 会将工作移交给 （竞争者事实、市场规模估算和“存在市场空白”等主张是否已有证据支持，还是仅凭假设或幻觉？），以及 （当需要对机会或竞争者层级排序时）。
pm-assumption-rigor-auditpm-prioritization-rigor-audit范围：本 Skill 负责竞争/市场分析，以及由分析推导出的定位结论。完整的产品战略交由 处理，定价策略交由 处理，go-to-market / 市场进入时机交由 处理，更宽泛的研究流程与伦理交由 处理，问题界定交由 处理。
pm-vision-strategyux-pricingpm-gtm-planpm-discoverypm-problem-statementStep 0 — Establish context before analyzing
第 0 步——分析前先确立背景
Ask if not known; state the assumption if proceeding without an answer:
- What decision does this inform? Set specific research objectives tied to a decision ("which competitor features drive acquisition?") rather than "understand competitors." The objective scopes the work and prevents an endless, unfocused scan.
- What's the industry context? Sketch the overview first — market size and growth (TAM/SAM/SOM), key trends and drivers, regulatory/economic environment, and structural shifts (new entrants, substitutes). A rival losing share in a shrinking segment faces different pressures than one in a growing market; context changes the meaning of every move.
- Who are the real competitors? Not just the obvious direct rivals — also indirect (same need, different approach) and potential/aspirational ones. Surface them by asking customers what they considered, following where capital flows, monitoring industry news, and searching like a customer would.
- What's the stage and resource budget? This sets how much primary vs. secondary research, and how deep the analysis goes.
如果信息尚不明确，应主动询问；如果未获回答便继续分析，则需明确说明假设：
- 这项分析要支持什么决策？ 将研究目标与具体决策绑定（例如：“哪些竞争者功能能够推动获客？”），而不是泛泛地说“了解竞争者”。研究目标可以限定工作范围，避免无休止且缺乏重点的扫描。
- 行业背景是什么？ 先勾勒整体情况——市场规模与增长（TAM/SAM/SOM）、关键趋势与驱动因素、监管/经济环境，以及结构性变化（新进入者、替代品）。一个在萎缩细分市场中失去份额的竞争者，与一个在增长市场中竞争的竞争者面临的压力完全不同；背景会改变每项行动的含义。
- 真正的竞争者是谁？ 不应只关注显而易见的直接竞争者，还要包括间接竞争者（满足同一需求，但采用不同方案）和潜在/对标型竞争者（可能进入市场，或树立了值得借鉴的标杆）。可以通过询问客户还考虑过哪些方案、追踪资本流向、监测行业新闻，以及像客户一样进行搜索来识别他们。
- 当前阶段和资源预算是多少？ 这决定一手研究与二手研究的比例，以及分析的深度。
The always-apply core (true for any competitive analysis)
始终应用的核心原则（适用于所有竞争分析）
- Frame the industry before benchmarking rivals. Lead with market size, trends, regulatory forces, and structural changes so individual competitor insights are interpreted in context, not as isolated comparisons.
- Cover all three competitor types. Direct (similar product, same customers), indirect (same need, different solution — Uber vs. public transport), and potential/aspirational (could enter, or set a benchmark worth learning from). Listing only direct rivals is the most common blind spot.
- Profile systematically, and mine real customer reviews. For each competitor capture features, pricing, UX, and how they position themselves (speed? quality? community?). Reviews are the richest signal: analyze patterns — a complaint echoed across dozens of reviews is a structural weakness; recurring praise is a strength you'll have to match or beat.
- Use the right framework for the question — not all of them. Perceptual/landscape map (2×2 on dimensions customers care about) to find white space; feature/competitive matrix to compare capabilities and separate table-stakes (everyone must have) from differentiators (what actually drives choice); SWOT to assess your position (the value is in the intersections — a strength that meets an opportunity — not the four lists); Porter's 5 Forces for industry profitability; TAM/SAM/SOM for whether the market is worth pursuing.
- Prioritize competitors into tiers. Primary (closest match, directly affects you), secondary (partial overlap), tertiary (could become relevant). Spend strategic energy on the primary tier rather than spreading thin across everyone.
- Gather intelligence honestly, from public sources. Public reviews, case studies, marketing materials, free-tier features, conferences, and honest conversations are legitimate. Fake accounts, misrepresenting identity, and ToS-violating scrapers are not. And — critically for an AI — do not invent competitor facts: every feature, price, and share figure must trace to a real source, or be flagged as unverified. The purpose is to understand and differentiate, not to copy or find ways to mislead.
- End with strategic implications and a position — the "so what." Translate findings at three levels: feature (where to match the standard, where to differentiate), positioning (which narratives are overcrowded, where you can own a distinct claim), and strategic (which moves need an immediate response vs. which are long-term trends to prepare for). Then land a clear position: pick one of cheapest / highest-quality / most-specialized (claiming two creates mixed signals that erode trust), tie it to a specific persona-problem-promise, and — for early stage — win a focused niche before expanding, one dimension at a time.
- 先构建行业框架，再对竞争者进行基准比较。 首先说明市场规模、趋势、监管力量和结构性变化，确保对单个竞争者的洞察是在具体背景下解读，而不是孤立的比较。
- 覆盖全部三类竞争者。 直接竞争者（相似产品、相同客户）、间接竞争者（满足同一需求但采用不同方案——例如 Uber 与公共交通），以及潜在/对标型竞争者（可能进入市场，或树立了值得学习的标杆）。只列出直接竞争者是最常见的分析盲点。
- 系统地分析竞争者，并深入挖掘真实用户评价。 对每个竞争者记录其功能、定价、UX，以及自身定位（速度？质量？社区？）。评价是最丰富的信号：应分析其中的模式——某项抱怨在数十条评价中反复出现，意味着结构性弱点；反复出现的赞扬则代表你必须追赶或超越的优势。
- 根据问题选择合适框架——并非所有框架都要使用。 使用感知/竞争格局图（perceptual/landscape map，基于客户关注维度绘制 2×2 图）寻找市场空白；使用功能/竞争矩阵比较能力，并区分入场基础项（table-stakes，每个人都必须具备）与差异化因素（真正驱动选择的因素）；使用 SWOT 评估自身位置（价值在于各项要素的交叉——让优势遇上机会——而不是简单罗列四张清单）；使用 Porter 五力判断行业盈利能力；使用 TAM/SAM/SOM判断市场是否值得进入。
- 将竞争者划分为不同层级。 主要竞争者（最相似、直接影响自身）、次要竞争者（仅部分重合）和第三层级竞争者（未来可能变得相关）。应将战略精力集中在主要层级，而不是对所有竞争者平均用力。
- 从公开来源诚实、审慎地收集情报。 公开评价、案例研究、营销材料、免费套餐功能、行业会议和坦诚交流都属于合法来源。虚假账号、冒充身份以及违反 ToS 的抓取器则不属于合法来源。对 AI 而言尤其关键的一点是：不得捏造竞争者事实——每项功能、价格和市场份额数据都必须能够追溯到真实来源，否则应明确标记为未经核实。分析的目的是理解并形成差异化，而不是复制或寻找误导他人的方法。
- 以战略启示和定位——“所以呢”——收尾。 从三个层面转化发现：功能层面（哪些基础标准需要追赶，哪些地方应形成差异化）、定位层面（哪些叙事已经过度拥挤，哪里可以占据独特主张），以及战略层面（哪些行动需要立即回应，哪些属于需要提前准备长期趋势）。随后给出清晰定位：在最便宜 / 最高质量 / 最专业化中选择一个（同时宣称两者会形成混乱信号并削弱信任），将其与具体的“用户画像—问题—承诺”（persona-problem-promise）绑定；对于早期阶段，应先赢得一个聚焦的细分市场，再逐个维度扩展。
The context-dependent decisions (surface, don't auto-apply)
依赖情境的决策（需要呈现，而非自动套用）
Present each with its trade-off and a recommendation tied to Step 0; let the user choose. Running every framework, or analyzing every competitor equally, is the failure mode.
| Decision | Apply when | Avoid / adapt when | Default recommendation |
|---|---|---|---|
| Which framework | Perceptual map to find white space; feature matrix to compare capabilities; SWOT for your position vs. a key rival; Porter's for industry attractiveness; TAM/SAM/SOM for market worth | Running all of them as ritual ("framework theater") that buries the insight | Pick 1–2 that answer the objective; always include the table-stakes vs. differentiator cut |
| Primary vs. secondary research | Secondary (reports, reviews, public data) first for breadth and speed; primary (interviews, surveys, focus groups) to fill specific gaps | Spending on primary research for questions public data already answers | Secondary to frame the landscape, targeted primary to validate the gaps that matter |
| Competitor depth | Tier them — deep on primary, lighter on secondary, monitor tertiary | Analyzing dozens equally (thin everywhere) or fixating on one rival | Depth proportional to tier; revisit tiers as the market shifts |
| Positioning stance | Cheapest, highest-quality, or most-specialized — the one your cost structure and strengths can actually sustain | Claiming two at once (premium + cheap, broad + specialized) — customers disbelieve at least one | Specialized/focused for early stage; one defensible stance, consistent across touchpoints |
| Expansion direction (if scope includes growth) | One dimension at a time — geography, customer size, or product line — matched to current strengths | Expanding multiple dimensions at once, or before winning the initial niche | Win the niche first; expand the single dimension your proven strengths support |
| AI's role | AI to draft landscapes, matrices, SWOTs, and positioning from data you provide or will verify | Trusting AI-generated competitor "facts" (hallucinated features, pricing, share) | Use AI to structure and accelerate; verify every competitor claim against a public source |
应结合第 0 步说明每项决策的取舍并给出建议，让用户自行选择。把所有框架都运行一遍，或对所有竞争者进行同等深度的分析，正是典型的失败模式。
| 决策 | 何时采用 | 应避免或调整的情形 | 默认建议 |
|---|---|---|---|
| 采用何种框架 | 感知图用于寻找市场空白；功能矩阵用于比较能力；SWOT 用于分析自身相对关键竞争者的位置；Porter 五力用于评估行业吸引力；TAM/SAM/SOM 用于判断市场是否值得进入 | 将所有框架仪式化地运行一遍（“框架表演”），导致真正洞察被掩盖 | 选择 1–2 个能够回答研究目标的框架；始终纳入“入场基础项与差异化因素”的切分 |
| 一手研究与二手研究 | 先用二手研究（报告、评价、公开数据）快速建立全貌；再通过一手研究（访谈、问卷、焦点小组）填补具体空白 | 对公开数据已经能够回答的问题投入一手研究 | 使用二手研究构建格局，再通过有针对性的一手研究验证关键空白 |
| 竞争者分析深度 | 对竞争者分层——深入分析主要竞争者，较浅分析次要竞争者，持续监测第三层级竞争者 | 对数十个竞争者进行同等分析，导致每个方向都不够深入；或只盯着一个竞争者 | 分析深度与层级相匹配；随着市场变化重新评估层级 |
| 定位立场 | 在最便宜、最高质量或最专业化中选择一个，且必须是成本结构和自身优势能够长期支撑的立场 | 同时宣称两个立场（高端又便宜、广泛又专业），客户至少会怀疑其中一个 | 早期阶段采用专业化/聚焦定位；确立一个可辩护的立场，并在所有触点保持一致 |
| 扩张方向（若范围包含增长） | 每次只沿一个维度扩张——地域、客户规模或产品线——并与当前优势相匹配 | 同时沿多个维度扩张，或在赢得初始细分市场之前就开始扩张 | 先赢得细分市场，再沿已被证明的优势所支持的单一维度扩张 |
| AI 的作用 | 使用 AI 根据用户提供或将要核实的数据起草竞争格局、矩阵、SWOT 和定位方案 | 直接相信 AI 生成的竞争者“事实”（幻觉功能、定价、市场份额） | 使用 AI 组织结构并提升速度；每项竞争者主张都应对照公开来源进行核实 |
Validate the result (orchestration)
验证结果（编排）
Hand-offs name each lens by its installable skill. Invoke one only if that skill is installed; if it isn't, this skill's own core already carries these rules — proceed without it rather than blocking.name
After producing or revising, hand it to the audit lenses rather than declaring it done. These are candidate lenses — posture per , or route the whole artifact through . Here is the always-relevant lens (auto-runs); the others are offered, tied to what the artifact actually contains. If the user invoked this skill for one specific thing, respect that scope.
docs/orchestration-policy.mdpm-product-reviewassumption-rigor- (auto-runs) — the grounding check, and the antidote to AI's biggest risk here: are the competitor facts, the market-size figures, and the "this gap exists / is worth $X" claims backed by real public evidence, or are they assumed, anecdotal, or fabricated? Flag every load-bearing claim that hasn't been verified.
pm-assumption-rigor-audit - (offer — if it ranks tiers or sets opportunity priorities) — when the analysis ranks competitor tiers or scores market opportunities: is the ranking evidence-based and tied to the decision, or false-precision scoring and a HiPPO pick?
pm-prioritization-rigor-audit
Composition (per §9): the analysis feeds downstream rather than auditing it. The problem () is an upstream input; the full strategy () and pricing () are downstream (offer to produce next, don't auto-generate). If the audits show the analysis rests on unverified competitor claims or a comparison with no conclusion, resolve toward the purpose: a competitive analysis exists to make a sharper strategic choice — if it doesn't change a decision and isn't grounded in real evidence, it's a table, not an analysis.
docs/orchestration-policy.mdpm-problem-statementpm-vision-strategyux-pricing移交给各审查视角时，使用其可安装 Skill 的标识。仅在相应 Skill 已安装时调用；若未安装，本 Skill 自身的核心规则已经涵盖这些要求——应直接继续，不要因此阻塞。name
产出或修订内容后，应将其移交给相应审查视角，而不是直接宣告完成。以下是候选审查视角——根据 调整处理方式，或将整个产物交由 审查。其中， 是始终适用的视角（自动运行）；其他视角则根据产物实际包含的内容按需提供。如果用户仅调用本 Skill 处理某一项具体事务，应尊重该范围。
docs/orchestration-policy.mdpm-product-reviewassumption-rigor- (自动运行)——负责依据核查，也是应对 AI 最大风险的关键：竞争者事实、市场规模数据，以及“存在这一空白 / 值得投入 $X”等主张，究竟有真实公开证据支持，还是仅凭假设、个案或捏造？应标记每一项尚未核实的关键主张。
pm-assumption-rigor-audit - (可选——当分析会对竞争者分层或设定机会优先级时)——当分析对竞争者层级进行排序或为市场机会评分时：排序是否有证据支持并与决策相关，还是使用虚假的精确评分并凭 HiPPO 拍板？
pm-prioritization-rigor-audit
编排关系（依据 §9）： 分析结果应向下游输出，而不是反过来对自身进行审计。问题（）是上游输入；完整战略（）和定价（）是下游内容（可以建议接下来产出，但不要自动生成）。如果审查表明分析依赖未经核实的竞争者主张，或者只有比较却没有结论，应围绕目的进行修正：竞争分析的存在意义，是让战略选择更加清晰——如果它不能改变任何决策，也没有真实证据支撑，那它只是一张表，而不是分析。
docs/orchestration-policy.mdpm-problem-statementpm-vision-strategyux-pricingCommon do/don't patterns
常见应做/不应做模式
| ❌ Don't | ✅ Do |
|---|---|
| List only the obvious direct competitors | Cover direct + indirect + potential/aspirational |
| Invent competitor features, pricing, or market share | Ground every claim in a public source; flag the unverified |
| Benchmark rivals with no market context | Frame industry size, trends, and structural shifts first |
| Dump a flat feature checklist | Separate table-stakes from differentiators; map the white space |
| Treat the SWOT as four lists | Mine the intersections — strengths that meet opportunities, threats that hit weaknesses |
| Analyze every competitor equally | Tier them; spend depth on the primary tier |
| Use fake accounts / ToS-violating scrapers | Public reviews, case studies, free tiers, honest conversations |
| Claim "cheapest and best" | Pick one stance — cheapest, quality, or specialized — and keep it consistent |
| Stop at a report | End with feature/positioning/strategic implications and a clear position |
| Trust an AI-generated landscape as fact | Use AI to structure; verify each fact yourself |
| Ship the analysis unchecked | Hand off to assumption-rigor (+ prioritization-rigor) |
| ❌ 不应做 | ✅ 应做 |
|---|---|
| 只列出显而易见的直接竞争者 | 覆盖直接、间接和潜在/对标型竞争者 |
| 捏造竞争者功能、定价或市场份额 | 将每项主张建立在公开来源之上；标记未经核实的信息 |
| 在缺乏市场背景的情况下对竞争者进行基准比较 | 先构建市场规模、趋势和结构性变化的行业框架 |
| 堆砌一份扁平的功能清单 | 区分入场基础项与差异化因素；绘制市场空白 |
| 将 SWOT 视为四张清单 | 挖掘要素交叉点——让优势遇上机会，让威胁击中弱点 |
| 对每个竞争者进行同等分析 | 对竞争者分层，将分析深度投入主要层级 |
| 使用虚假账号或违反 ToS 的抓取器 | 使用公开评价、案例研究、免费套餐和坦诚交流 |
| 宣称“最便宜又最好” | 选择一个立场——最便宜、质量或专业化——并保持一致 |
| 只交付一份报告 | 以功能、定位和战略启示收尾，并给出清晰立场 |
| 将 AI 生成的竞争格局直接视为事实 | 使用 AI 组织结构；自行核实每项事实 |
| 未经审查就交付分析 | 移交给 |