「customer」の検索結果

Product-led growth and customer-base growth for B2B SaaS. Use this skill for self-serve funnel work (activation, time-to-value, free trial vs freemium, PQL definition, in-product upgrade moments, sales-assist triggers), for the self-guided interactive product demo that runs in front of the login wall (demo portfolio and flow design, gated vs ungated policy, demo seed data and privacy, keeping a published demo in sync with the shipping product, step-level demo analytics), and for growing revenue from existing customers (adoption, expansion, churn-save, the self-serve cancel flow and failed-payment recovery, renewal marketing, net revenue retention, and champion tracking: watching the people who bought and used you at each customer, confirming a job change from evidence, and running both plays a move fires, the seat they left and the account they joined). Also triggers on: PLG, product-led growth, activation, aha moment, time to value, free trial, freemium, PQL, product qualified lead, onboarding, self-serve, customer marketing, expansion revenue, upsell, cross-sell, churn, retention, NRR, renewal, cancel flow, cancellation flow, save offer, exit survey, pause subscription, dunning, failed payment recovery, involuntary churn, people keep canceling, champion tracking, job change signals, job change alerts, our champion left, our champion changed jobs, customer alumni, former customers who moved to a new company, interactive demo, self-guided demo, product tour, click-through demo, demo automation, demo library, should our demo be gated, ungated demo, demo without a sales call, our demo is out of date, demo shows the old UI, put a demo on our homepage, demo completion rate, demo drop-off, try before you talk to sales.

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Build or refine the Ideal Customer Profile (ICP) and personas using the Jobs-to-be-Done framework (Clayton Christensen / Bob Moesta). Use when the user asks for ICP research, persona development, "who are our customers", buyer personas, audience research, "build our ICP", target customer definition, or wants to update persona docs. JTBD interview questions, three job dimensions (functional/emotional/social), and the Four Forces of Progress are wired into every persona. Writes to knowledge/icp/personas.md so all other skills get smarter. For the individual buyer persona rather than the segment, see customer-persona. For sourcing real customer language, see customer-research.

日本語の概要は準備中です。原文の説明を表示しています。

顧客の契約・請求状況を調べ、重複購入や更新失敗を分類し、返金・解約・請求管理画面の復旧から、顧客への返信案と製品の改善点まで整理するスキル。

• 重複契約や意図しない請求の調査
• 更新失敗や支払い方法の問題への対応
• 請求管理や解約画面を復旧したいとき

Define a brand's target audience with deep personas, psychographics, and ICP (Ideal Customer Profile). Use when the user says "target audience", "ideal customer", "customer persona", "audience persona", "ICP", "who is our customer", "define our audience", "audience research", "buyer persona", "who should we be targeting", "audience profile", "customer profile", "who buys this", or needs to understand their audience more deeply before investing in brand or marketing work.

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Use when the user needs to understand customers deeply enough to write copy and pick targeting — consumer versus shopper, JTBD, layered persona, internal monologue, pain map, objection list, journey map, and a customer language bank pulled from real reviews and DMs. Trigger on 'customer insight', 'buyer persona', 'who is my customer', 'what do they actually want', 'jobs to be done', 'why do they hesitate before buying'. Also use when the user cannot explain who the product is for. Not for — intake questions when an agency signs a new client, see `20-client-intake-brief-global`; paid audience targeting setup, see `51-audience-research-global`; competitor study, see `08-competitor-research-global`.

日本語の概要は準備中です。原文の説明を表示しています。

产品营销 (PMM, Product Marketing) — 拥有「产品如何被定位 / 表达 / 发布 / 卖进市场」的从业者认知操作系统: 是产品 / 销售 / 市场 / 客户之间的连接组织, 负责把产品能力翻译成市场价值, 并把市场声音带回产品。覆盖 (a) 定位与差异化 (April Dunford 「刻意选择语境」框架 + 竞争性替代方案 + 卖价值不卖功能 + 选择「让你优势成立的市场参照系」, 对照 Ries & Trout 经典「定位是占领心智」), (b) 信息传递与叙事 (messaging 层级 / 信息屋 + 价值主张 + 收益导向 vs 战略叙事「换框架」Andy Raskin + 表达清晰度 Emma Stratton / Punchy + 初创 homepage 定位 FletchPMM), (c) 进入市场 (GTM) 策略与产品发布 (发布分级 T1/T2/T3 + 发布流程与跨职能编排 + GTM 打法 PLG vs SLG vs 混合 + 滩头细分选择), (d) 市场与竞争情报 (竞品分析 + battlecard 战卡 + 输赢分析 win/loss + 竞争赋能 Klue/Crayon/Clozd), (e) 买家与客户研究 (ICP 理想客户画像 + 买家 / 用户 persona + Jobs-to-be-Done 任务理论 Christensen/Moesta/Ulwick ODI + 客户之声 VoC + 用真实买家测信息 Wynter/Peep Laja), (f) 销售赋能 (战卡 + pitch / 销售 deck + 一页纸 + demo 叙事 + 异议处理 + 销售培训 + 内容采用率 — 你的产出只值销售实际用到的那部分), (g) 定价与打包 (价值定价 + 打包分层 + 《Monetizing Innovation》Ramanujam/Simon-Kucher + PLG 定价 — 常与产品 / 财务共担), (h) 细分与品类 (市场细分 + TAM/SAM/SOM + 技术采用生命周期与跨越鸿沟 Geoffrey Moore + 品类设计与叙事 Play Bigger / Christopher Lochhead — 稀有且昂贵, 不是默认选项), (i) 需求生成与内容协同 (campaign 信息 + 思想领导力 + 漏斗内容 TOFU/MOFU/BOFU + ABM 基于客户营销), (j) 分析师与影响者关系 (Gartner 魔力象限 + Forrester Wave + 分析师 briefing — To B 场景, 对 pay-to-play 影响诚实标注), (k) 客户营销与倡导 (参考客户 + case study + 评测站 G2/TrustRadius/Capterra 运营 + 社区), (l) PMM 运营与度量 (影响管道 + 赢率 + 发布采用率 + 信息穿透率 + 角色汇报线「向产品还是向市场」之争 + PMM 作为战略职能 vs 接单工具人陷阱); 跨 B2B SaaS (该学科重心) / B2C 消费 / 开发者 PLG / 平台产品。不含 产品管理 (PM 造产品 / 拥有 roadmap, PMM 拥有市场 — 相邻且极易混淆) / 增长 / 效果营销 / 付费投放 (平行学科) / 品牌 / 企业传播 / 公关为终点 / 需求生成为终点 (PMM 与之协同但不等同) / 平面设计 /「做 slide 和周边的团队」(PMM 抗争的接单工具人窄化) / 泛泛「市场营销」。 (Product Marketing (PMM) — the cognitive operating system of practitioners who own how a product is positioned, messaged, launched, and sold into a market: the connective tissue between product, sales, marketing, and customers, responsible for translating product capability into market value and bringing the voice of the market back into product. Covers (a) positioning & differentiation (April Dunford's deliberate-context framing, competitive alternatives, value-not-features, framing the market in which your strengths matter — vs Ries & Trout classic perception-in-the-mind positioning), (b) messaging & narrative (messaging hierarchy / house, value proposition, benefit-led vs strategic-narrative / change-the-frame messaging Andy Raskin, clarity craft Emma Stratton/Punchy, homepage & startup positioning FletchPMM), (c) go-to-market (GTM) strategy & product launches (launch tiers T1/T2/T3, launch process & cross-functional orchestration, GTM motion PLG vs SLG vs hybrid, beachhead segment selection), (d) market & competitive intelligence (competitive analysis, battlecards, win/loss analysis, competitive enablement Klue/Crayon/Clozd), (e) buyer & customer research (ICP ideal customer profile, buyer & user personas, Jobs-to-be-Done Christensen/Moesta/Ulwick ODI, voice of customer, message testing with real buyers Wynter/Peep Laja), (f) sales enablement (battlecards, pitch & sales decks, one-pagers, demo narratives, objection handling, sales training, content adoption — output is only as good as what sales actually uses), (g) pricing & packaging (value-based pricing, packaging & tiering, Monetizing Innovation Ramanujam/Simon-Kucher, PLG pricing — often shared with product/finance), (h) segmentation & category (market segmentation, TAM/SAM/SOM, technology adoption lifecycle & crossing the chasm Geoffrey Moore, category design & narrative Play Bigger / Christopher Lochhead — rare and expensive, not a default), (i) demand-gen & content partnership (campaign messaging, thought leadership, funnel content TOFU/MOFU/BOFU, ABM account-based marketing), (j) analyst & influencer relations (Gartner Magic Quadrant, Forrester Wave, analyst briefings — for B2B, with honest read on pay-to-play perception), (k) customer marketing & advocacy (references, case studies, reviews G2/TrustRadius/Capterra presence, community), (l) PMM operations & metrics (influenced pipeline, win rate, launch adoption, message pull-through, the role's reporting line product-vs-mark

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Comprehensive customer success and retention expertise combining onboarding, health scoring, churn prevention, retention strategies, and LTV maximization. Use when designing customer onboarding flows, reducing churn, building health scores, creating retention systems, designing upsells, or improving customer lifetime value. Covers proactive engagement, cancel flows, dunning, re-engagement, and the full customer lifecycle.

日本語の概要は準備中です。原文の説明を表示しています。

Customer segmentation model builder — tiers customers by ARR, health, and expansion potential; defines CS motion per tier; maps resource allocation. Use when asked to "segment our customers", "define our CS tiers", "how should we allocate CS resources", "build a customer segmentation model", or "who gets high-touch vs. digital".

日本語の概要は準備中です。原文の説明を表示しています。

Build structured ICP documentation by scraping case studies, testimonials, and solutions pages from your website. Produces firmographics, champion + economic buyer personas, pain points, decision criteria, anti-ICP, customer proof points, and voice-of-customer synthesis. Writes to marketing/icp/ICP.md as the canonical ICP every downstream skill reads. Triggers - "icp research", "ideal customer profile", "persona research", "customer segments", "who are our customers", "build ICP"

日本語の概要は準備中です。原文の説明を表示しています。

Customer retention system — churn analysis, retention tactics, loyalty programs, and engagement scoring. Use when "retention", "reduce churn", "keep customers", "loyalty program", "customer retention", "churn prevention", "churn analysis", "engagement scoring", "win-back", "customer lifetime value", or any request to analyze, prevent, or reduce customer churn.

日本語の概要は準備中です。原文の説明を表示しています。

"Perform RFM (Recency, Frequency, Monetary) customer segmentation from transaction data. Use this skill when the user needs to segment customers by purchase behavior, identify high-value buyers, design retention campaigns, or prioritize marketing spend by customer value — even if they say 'who are our best customers', 'which customers are at risk of churning', or 'how do we target our marketing'.".

日本語の概要は準備中です。原文の説明を表示しています。

"Customer relationship management strategy — integrated framework with six pillars: customer segmentation (RFM/CLV), journey orchestration (cross-channel), CDP technology stack, loyalty-program design, B2B key-account management (KAM), and CRM organization/governance. Use for VIP program design, membership-system decision, retail/ecommerce/B2B customer strategy, CDP buy-vs-build, marketing-automation adoption, or key-customer churn. Triggers: 『CRM 系統』『會員經營』『客戶分級』『大客戶策略』『CDP』『行銷自動化』『客戶生命週期』『VIP 方案』『顧客忠誠』『RFM』『CLV』『KAM』『Journey Orchestration』. For 師大 EMBA CRM, 政大 ecommerce, 中山 marketing cases. Complements Asgard `biz-cac-ltv` (tactics) and `biz-customer-journey` (single method) with the strategic integration layer.".

日本語の概要は準備中です。原文の説明を表示しています。

Master orchestrator for B2B SaaS content creation and the editorial production system behind it. Use this skill to produce blog articles, whitepapers, case studies, video scripts, newsletters and ghostwritten thought leadership, to develop content strategy, and to run the publishing line itself — content briefs, editorial calendars and production capacity, review and approval workflow, subject-matter-expert access, the style guide, an AI-drafting policy, and a content inventory with owners. Also triggers on: blog, article, case study, whitepaper, newsletter, video script, ghostwriting, content calendar, editorial, thought leadership, content strategy, content brief, content operations, content ops, editorial workflow, managing editor, who reviews this, our content pipeline is stuck, content is stuck in review, content audit, content inventory, content governance, style guide, house style, SME interview, expert interview, freelance writers, AI content policy, how much content can we actually produce. Also owns the customer academy and customer education: online courses, onboarding curriculum, tutorials, certification programs, digital credentials and badges, exam and pass-mark design, course freshness when the product UI changes, and whether the academy should sit behind a login. Triggers on: customer academy, customer education, online course, course library, learning path, curriculum, tutorial, certification program, certified users, digital badge, Open Badges, recertification, exam, pass mark, LMS, Skilljar, our tutorial shows the old UI, our course is out of date, should the academy be gated, do certified customers renew better.

日本語の概要は準備中です。原文の説明を表示しています。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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Watches what customers are saying in public and in private, then does something about it. Aggregates Google, Yelp, and Facebook reviews alongside disputes, tickets, and email into themes backed by verbatim quotes; drafts a reply to every review in the owner's own voice for approval; spots customers who have gone quiet or look likely to leave; and drafts win-back offers for the ones worth keeping. With Shopify connected, order and fulfillment patterns become a sentiment signal too. Works from pasted or exported reviews when nothing is connected. Use this whenever the owner asks about reviews, ratings, reputation, complaints, or repeat business — including "what are people saying about us," "did we get any bad reviews," "how do I respond to this one-star," "our rating dropped," "which customers have gone quiet," "who hasn't ordered in a while," "how do I win them back," or "are customers happy."

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Health check on a customer account and QBR-ready prep - relationship strength, engagement trend, risk signals, value delivered, and the agenda that makes the review worth their time. Use when the user asks "how healthy is [account]", "customer health check", "prep the [account] QBR", "business review prep", or "are we at risk with [customer]".

日本語の概要は準備中です。原文の説明を表示しています。

Surface what customers are actually saying - direct attributed quotes on a topic across call transcripts and email, across your accounts. Use when the user asks "what are customers saying about [topic]", "pull quotes on [objection/feature/competitor]", "voice of customer on [X]", or "what's coming up in calls".

日本語の概要は準備中です。原文の説明を表示しています。

Chief Customer Officer advisory for startups: retention decomposition (gross retention vs NRR honesty, churn root-cause taxonomy), customer segmentation strategy (differential investment across tiers + ICP fit scoring), CS team coverage model (pooled vs named CSM thresholds + ratio math), and CS team org evolution (CS vs Support vs AM distinctions). Use when designing retention strategy, segmenting customers for differential investment, sizing CS team, or sequencing CS hires. Strategic only — does not duplicate engineering/business-growth tactical skills.

日本語の概要は準備中です。原文の説明を表示しています。

Extract customer reviews from any e-commerce product page or reviews page. Returns reviewer name, star rating, date, review title, review body, verified purchase status, and helpful votes per review. Works on Amazon, WooCommerce, Shopify, and any site with standard review markup. Supports pagination for multi-page review sections. Use when: product reviews, customer feedback, review scraping, get reviews, sentiment analysis data, review extraction, customer ratings, extract customer opinions, product feedback, user reviews, review mining, bulk review collection, review analysis, scrape ratings and comments, ecommerce review data.

日本語の概要は準備中です。原文の説明を表示しています。

[omh] Unsorted customer feedback and bug reports: cluster customer signals and choose the next workflow. Use when the user says: feedback-triage, customer-feedback-triage, feedback triage, customer feedback, feedback cluster, bug or feature, feature request triage, payment failure feedback.

日本語の概要は準備中です。原文の説明を表示しています。

Discover what customers truly need by analyzing the "job" they hire your product to do. Use when the user mentions "customer discovery", "why customers churn", "what job does this solve", "competing against luck", "product-market fit", "switching behavior", "milkshake moment", or "functional vs emotional jobs". Also trigger when investigating why users choose competitors, designing features around real customer needs, or reframing a value proposition. Covers JTBD interviews, competition analysis, and jobs-oriented roadmaps. For product positioning, see obviously-awesome. For rapid validation, see design-sprint. For non-leading interview technique, see mom-test.

日本語の概要は準備中です。原文の説明を表示しています。

Talk to customers without leading them using Mom Test rules: discuss their life not your idea, ask about specifics in the past, and talk less. Use when the user mentions "customer interviews", "validate my idea", "users say they want it but dont buy", "leading questions", "The Mom Test", "customer feedback bias", or "interview script". Also trigger when preparing user-research questions, interpreting ambiguous feedback, or designing customer-discovery that avoids false positives. Covers commitment and advancement, avoiding compliments, and extracting signal from noise. For product-market fit, see jobs-to-be-done. For rapid prototype testing, see design-sprint.

日本語の概要は準備中です。原文の説明を表示しています。

Builds the loop from what customers say to what gets changed — collecting feedback, distinguishing signal from noise, routing it to owners, and closing the loop back to the customer. Use this to set up a feedback program, design or interpret CSAT/NPS, decide what customer feedback deserves action, get product to act on recurring issues, or diagnose why feedback is collected but nothing changes.

日本語の概要は準備中です。原文の説明を表示しています。

Owns the customer's experience after the sale — support, success, escalation, and the feedback loop back into product. Use this for a decision spanning support and product, when service quality and cost are in tension, when deciding what to staff or automate, when a customer relationship is at risk above the account-manager level, or when nobody owns a recurring customer problem.

日本語の概要は準備中です。原文の説明を表示しています。