「customer」の検索結果

顧客や取引先への返信案を人の承認に結び付け、承認された本文と送信先、送信結果を記録します。修正前の古い承認による送信や、複数の担当処理による重複送信を防ぐ設計です。

• 顧客への返信を承認制にしたいとき
• 承認本文と送信結果を記録したいとき
• 修正前の承認による送信を防ぎたいとき

顧客や取引先が参加するチャットで、エージェントの応答条件と送信内容を定めるスキル。呼びかけへの応答、内部情報の保護、承認用の下書きへの切り分けを扱います。

• 顧客グループでの応答ルール設定
• 取引先への返信から内部情報を守りたいとき
• 価格や契約の回答を承認用下書きに分ける

OpenDesign renewal + seat-expansion business case for a growing customer: realized value, usage proof, and the expansion ROI. Built as a decision-grade B2B sales deck for champion, finance approver.

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。

A customer-success workshop onboarding users to a project-management app — the first-value path and the habits that retain. Built as a decision-grade professional training deck for new customers, CS team.

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。

Capture surprises, workarounds, and rough edges hit while *consuming* the public surface of Prisma 8, Prisma Compute, or Prisma Postgres — anything a real user of these products would experience. Fires whenever an operator (or agent) writes a workaround, hits a surprising failure mode, or finds undocumented behaviour while using one of these three products from the outside (extension authoring, example apps, integration tests, customer reproductions, internal demos, manual repros). Does NOT fire on bugs in code the operator's own team maintains — those are normal product-backlog bugs. In product-team repos (e.g. `prisma-8-ws`), surfaces the gotcha and offers the operator three paths (capture-as-gotcha, file a normal bug, or note-and-move-on). Outside product-team repos (pet projects, hackathon entries, customer codebases), silent-captures into the project's gotchas log AND a Triage-state Linear ticket in the matching gotchas project — no operator escalation. Do not skip the recording step.

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。

Ask real executives and domain experts a question through Instant Expert for a written answer or short call: practitioner knowledge, customer discovery. Free test mode; live sends need approval.

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。

Four-phase framework for onboarding enterprise customers from contract to value realization. Use when implementing new enterprise customers, preventing churn during onboarding, or solving the adoption cliff that kills deals post-go-live. Includes the Week 4 ghosting pattern.

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。

Analyze unit economics for PE targets — ARR cohorts, LTV/CAC, net retention, payback periods, revenue quality, and margin waterfall. Essential for software/SaaS, recurring revenue, and subscription businesses. Use when evaluating revenue quality, building a cohort analysis, or assessing customer economics. Triggers on "unit economics", "cohort analysis", "ARR analysis", "LTV CAC", "net retention", "revenue quality", or "customer economics".

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。

Prepare for due diligence meetings — management presentations, expert network calls, customer references, and advisor sessions. Generates targeted question lists, benchmarks to reference, and red flags to probe. Use before any diligence meeting or call. Triggers on "prep for management meeting", "diligence call prep", "expert call questions", "customer reference questions", or "meeting prep for [company]".

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。

Multi-agent autonomous startup system for Claude Code. Triggers on "Loki Mode". Orchestrates 100+ specialized agents across engineering, QA, DevOps, security, data/ML, business operations, marketing, HR, and customer success. Takes PRD to fully deployed, revenue-generating product with zero human intervention. Features Task tool for subagent dispatch, parallel code review with 3 specialized reviewers, severity-based issue triage, distributed task queue with dead letter handling, automatic deployment to cloud providers, A/B testing, customer feedback loops, incident response, circuit breakers, and self-healing. Handles rate limits via distributed state checkpoints and auto-resume with exponential backoff. Requires --dangerously-skip-permissions flag.

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。

Manage customer support — track tickets, respond, escalate issues.

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。

Drafts overdue-invoice reminder emails from the ledger (MYOB, NetSuite, QuickBooks, Xero, or Zoho Books) plus PayPal, Stripe, and Airwallex data, matched to each customer's payment history and tone (gentle for good customers, firm for repeat late payers). Sends via PayPal with owner approval; everything else queues as a mail draft, with the Airwallex hosted pay link included where one exists. Use when the user asks "who owes me money," mentions overdue invoices, or wants to follow up on unpaid invoices.

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。

Design, optimize, and communicate SaaS pricing — tier structure, value metrics, pricing pages, and price increase strategy. Use when building a pricing model from scratch, redesigning existing pricing, planning a price increase, or improving a pricing page. Trigger keywords: pricing tiers, pricing page, price increase, packaging, value metric, per seat pricing, usage-based pricing, freemium, good-better-best, pricing strategy, monetization, pricing page conversion, Van Westendorp. NOT for broader product strategy — use product-strategist for that. NOT for customer success or renewals — use customer-success-manager for expansion revenue.

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。

Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences. Use when designing or optimizing a cancel flow, building save offers, setting up dunning emails, or reducing failed-payment churn. Trigger keywords: cancel flow, churn reduction, save offers, dunning, exit survey, payment recovery, win-back, involuntary churn, failed payments, cancel page. NOT for customer health scoring or expansion revenue — use customer-success-manager for that.

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。

Router/index for the 4 business & growth skills bundled in this plugin: customer-success-manager (health scoring, churn risk, expansion), sales-engineer (RFP analysis, competitive matrices, PoC planning), revenue-operations (pipeline, forecast accuracy, GTM efficiency), and contract-and-proposal-writer. Use when a growth/revenue request doesn't obviously match one skill and you need to pick the right one (e.g., 'which accounts are at risk', 'should we bid on this RFP').

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。

Design a detailed value proposition using a 6-part JTBD template — Who, Why, What before, How, What after, Alternatives. Use when creating a value proposition, analyzing customer value delivery, or articulating why customers should choose your product.

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。

Reconstruct a customer relationship from recorded interactions before answering or drafting a response.

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。

Answer a question about money that already moved in Stripe — why a charge failed, what a customer was billed, where an invoice or payout stands — by reading the object chain instead of guessing from a dashboard total. Use when the user pastes a Stripe id, asks why a payment failed, asks what a customer is paying, or wants revenue, invoice, or subscription state.

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。

Mine public reviews, app stores, and forums for unmet needs, competitor weaknesses, and switching triggers — with quoted evidence. Use when you want customer voice without waiting on interviews.

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。

Run a customer journey mapping workshop with adaptive questions and outputs. Use when you need to map stages, actions, emotions, pain points, and opportunities for a persona and scenario.

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 the support FAQ, sales talking points, and objection handling teams need before an EOL announcement. Use when customer-facing teams must be ready before customers hear.

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。

When the user wants to define their ideal customer profile, position an AI product, build messaging architecture, or validate product-market fit. Also use when the user mentions 'ICP,' 'ideal customer profile,' 'positioning,' 'PMF,' 'product-market fit,' 'messaging,' 'buyer persona,' 'enrichment signals,' 'market positioning,' or 'competitive positioning.' This skill covers market positioning, ICP definition, messaging architecture, and PMF validation for AI-native products. Do NOT use for technical implementation, code review, or software architecture.

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。

Trustpilot customer reviews scraper for any company listed on trustpilot.com — given a company domain (e.g. shopify.com, apple.com, shopwagandtail.com) plus optional filters (page number, single star rating 1-5, single language ISO code, verified-only flag, has-company-reply flag, date period last30days/last3months/last6months/last12months, free-text keyword search, and reviewer countryCode client-side filter), extracts paginated reviews with 20+ fields per review: reviewId, reviewUrl, reviewTitle, reviewDescription, reviewRatingScore (1-5), reviewDate (ISO publishedDate), reviewDateOfExperience, reviewLabel, isReviewVerified, reviewer (display name), reviewerId, reviewersCountry (ISO Alpha-2), reviewLanguage, reviewCompanyResponse (the company reply text), plus pagination metadata (currentPage, totalPages, totalCount). Optional flags add reviewer profile metadata (reviewerNumberOfReviews, reviewerProfileIsVerified), reply analysis dates (companyReplyPublishedDate, companyReplyUpdatedDate), extended metadata (reviewSource, reviewVerificationSource, reviewLikes), and review photos. Use when user mentions Trustpilot reviews, scrape Trustpilot, get reviews from Trustpilot, Trustpilot review scraper, Trustpilot customer reviews, extract Trustpilot reviews, Trustpilot review data, download Trustpilot reviews, paginate Trustpilot, paginated Trustpilot reviews, filter Trustpilot reviews by star, filter Trustpilot by language, verified reviews Trustpilot, has reply Trustpilot, company response Trustpilot, Trustpilot reply analysis, brand monitoring Trustpilot, sentiment analysis Trustpilot, competitor reviews Trustpilot, bulk reviews from a Trustpilot page, batch download reviews, trustpilot.com reviews scraping, fake review research Trustpilot, Trustpilot dataset, persona research from Trustpilot reviews, Trustpilot keyword search reviews, Trustpilot date range reviews, review export Trustpilot. Also applies to comparing review trends across competitors, training data for LLM sentiment classifiers, monitoring competitor response time, exporting reviews for BI dashboards, lead generation from active reviewers, ML / fake-review detection, and aggregator sites that display third-party reviews.

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。

Walmart product reviews scraper: given a walmart.com product item ID, navigate to the reviews page and extract paginated customer reviews including reviewId, rating, title, review text, author nickname, submission date, verified purchase status, helpful votes, variant selected (color/size), badges, fulfilled by, seller name, and photo count. Use when user mentions walmart reviews, walmart product reviews, walmart customer reviews, scrape walmart reviews, extract walmart reviews, walmart review scraper, walmart ratings and reviews, walmart review data, walmart review text, walmart review pagination, get reviews from walmart, walmart review collector, walmart verified purchase reviews, walmart review analysis, walmart sentiment analysis, walmart review export, walmart buyer feedback. Also applies to bulk collection of walmart product reviews across multiple items, sentiment analysis on walmart reviews for market research, competitor product review benchmarking on walmart, and monitoring new walmart reviews over time.

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。