「customer」の検索結果

Use this skill when answering business analytics, RevOps, GTM metric, pipeline, revenue, funnel, customer, or warehouse questions with Deepline. Triggers on phrases like 'query Snowflake', 'analyze pipeline', 'total ACV', 'break down by quarter', 'use the semantic layer', 'run a semantic query', or any use of snowflake_get_semantic_layer / snowflake_run_semantic_query. Skip prospecting, enrichment, contact finding, outbound, or personalization workflows; use deepline-gtm for those.

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。

DRAFT. Build anonymizable host-prep one-pagers for must-meet guests at an in-person event: rank, enrich, light research, warm-intro angles, PDF pack. Not installed by deepline skills. No real customer data in repo samples.

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。

Core marketing concepts, psychology, and frameworks for effective marketing. Use for foundational knowledge on funnels, customer journey, positioning, value propositions, and marketing psychology.

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 sales-call transcripts to extract why deals are won and lost across six dimensions — product, messaging, GTM/sales, pricing, competition, and customer context. Produces aggregated patterns with verbatim buyer quotes, frequencies, and recommendations. Writes to marketing/win-loss/win-loss.md as the evidence base under positioning, messaging, and ICP. Triggers - "win loss analysis", "why are we losing deals", "why do we win", "analyze sales calls", "churn analysis", "deal review"

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 MotherDuck analytics into customer-facing applications with tenant isolation, backend routing, and serving APIs.

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。

Generate customer-focused marketing content from recent git changes, commits, merged pull requests, and shipped features. Use when the user invokes /diff-marketing or /marketing, or asks for blog posts, tweets, changelogs, or emails about what shipped.

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 high-converting copy for landing pages, headlines, cold emails, X/LinkedIn posts, video intros, or SEO titles — and already knows their audience. Also use when the user mentions "blitz copy", "dopamine copywriting", hooks, or asks to rewrite flat copy that explains instead of sells. For audience research first, use the understand-customers skill.

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。

Investigate an alert, page, or production symptom in an incident channel or a team's oncall / monitoring channel, and report findings a human can verify. Ordinary conversation and chatter are not alerts; leave those alone. Use when an alert or page lands, when error rate, latency or saturation is up, when someone asks "why is X broken", "investigate", "what changed", "root cause this", pastes a monitor, dashboard, trace or error-tracker link, or reports production trouble; also by default when an alert lands in a covered channel unasked. Feed-level asks land here too ("which alerts matter", "triage today's alerts"), plus the scheduled alert-review routine and the ticket path ("customer X can't check out"). Runs a fast first pass posted as a short interim update with a TL;DR, every finding carrying the query or link to verify it, then proposes the fix and — with connector access and confirmation — carries it out, never unattended. Afterwards `incident-postmortem` writes it up.

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。

Use when preparing for a sales meeting, discovery call, demo, or customer check-in. Triggers: 'prep me for a meeting with [company]', 'meeting brief for [company]', 'pre-call prep', 'I have a call with [contact] at [company]', 'meeting prep', 'call prep'.

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。

设计用户从认知到留存的完整旅程时使用。适用于新产品/新功能的全流程设计、识别痛点和机会、给 UI/UX 提供设计输入。优先使用 NNGroup 的用户旅程地图方法。

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。

Use Retentioneering's Python toolkit, MCP server, and agent skills to run reproducible customer-journey and event-log analytics that agents can validate and cross-check.

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。

Expert support operations guidance for customer service excellence. Use when designing ticket management systems, creating SLA policies, building support tier structures (L1/L2/L3), optimizing knowledge bases, defining severity levels and escalation procedures, implementing support metrics (CSAT, FRT, TTR, FCR), configuring support tool stacks, or building support-to-CS feedback loops. Covers Zendesk, Intercom, Freshdesk, and help desk best practices.

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。

Expert Quarterly Business Review facilitation for maximizing customer value and strategic alignment. Use when designing QBR programs, preparing executive presentations, demonstrating ROI and value realization, conducting strategic account planning, aligning product roadmaps, identifying risks and opportunities, facilitating business reviews, or automating QBR processes. Use for EBR preparation, success metrics presentation, renewal preparation, and stakeholder engagement.

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。

Expert product discovery guidance for user research and problem validation. Use when conducting user interviews, validating problems, applying jobs-to-be-done framework, sizing opportunities, customer segmentation, competitive analysis, prototype testing, usability testing, designing surveys, or synthesizing research insights. Covers discovery sprints, continuous discovery, and research operations.

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。

Test a product concept with Amazon's Working Backwards method: write the press release for the finished product first, then answer hard customer and stakeholder questions, ending in a complete PRFAQ document. Use when the user requests to 'create a PRFAQ', 'work backwards', or 'run the PRFAQ challenge'

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。

Use when Codex must make a high-quality judgment on any complex problem, not only technical problems. Trigger when a question has high complexity, uncertainty, cost of being wrong, long-term impact, value tradeoffs, possible structural causes, or when the user asks for 全面思考, 深度理解, 系统性分析, 帮我想清楚, 从根上看, 这件事到底怎么看, 方法论, 复杂问题拆解, 系统方案, 架构判断, 策略判断, or 根因分析. Also trigger for project and engineering high-risk scenarios such as multi-module, multi-environment, multi-data-source, multi-state, financial truth, live trading, ledger, revenue, customer assets, order governance, broker interfaces, online availability, major solution selection, and system closure.

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。

Structures growth-focused DD with revenue quality, customer concentration, technology scalability, and organizational readiness. Use when conducting growth DD, validating revenue sustainability, or assessing scale capability.

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。

Structures CDD with market sizing, customer concentration, competitive dynamics, and growth sustainability analysis. Use when conducting commercial DD, validating market assumptions, or assessing revenue durability.

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。

Use when a B2B SaaS founder needs to choose, prioritize, or rebalance customer acquisition channels — deciding outbound vs inbound, paid vs PLG, where to put marketing budget, or sanity-checking CAC, LTV:CAC, and payback. Also for channel-specific playbooks (cold email, LinkedIn, paid social, community, partnerships) and channel-mix audits. Not for closing tactics (use sales-skill) or copy (use copywriter-skill).

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。

Establish Service Level Objectives (SLO), Service Level Indicators (SLI), and Service Level Agreements (SLA) with error budget tracking, burn rate alerts, and automated reporting using Prometheus and tools like Sloth or Pyrra. Use when defining reliability targets for customer-facing services, balancing feature velocity against system reliability through error budgets, migrating from arbitrary uptime goals to data-driven metrics, or implementing Site Reliability Engineering practices.

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。

Create or audit a complete, concise, UI-ready website page content framework from verified business facts before visual design. Use to define page goals, customer decision flow, section order, realistic draft copy, content and evidence needs, CTAs, or page-family rules; do not use for visual design, HTML, SEO implementation, or platform code.

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。

当用户需要深入理解目标客户的心理动机来撰写有共鸣的文案时调用。 适用于：写文案前分析客户心理、客户画像不够深入、文案太平面缺乏情感共鸣、 做用户调研准备。核心信号：用户在问"客户到底在想什么""怎么打动他们"。 不适用于：纯功能型产品文案（技术规格就够了）、不需要情感共鸣的B2B技术文档。

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。

当用户需要将产品/服务/个人的特点转化为对受众有吸引力的利益点时调用。 适用于：写产品文案不知从何下笔、准备销售话术、撰写简历或自我介绍、 做产品定位思考。核心信号：用户在列举产品特点但不清楚"别人为什么要在乎"。 不适用于：纯技术文档、产品规格说明（此时特色本身就是目的）。

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 AI customer feedback analysis systems. TRIGGERS - Use when user needs help with ai-feedback-analyzer related tasks.

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。