「drop-off」の検索結果

ユーザーストーリーを可視化する専門スキル。6つの専門エージェントチームで、 ジャーニーマップの分析から Pencil (.pen) ビジュアル出力まで一気通貫で実行する。 プロダクト情報とターゲットユーザーを入力し、認知→検討→初回利用→習慣化→推薦の 5フェーズで行動・思考・感情・接点・機能・課題・機会・Devアクションを構造化し、 Markdownドキュメントと Pencil ビジュアルジャーニーマップを出力する。 離脱トリガー分析を強化し、ペインポイントと機会を視覚的に強調する。 ペルソナファイルがあれば自動読み込み、なければ手動入力でも動作する。 Use when: ジャーニーマップを可視化したい、ユーザー体験を図で表現したい、 カスタマージャーニーをビジュアル化したい、離脱要因を分析したい、 UXフローを .pen ファイルで出力したい。 Triggers: "ジャーニー", "journey", "ジャーニーマップ", "journey map", "ユーザー体験", "user journey", "UXフロー", "体験設計", "カスタマージャーニー", "customer journey", "可視化", "visualize", "user story", "ユーザーストーリー", "離脱分析", "drop-off"

Analyze conversion funnel drop-offs and identify biggest leak points with impact-ranked recommendations

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。

Maps out how users move through your funnel from first ad click to conversion. Identifies where the biggest drop-offs happen, which campaigns contribute most at each stage, and how long the typical conversion path takes across different audience segments. Platform: Google and Meta.

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。

Guided journey from a leaking conversion flow - landing page, signup, checkout, or in-app onboarding - to a measured, tested funnel. Orchestrates six skills phase by phase - lean-analytics, cro-methodology, storybrand-messaging, hundred-million-offers, influence-psychology, design-everyday-things - each phase carries its full method inline so it runs standalone, asking the user questions at every decision point and recording results in the project docs/ folder (FUNNEL.md, METRICS.md, EXPERIMENTS.md, CONVERSION-OPTIMIZATION-PLAN.md) so the journey resumes across sessions. Use when the user wants to raise conversion on a specific flow, fix checkout or signup abandonment, diagnose onboarding drop-off, or says 'people start but never finish'. With no site yet, use create-website; for a whole-site look, message, and speed audit, improve-website; if the flow converts but needs traffic, grow-website; for in-product engagement and retention, improve-app. For one framework in isolation, invoke that skill directly.

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 improve their app's onboarding experience, increase activation rate, reduce Day 1 drop-off, or optimize the first-run flow. Use when the user mentions "onboarding", "first-run", "activation", "tutorial", "day 1 retention", "new user flow", "permission prompts", "sign-up conversion", "onboarding funnel", or "users dropping off early". For overall retention strategy, see retention-optimization. For paywall placement, see monetization-strategy.

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。

Audit a landing page or funnel step and produce a prioritised CRO test plan. Use when asked to improve conversion rate, audit a landing/signup/checkout page, reduce funnel drop-off, or plan A/B tests for a page. Produces a CRO plan — a heuristic conversion audit, the diagnosed friction, prioritised test hypotheses (ICE), test designs with sample-size math, and the measurement guardrails.

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。

Designing first-run product onboarding wizards that get users to the ah-ha moment without overwhelming them. Step architecture, progressive disclosure, escape hatches, completion incentives, drop-off measurement. Honest about tutorial-overload (dump everything upfront), skip-friendly-empty (skipped onboarding leads to abandoned product), and earned-progressive-disclosure (right things at the right moments) patterns. Triggers on onboarding wizard, product onboarding, first-run experience, signup flow, activation flow, FRX, time-to-value, ah-ha moment design. Also triggers when activation rates are low, when users skip onboarding and never return, when onboarding flows are being scoped for the first time, or when audience research shows users not finding key features.

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。

Find funnel drop-offs from stage numbers you give or connected data, benchmarked, ranked by revenue. "where are we losing people"

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。

Conversion funnel analysis with drop-off investigation. Use when analyzing multi-step processes, identifying conversion bottlenecks, comparing segments through a funnel, or optimizing user journeys.

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。

检查并修复短视频逐字稿的段落衔接、信息密度、口播节奏和观众流失风险。用户问稿子顺不顺、哪里容易被划走，或需要制作可直接拍摄的版本和标记式改稿时使用。 English: Check and improve short-video scripts for transitions, information density, spoken rhythm, and audience drop-off risk. Use when the user wants to know where viewers may leave, whether the script flows, or needs a shoot-ready or annotated revision.

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。

Map customer journeys from awareness to advocacy. Visualize touchpoints, identify drop-off points, analyze channel interactions, and optimize the end-to-end experience. Use when the user asks about customer journey, funnel mapping, touchpoint analysis, or experience optimization.

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。

Optimize customer onboarding — map the activation sequence, identify drop-off points, design the aha moment, and produce the onboarding email sequence. Use when asked to "fix onboarding", "improve activation", "time-to-value is too slow", or "customers aren't getting started".

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。

Optimizes multi-step conversion flows including signup, onboarding, upgrade, and checkout. Maps each step, identifies friction and drop-off risks, then recommends specific copy/UX changes with A/B test plans. Use when someone says 'signup flow', 'onboarding optimization', 'checkout conversion', 'paywall optimization', 'activation rate', 'funnel analysis', 'why are users dropping off', 'registration flow', 'trial conversion', 'free to paid', 'upgrade flow', 'user journey', or wants to improve any multi-step user journey. If they mention steps, screens, or a sequence that leads to signup, payment, or activation, this is the skill. Even casual mentions like 'users aren't finishing signup' or 'our onboarding sucks' should trigger this. Use this instead of page-cro when the problem spans multiple screens rather than a single page.

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 e-commerce performance using GA4 metrics, conversion funnel analysis, and key e-commerce KPIs. Use this skill when the user needs to evaluate online store performance, diagnose conversion drop-offs, set up e-commerce tracking, or create performance dashboards — even if they say 'why are sales down', 'optimize our online store', 'set up GA4 for e-commerce', or 'what metrics should we track'.".

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。

"Map and analyze the customer journey across Awareness, Consideration, Decision, Usage, and Advocacy stages. Use this skill when the user needs to understand the customer experience end-to-end, identify drop-off points, optimize touchpoints, or improve conversion — even if they say 'where are we losing customers', 'what's our funnel look like', or 'map the user experience'.".

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。

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.

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。

Audit a user flow for friction and drop-off points. Use when the user says "UX audit", "audit this flow", "where are users dropping off", "why isn't this converting", "review the onboarding", "usability audit", "what's causing friction", "user journey review", or wants to identify why users struggle with a flow - even if they don't explicitly say "UX audit".

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。

Map every touchpoint from first click to loyal advocate. Identify drop-off points, emotional peaks, and automation opportunities across your entire 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。

Use when designing customer onboarding — time-to-first-value, milestone design, friction audit, drop-off diagnosis. Triggers on 'fix onboarding', 'why do new accounts churn fast'.

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。

Evaluate UI/flows from cognitive load, error prevention, and accessibility perspectives. Apply when reviewing UX, discussing user confusion, high drop-off, or form usability 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。

When the user wants to improve their app's onboarding experience, increase activation rate, reduce Day 1 drop-off, or optimize the first-run flow. Use when the user mentions "onboarding", "first-run", "activation", "tutorial", "day 1 retention", "new user flow", "permission prompts", "sign-up conversion", "onboarding funnel", or "users dropping off early". For overall retention strategy, see retention-optimization. For paywall placement, see monetization-strategy.

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。

Busabase App-in-Skill dashboard over a fixed, deterministic mock user-behavior funnel dataset (browse → search → compare → booking attempt/abandon → complete) for a generic consumer booking product. Use when the user invokes $kelly-behavior-predict or /kelly-behavior-predict, wants to review funnel drop-off, per-segment predicted next actions, or backtest a rule-based "predicted next action" heuristic against a mock historical sample. Fully deterministic mock data and a hand-recomputable rule — never a real ML/LLM model, never a live system.

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。

Analyzes a multi-step conversion funnel to find where visitors drop off and which steps have the worst leakage. Use this skill when someone describes a journey and asks about conversion rates, drop-off, fallout, or step completion. Trigger for "analyze our checkout funnel," "where are visitors dropping off," "what's our add-to-cart to purchase conversion rate," "funnel analysis," "show me fallout between steps," or "which step loses the most visitors."

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。

Analyzes a multi-step conversion funnel to find where users drop off and which steps have the worst leakage. Use this skill when someone describes a journey or funnel and asks about conversion rates, drop-off, fallout, or step completion. Trigger for phrases like "analyze our onboarding funnel," "where are users dropping off," "what's our checkout conversion rate," "funnel analysis," "show me fallout between these steps," or "which step loses the most users."

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。