特定の機能の主要業績評価指標を特定する
Prompt detail
機能の成功を評価するために最も関連性の高い主要業績評価指標（KPI）を特定してください。
ユーザー指標、製品指標、ビジネス指標ごとにグループ化されたKPIのリストを作成し、簡潔なベンチマーク数値とそれぞれの重要な理由を説明してください。
##提供情報：
機能名：{{Feature_name}}
機能の説明：{{@Description}}
##考慮事項：
● ユーザーが機能をどのように利用しているか（エンゲージメント、採用、維持）。
● ユーザーエクスペリエンスと満足度への影響。
● この機能がサポートするビジネス目標または製品目標。
● 成功または失敗を示す測定可能なシグナル。
What the prompt does
Choosing the right KPIs for a new feature launch is critical, yet product managers often default to vanity metrics or miss important signals. This prompt takes a feature name and description and produces a structured, benchmark-backed list of KPIs organized into user metrics, product metrics, and business metrics.
remio enriches this process by referencing your existing product documents, past launch retrospectives, and team discussions in Slack and meetings. Instead of starting from scratch, you get KPIs grounded in your actual product context — complete with benchmark targets and explanations of why each metric matters.
When to use
• You're writing a PRD and need to define measurable success criteria before engineering kicks off development.
• A feature just shipped and stakeholders are asking how you'll evaluate whether it's working — you need a defensible metrics framework fast.
• You're preparing for a quarterly business review and want to ensure your feature KPIs align with broader company OKRs.
• Your team is debating which metrics matter most for a feature, and you need a structured starting point to align everyone.
• You're conducting a post-launch review and need to retroactively define what success looks like across user, product, and business dimensions.
Prompt examples
Input:
Feature name: Smart Reply Suggestions
Feature description: An AI-powered feature in our messaging app that suggests three contextual reply options based on the incoming message content, conversation history, and user tone preferences. Aimed at reducing response time for busy professionals.
remio responds:
Here are the recommended KPIs for Smart Reply Suggestions, grouped by category:
User Metrics: Adoption rate (target: 30%+ of active users within 60 days), suggestion acceptance rate (benchmark: 15-25% of displayed suggestions clicked), and daily active usage frequency. These measure whether users find the feature intuitive and valuable enough to integrate into their workflow.
Product Metrics: Average response time reduction (target: 40% decrease), suggestion relevance score based on user feedback signals, and feature-related error or dismiss rate (target: below 20%). These track whether the AI is performing accurately.
Business Metrics: User retention lift among Smart Reply adopters vs. non-adopters, impact on messages sent per session (engagement proxy), and contribution to premium tier conversion if gated. These connect the feature to revenue and growth goals.
Tip 1: Include specific product goals or OKRs in the feature description — remio will tailor KPI recommendations to align with those targets rather than producing generic metrics.
Tip 2: Mention the target user segment (e.g., "enterprise users" or "free-tier mobile users") so the suggested benchmarks reflect realistic adoption and engagement expectations for that audience.
Tip 3: After generating KPIs, ask remio to search your past launch retrospectives for historical benchmark data to validate or adjust the suggested targets.
More tips
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