Identify key performance indicators for a specific feature
Prompt detail
Identify the most relevant key performance indicators (KPIs) for evaluating the success of the feature.
Provide a structured list of KPIs, grouped by user metrics, product metrics, and business metrics, with a brief benchmark number and explanation of why each is important.
##Given info:
Feature name: {{Feature_name}}.
Feature description: {{@Description}}.
##Consider:
● How users interact with the feature (engagement, adoption, retention).
● The impact on user experience and satisfaction.
● Business or product goals this feature supports.
● Measurable signals of success or failure.
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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