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product-insights

Aggregate customer signals into a ranked backlog with RICE scores.

1|1|Updated Mar 13, 2026
Search Tags:#onboarding#prioritization#sprint-planning#customer-feedback#transcript-analysis#product-insights#rice-scoring
One-click install
npx skills add https://github.com/jp-solumhealth/jpstack --skill product-insights
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: product-insights
Source: https://github.com/jp-solumhealth/jpstack/tree/main/product-insights
Command: npx skills add https://github.com/jp-solumhealth/jpstack --skill product-insights

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Convert scattered customer feedback, support notes, and onboarding pain into a defensible, prioritized engineering backlog so teams stop building from gut and start building from evidence.

Core Features & Use Cases

  • Aggregate multi-source signals: Extract feature requests, bug reports, and UX friction from call transcripts, CRM notes, and onboarding sessions.
  • Evidence-backed prioritization: Calculate RICE scores, apply revenue impact multipliers, and rank items for sprint allocation.
  • Actionable deliverables: Produce a sprint-ready report with verbatim customer quotes, suggested MVP scope, and ticketing prompts for Jira/Linear.
  • Use case: During sprint planning, run a two-week product-insights pass to deliver the top 10 RICE-ranked items with associated customer evidence and suggested scope.

Quick Start

Analyze the last 14 days of customer calls, CRM notes, and onboarding sessions and produce a prioritized Product Insights report with the top 10 RICE-ranked items and verbatim customer quotes.

Frequently Asked Questions about product-insights

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prioritize customer feedback into a sprint backlog using RICE scoring?▼

To prioritize customer feedback into a sprint backlog, aggregate signals from calls and CRM notes, compute RICE scores with revenue multipliers, and generate a ranked report with verbatim quotes and suggested MVP scope.

What is the best way to extract feature requests from onboarding transcripts and CRM notes?▼

Extracting feature requests from onboarding transcripts and CRM notes involves aggregating multi-source signals to capture verbatim quotes, frequency, and UX friction, converting scattered customer feedback into defensible product insights.

Can I use RICE scoring with revenue impact multipliers for early-stage SaaS sprint planning?▼

RICE scoring with revenue impact multipliers works for early-stage SaaS sprint planning by ranking feature requests and bug reports based on computed scores, enabling evidence-backed prioritization for engineering teams.

How do I generate ticketing prompts for Jira or Linear from customer call analysis?▼

Generate ticketing prompts for Jira or Linear from customer call analysis by producing a sprint-ready report that maps extracted verbatim quotes and suggested MVP scope into actionable engineering backlog items.

Does product signal aggregation work for competitive research and bug triage in healthcare product teams?▼

Product signal aggregation supports competitive research and bug triage for healthcare product teams by capturing impact and frequency across multi-source inputs, yielding a traceable sprint recommendations report for roadmap review.

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