Back to templates

Feature Prioritization Scorer

Feature prioritization workflow built with Langflow that scores ideas using RICE or Kano and outputs a ranked list with clear rationale.

Share

If the flow preview doesn't load, you can open it in a new tab.

This Langflow flow helps product teams make prioritization decisions that are consistent, explainable, and tied to strategy. It takes raw feature ideas and customer feedback (tickets, call notes, reviews, requests), extracts key signals, and applies a structured scoring framework such as RICE or Kano to produce a ranked list of opportunities. Instead of debating opinions, teams get a transparent scoring table with rationale, assumptions, and clear next steps for validation.

How it works

This Langflow flow implements a structured feature prioritization pipeline using common product frameworks.

It starts by ingesting candidate feature ideas along with supporting context such as customer feedback snippets, segments, business goals, and constraints. Normalization components standardize the inputs (consistent fields, deduplication, and clarity improvements) so each idea can be scored fairly.

A signal-extraction stage identifies prioritization factors from the evidence: estimated reach, potential impact, confidence level, effort/cost, and qualitative indicators such as customer sentiment or urgency. These signals can be derived from structured inputs or inferred from text evidence when explicit numbers are missing.

The scoring stage applies a selected framework. For RICE, the flow computes a composite score from Reach, Impact, Confidence, and Effort. For Kano, it classifies features into categories (Must-have, Performance, Delighter) and can incorporate weighting rules to reflect strategy.

A rationale layer produces a concise explanation of why each feature received its score, referencing the underlying evidence and highlighting assumptions. Finally, structured output components generate a ranked prioritization table that can be exported to planning docs, roadmaps, or tickets for follow-up discovery and delivery.

Example use cases

  • Product teams can triage a backlog of feature requests by scoring them with RICE, focusing discovery and engineering on the highest expected ROI.

  • PMs can connect qualitative feedback to a Kano classification to balance must-have improvements with delighters that differentiate the product.

  • Startups can prioritize a fast-moving roadmap by combining customer interviews and support tickets into a consistent scoring model.

  • Enterprise teams can align stakeholders by generating an explainable prioritization report that documents trade-offs and assumptions.

  • Growth teams can rank experiments and feature bets by expected reach and impact, generating a clear execution queue.

The flow can be extended to integrate deeply with your tooling and improve scoring quality over time. Connect to Jira/Linear/GitHub Issues to ingest feature requests, and to CRM/analytics tools to pull usage and revenue signals for more accurate reach and impact estimates. Store historical decisions and outcomes in a vector store to calibrate scoring (what actually moved KPIs) and to recommend better confidence levels. Add governance rules (e.g., mandatory metrics, dependency checks, compliance constraints) and review gates so only well-defined ideas advance. Advanced setups can generate a discovery plan per top-ranked feature (hypotheses, questions, experiments) and automatically create tickets or roadmap entries with the computed scores and rationale.

What you'll do

  • 1.

    Run the workflow to process your data

  • 2.

    See how data flows through each node

  • 3.

    Review and validate the results

What you'll learn

How to build AI workflows with Langflow

How to process and analyze data

How to integrate with external services

Why it matters

Feature prioritization workflow built with Langflow that scores ideas using RICE or Kano and outputs a ranked list with clear rationale.

Create your first flow

Join thousands of developers accelerating their AI workflows. Start your first Langflow project now.

gradiant