product-manager-toolkit

To use RICE prioritization, run a Python script that scores potential features based on reach, impact, confidence, and effort. This provides a data-driven output to inform your roadmap and replace subjective prioritization debates.

Analyzing customer discovery interviews is best handled by using a Python script to extract actionable insights, pain points, and jobs-to-be-done. This process transforms raw qualitative interview data into structured product strategy inputs.

You need Python 3 specifically to run the automated RICE scoring and interview analysis scripts. However, the included Markdown templates for product documentation and discovery frameworks can be utilized without any Python environment setup.

To structure a product requirements document (PRD), use pre-defined Markdown templates that ensure clear communication of feature briefs and strategy. These templates standardize documentation format, facilitating efficient alignment across product development teams.

You can automate roadmap planning by first extracting pain points from customer interviews using the analysis script, then feeding your feature ideas into the RICE prioritizer. This workflow supports continuous data-driven product strategy execution.