product-manager-toolkit

The RICE framework objectively ranks product features by scoring reach, impact, confidence, and effort. This toolkit provides a prioritizer script that calculates these scores to generate a data-driven feature ranking.

Yes, you can analyze customer interview transcripts using NLP-based analysis. The toolkit processes text to automatically extract key pain points, feature requests, and jobs-to-be-done for product strategy validation.

The best way to structure a PRD is by using standardized PRD templates. This toolkit provides various templates to ensure your requirement documentation is clear, structured, and comprehensively captures necessary features.

Yes, the toolkit requires Python dependencies including pandas and nltk. These libraries enable the NLP-based analysis of customer interviews and support data-driven decision-making workflows.

You can calculate feature prioritization for a specific team capacity by running the RICE prioritizer script with your features file. Input your feature list and specify your team capacity, such as 15 person-months, to get a tailored ranking.