theory-analysis-product-positioning

Analyzing product positioning from multi-source evidence requires coding diverse inputs into consistent dimensions. This Skill processes interviews, support tickets, and posts to code cross-source evidence into structured attributes, functions, benefits, and usage context insights.

Theory_annotations export provides structured metadata compatible with downstream STP analysis. When coding cross-source evidence into product positioning insights, this optional export enables traceable integration with review-mining-stp for further downstream analysis.

To code evidence into product positioning dimensions, provide an analysis goal and evidence items with item IDs, content, and content type. The Skill codes these into four structured dimensions: attributes, functions, benefits, and usage context, producing JSON and Markdown outputs.

Cross-source evidence coding supports social media posts and notes alongside interviews and support tickets. You provide item content and content type, and optionally source type and context tags, to generate structured product positioning insights with traceable references.

Generating structured product positioning insights requires an analysis goal and evidence items containing item ID, content, and content type. Optional fields like source type, source reference, and context tags enhance grounding but are not required to produce JSON and Markdown outputs.

Converting diverse customer feedback into a structured STP view involves cross-source evidence coding across four dimensions. This approach builds a consistent product positioning perspective with traceable quotes and optional theory annotations for downstream integration.