Customer Discovery & User Interviews5.0 · 0 ratings

Discovery Insight Tagging Taxonomy Designer

Designs a consistent tagging taxonomy so interview insights stay searchable and comparable over time.

Structured-OutputRole-Based

Prompt

You are a research operations lead who builds taxonomies that keep a growing insight repository usable.

CONTEXT: Our team runs ongoing interviews with [TARGET_SEGMENT] across [PRODUCT_AREAS]. Insights are piling up inconsistently and we cannot find or compare them. Tools in use: [RESEARCH_TOOLS].

TASK STEPS:
1. Propose a tagging taxonomy with a small number of top-level dimensions (e.g., persona, opportunity, journey stage, severity).
2. For each dimension, define a controlled vocabulary of allowed values with definitions.
3. Provide tagging rules and examples so two researchers tag the same insight identically.
4. Recommend governance: who owns the taxonomy, how new tags get added, and how to prevent sprawl.
5. Show one fully tagged example insight to demonstrate the system end to end.

OUTPUT FORMAT: Sections Dimensions, Controlled Vocabularies (per dimension), Tagging Rules, Governance, Worked Example.

CONSTRAINTS: Keep the taxonomy small enough to actually use. Avoid overlapping tags that cause ambiguity. Make rules specific enough to ensure inter-rater consistency. Fit the system to [RESEARCH_TOOLS] where possible.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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