ipIterPrompt

Research Readout — Mobile App

Present research to stakeholders who weren't in the room. Purpose-built for mobile app contexts.

iterpromptUpdated 2026-06-26627 copies

A structured designer prompt for user research synthesis: present research to stakeholders who weren't in the room, tailored to a native mobile app with small screens, gestures, and platform conventions. It walks the model through a proven process with an explicit quality bar, and delivers a readout structure.

The prompt

Variables to fill in: {{research_data}}{{research_questions}}{{decisions_pending}}

You are a design researcher who turns messy human data into decisions teams trust. I need your help in the context of a native mobile app with small screens, gestures, and platform conventions.

TASK: Present research to stakeholders who weren't in the room.

DELIVERABLE: Produce a readout structure: the questions and method in 60 seconds, findings as narratives with participant voices, the so-what per finding, and the disagreement-handling plan for contested findings.

PROCESS:
1. Review the inputs below. If anything critical is missing or ambiguous, ask me up to three clarifying questions before producing the deliverable.
2. Separate observations from interpretations from the start; keep participants' words attached to every theme.
3. Look actively for disconfirming evidence — synthesis that only confirms the roadmap is broken.
4. End at decisions: every theme connects to something the team should do, test, or stop.
5. Produce the deliverable in a clean, skimmable format I can use directly.

QUALITY BAR:
- Themes are supported by multiple participants and quoted evidence.
- Sample limits are stated plainly — no 'users want' from five interviews without caveats.
- Findings distinguish what people did from what they said.

INPUTS:
- The raw material: interview notes, transcripts, test recordings summaries, survey results: {{research_data}}
- What the research was trying to learn: {{research_questions}}
- The product/design decisions this should inform: {{decisions_pending}}

Run this prompt on a real model without leaving the page. Every run is saved to your history for this prompt.

Fill in the variables

How to use

  1. 1Fill in the {{research_data}}, {{research_questions}}, {{decisions_pending}} variables with your real details — specifics in, specifics out.
  2. 2Paste the prompt into ChatGPT, Claude, Gemini, or any capable model.
  3. 3Answer the clarifying questions it asks; that step is what makes the output fit your situation.
  4. 4Iterate on the deliverable: ask for alternatives, tighter versions, or a different angle on any section.

Pro tips

  • If the output feels generic, add more concrete detail to the inputs — names, numbers, and constraints sharpen everything.
  • Works well in a thread: keep the conversation going to refine a readout structure.

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