P

Sora Prompt for Analyzing User Feedback

Analyzing user feedback is a crucial step to improve a product, service, or customer experience. Sora, OpenAI's video generation model, offers an innovative approach to transform textual user feedback into impactful visual content. By generating videos that illustrate user journeys, friction points, and moments of satisfaction, Sora allows product and UX teams to communicate their analyses far more effectively than a simple written report. Rather than presenting raw data tables, you can create visual scenarios that concretely show what your users experience, making insights immediately understandable to all stakeholders. This visual approach facilitates decision-making in meetings, team alignment, and prioritization of improvements. Whether you work on a mobile app, an e-commerce site, or a SaaS service, using Sora to stage user feedback transforms abstract data into concrete and memorable visual narratives.

The prompt

Sora

Generate a 30-second video illustrating the following user journey based on real collected feedback: [PASTE FEEDBACK HERE]. The video should show a typical user interacting with the interface, highlighting the 3 main friction points identified in the feedback. Use a clean and professional style with superimposed text annotations summarizing each problem encountered. Alternate between moments of frustration (signaled by a subtle red tint) and moments of satisfaction (green tint). End the video with a summary screen listing the priority improvement areas extracted from the feedback. Visual tone: modern UI/UX design, neutral colors, readable typography. Format: 16:9, suitable for presentation in a product team meeting.

Personalize this prompt with Léa

Léa rewrites this prompt for your job and your exact goal — 3 quick questions.

Why it works

This prompt works because it structures the request in three layers: the context (real feedback), the staging (user journey with emotional color coding), and the final deliverable (actionable summary). The visual color coding exploits Sora's ability to create coherent narrative transitions, while the text annotations anchor the video in concrete data. Specifying the format and tone ensures a result directly usable in a professional context.

Expected result

You will get a 30-second video showing a user navigating an interface, with key moments annotated corresponding to the analyzed feedback. Friction points are visually identified through color changes and annotations, creating a presentation support immediately understandable for non-technical stakeholders.

Variants by level

FAQ

How should I prepare my user feedback before submitting it to Sora?
Before using Sora, structure your feedback by grouping it by theme (navigation, performance, design, features). Identify the most representative verbatims and classify them by frequency of occurrence. Summarize each group in a clear sentence describing the problem or satisfaction. The more organized and synthesized your feedback is upfront, the more relevant and true to the user experience the generated video will be. You can use a tool like ChatGPT to pre-process and categorize your raw feedback before feeding it to Sora.
Can Sora replace traditional qualitative feedback analysis?
No, Sora does not replace qualitative analysis but powerfully complements it. Textual and statistical analysis remains essential to identify trends, measure the frequency of problems, and prioritize actions. Sora comes in downstream as a communication and storytelling tool: it transforms your analysis conclusions into visual aids that make insights accessible to everyone. Use NLP analysis tools for data processing, then Sora for staging the results.
What types of feedback work best with Sora for visualization?
Feedback that describes concrete interactions with an interface works particularly well: purchase journey, registration process, menu navigation, use of a specific feature. Strong emotional feedback (frustration, confusion, satisfaction) also translates very well visually. On the other hand, very abstract or technical feedback (server performance, backend bugs) is more difficult to illustrate and requires more visual translation work in the prompt.

How to use this prompt

  1. Copy the prompt with the button above.
  2. Paste it into ChatGPT, Claude or your favorite AI assistant.
  3. Replace the bracketed variables with your details, then refine the result.

About Prompt Guide

Prompt Guide is a free library of 4800+ ready-to-use prompts for ChatGPT, Claude and other AIs, with guides to learn prompting and tools to build and optimize your own prompts.

More prompts to explore

Go further

Get new prompts every week

Join our newsletter.