Prompt Sora to Define a Positioning
Sora, OpenAI's video generation model, opens up unprecedented possibilities for defining and testing brand positioning. Rather than staying in the abstract, you can now concretely visualize how your positioning comes to life through video sequences: atmosphere, tone, visual universe, target in context. By generating videos that embody different positioning axes, you get a powerful decision-making tool. You immediately see whether your premium, accessible, disruptive, or institutional positioning works visually. This approach allows validating positioning hypotheses before investing in real production, creating dynamic moodboards to align teams, and testing the emotional resonance of your brand with stakeholders. Whether you are launching a new brand, repositioning an existing product, or exploring a new market segment, Sora transforms a strategic exercise that is often abstract into a tangible and shareable visual experience.
The prompt
Generate a 10-second video illustrating the positioning of a brand in [INDUSTRY] targeting [TARGET AUDIENCE]. The ambiance should reflect a [premium / accessible / disruptive / artisanal] positioning. Show a character matching the target (age, style, environment) interacting with the product/service in a [USAGE SITUATION] context. Lighting is [natural and warm / clean studio / urban contrast], color palette revolves around [BRAND COLORS]. Camera movement is [slow and cinematic / dynamic and immersive / stable and documentary]. The dominant emotion to convey is [trust / desire / belonging / freedom]. No text on screen, the video must communicate positioning solely through imagery.
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Why it works
This prompt works because it structures the request around the four pillars of visual positioning: the embodied target, the usage context, the aesthetic universe, and emotion. By forcing a choice between precise options (type of positioning, lighting, camera movement), it requires crystallizing strategic decisions that are often left vague. The ban on on-screen text ensures that positioning is truly carried by the image, the ultimate test of its coherence.
Expected result
Variants by level
FAQ
How to use Sora to compare multiple positioning axes?
Can Sora replace a traditional positioning study?
How to ensure the generated video accurately reflects the intended positioning?
How to use this prompt
- Copy the prompt with the button above.
- Paste it into ChatGPT, Claude or your favorite AI assistant.
- Replace the bracketed variables with your details, then refine the result.
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