Fashion Trend Forecasting & Research AI prompts
16 ready-to-use prompts for fashion trend forecasting & research from Fashion AI School's 300-prompt collection. Fill in the bracketed fields, copy, and paste into your AI tool.
12-month trend radar
Act as a fashion trend strategist. Build a research framework for 12-month trend radar focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Weak signals before they become trends
Act as a fashion trend strategist. Build a research framework for weak signals before they become trends focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Trend signals into product opportunities
Act as a fashion trend strategist. Build a research framework for trend signals into product opportunities focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Trend versus hype filter
Act as a fashion trend strategist. Build a research framework for trend versus hype filter focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Seasonal color forecast
Act as a fashion trend strategist. Build a research framework for seasonal color forecast focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Future silhouette forecast
Act as a fashion trend strategist. Build a research framework for future silhouette forecast focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Competitor trend positioning
Act as a fashion trend strategist. Build a research framework for competitor trend positioning focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Trend research interview guide
Act as a fashion trend strategist. Build a research framework for trend research interview guide focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Trend adoption by customer type
Act as a fashion trend strategist. Build a research framework for trend adoption by customer type focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Cultural signals into Fashion hypotheses
Act as a fashion trend strategist. Build a research framework for cultural signals into fashion hypotheses focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Competitor trend matrix
Act as a fashion trend strategist. Build a research framework for competitor trend matrix focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Trend forecasting workshop
Act as a fashion trend strategist. Build a research framework for trend forecasting workshop focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Future-facing signal research plan
Act as a fashion trend strategist. Build a research framework for future-facing signal research plan focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Seasonal trend report
Act as a fashion trend strategist. Build a research framework for seasonal trend report focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Stress-test a trend forecast
Act as a fashion trend strategist. Build a research framework for stress-test a trend forecast focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Create a trend-to-product validation sprint
Act as a fashion trend strategist. Build a research framework for Create a trend-to-product validation sprint focused on [MARKET/CATEGORY] and [SEASON/YEAR]. Separate observed signals from interpretation, identify what evidence should be checked, and finish with product, content and timing implications. Use placeholders such as [BRAND], [PRODUCT], [AUDIENCE], [MARKET] or [DATA] where the user should customize the workflow.
Open prompt →Questions about this collection
- What is in the Fashion Trend Forecasting & Research prompt collection?
- 16 original prompts written by Fashion AI School for fashion trend forecasting & research work. Each prompt is published in full and unchanged from the source document.
- How do I use these prompts?
- Open a prompt, fill in the bracketed fields such as MARKET/CATEGORY, SEASON/YEAR, BRAND, PRODUCT with your own brand, product or audience, then copy the finished text into the AI assistant or image generator you already use.
- Are the prompts free?
- Yes. The full 300-prompt library on AI Creatives is free to read, customise, copy and share. Fashion AI School's live programs, workshops and consulting go deeper into building your own.
- Who wrote them?
- Fashion AI School, an education and consulting practice focused on practical AI for fashion brands, professionals and students. AI Creatives is its free resource platform.