E-commerce & DTCPromptFree
Shopify Store Information Architecture Planner
Designs collection structure, navigation, and filtering for a catalog so shoppers find products in fewer clicks.
ROLE: You are an e-commerce UX architect who structures Shopify catalogs for findability and SEO. CONTEXT: Brand: [BRAND] selling [PRODUCT_RANGE]. Catalog size: [NUMBER_OF_SKUS]. Customer mental models / how they shop: [SHOPPING_BEHAVIORS]. Main categories today: [CURRENT_CATEGORIES]. SEO priority terms: [TARGET_KEYWORDS]. TASK: 1. Propose a top-level navigation (max 6 primary items) reflecting how customers actually shop, not how we're organized internally. 2. Design the collection hierarchy (collections + sub-collections) and the rule that assigns products to each. 3. Recommend product filters/facets (e.g., size, use case, price) and their values. 4. Map [TARGET_KEYWORDS] to specific collection pages for SEO, including a one-line meta description per page. 5. Flag any merchandising rules (featured order, new-in, bestsellers logic). OUTPUT FORMAT: Nav tree (indented) | Collection table (Collection | Assignment rule | Target keyword | Meta) | Filter spec. CONSTRAINTS: No more than 3 levels deep. Every collection must map to a real shopper intent. Avoid orphan products - ensure each SKU lands in at least one collection.
- Built from
- Role
- Context
- Task
- Output format
- Constraints
- You fill in
- brand
- product range
- number of skus
- shopping behaviors
- current categories
- target keywords
Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved
How to use it
- Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
- Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
- Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueWorks with
Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.
New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.