Use Case: Fashion Store — AI Styling Recommendations & Higher AOV

A Shopify-to-WooCommerce fashion boutique increased average order value by 23% in 60 days using AIWU’s AI styling assistant and product recommendation engine. Here’s the full playbook.

Before You Start

This use case combines several AIWU features. Guides you’ll want to read first:

• Auto-Generate Product Descriptions — WooCommerce AI basics
• AI Product Images — visual product content
• WooCommerce Chatbot Recommendations — product search in chat
• Quiz Builder — style quiz for customers

The Challenge

The store had 800+ SKUs across seasonal collections. Customers arrived not knowing what to buy, browsing aimlessly and leaving without purchasing. Cart abandonment was 78%. The team didn’t have resources to hire a personal stylist, but knew that customers who got styling advice converted at 3× the rate of those who didn’t.

The Solution: AI Personal Stylist

Part 1: Chatbot as Personal Stylist

The store configured the chatbot to act as a fashion advisor, not just a product search tool.

System prompt used:

You are [Store Name]'s personal styling assistant. 
Your goal is to help customers find pieces they'll love 
and feel confident wearing.

Start by understanding the customer: ask about the occasion, 
their style preferences, and what they already own if 
they're building an outfit. Then suggest 2-3 specific 
products from our collection.

Always suggest complete outfits, not just single items. 
If someone asks about a dress, also suggest shoes, 
accessories, or a jacket that complements it.

Be enthusiastic but not pushy. Use conversational language. 
You can reference seasonal trends but focus on timeless 
style principles.

WooCommerce settings enabled:

• Product Search in Chat: On
• Show Product Cards: On — displays product image + price inline in chat
• Max Products in Response: 3

Part 2: Training the AI on Fashion Context

Product descriptions alone aren’t enough — the AI needed to understand how items combine and who they’re for.

Training data added:

• Style guide Q&A pairs — 40 entries like “What to wear to a summer wedding?”, “Best casual Friday outfit ideas?”, “How to style wide-leg trousers?”
• Product category pages — trained on all category page content so the AI understands the collection structure
• Look book content — trained on blog posts describing seasonal outfits and how pieces combine
• Size guide — so the AI can answer fit questions

Because AI search is enabled, the chatbot retrieves actual current products from the catalog when making suggestions — it doesn’t hallucinate items that don’t exist.

Part 3: Proactive Styling Suggestions

The biggest conversion driver was outfit recommendations for specific occasions. The store customized the chatbot’s welcome message per page to proactively engage visitors.

How it works: With Content-Aware mode enabled, the chatbot knows which page the visitor is on. The system prompt includes instructions like: “If the user is browsing a product category, proactively suggest a complete outfit using items from that category.”

When a customer lands on “Summer Dresses,” the chatbot opens and says: “Spotted you checking out summer dresses! Here’s a look we’re loving this season — I can suggest pieces that go together if you tell me the occasion.”

Part 4: Styling-Focused Recovery Emails

When a customer abandons their cart, the store uses a workflow to send AI-personalized follow-up emails.

Workflow: Cart Contents → AI Styling Email

1. Trigger: WooCommerce order status — pending payment (no completion after 30 min)
2. Action: Get order items
3. Action: Generate Text — “Write a warm, helpful styling email. The customer was interested in: [items]. Suggest how to style one of the items. End with a single clear call to action. No discount — focus on the styling angle.”
4. Action: Send Email via WordPress SMTP

Results After 60 Days

Key Takeaways for Fashion Retailers

• Complete outfits beat single items. Customers don’t just want a product — they want to know how it fits into their life. Configure your system prompt to always suggest combinations.
• Product cards in chat change everything. Showing product images inline in the conversation reduces the friction of clicking away. Enable “Show Product Cards” in WooCommerce chatbot settings.
• Train on real styling content. Blog posts, lookbooks, and style guides — not just product descriptions — are what make the AI give genuinely useful fashion advice.

What’s Next

• 🏥 See another use case: Dental Clinic: Reduce Phone Calls with AI Chat
• ✍️ Content agency use case: Content Agency: Scale Output with AI Workflows
• 📊 Track performance: Chatbot Analytics

Last verified: AIWU v.4.9.2 · Updated: 2026-02-25