If you're running an e-commerce store today, you've likely noticed that the game is changing. AI is quickly reshaping the way we think about building and designing user interfaces. So how does that breakdown into Ecommerce?
From Merchandising to Experience Curation
Think about how you currently manage your store. You or your team probably spend hours selecting products, managing inventory, and writing product descriptions. This is particularly cumbersome as it is as a small business owner, let alone in a big team with more skus/volume.
But in the AI era, a lot of this stuff can be automated - freeing up your time. But my prediction is above that, your job requirement is changing by the day.
What's Changing:
Traditional Role (Yesterday):
- Spending hours organising products into categories
- Writing individual product descriptions
- Manually creating collections for product categories / seasons and/or themes
- Setting fixed prices and running standard promotions with discount coupons / 20% off price promos
- Managing inventory based on general sales patterns - i.e. buying what you think will sell and needing to buy enough stock to cover 2-4 weeks sales
New Role (Today & Tomorrow):
- Creating shopping experiences that feel personal - so no longer building manual collections but instead letting AI build deeply personal collections on the fly
- Developing product stories that resonate with different customer needs - one description does not fit all. I may need to know something more specific about a laptop from a coding point of view, whereas my team would want to know from a graphics or editing point of view. Let’s get the relevant information out for the user, asap.
- Designing discovery paths that feel natural and intuitive - a chat interface
Real-World Example: Take a clothing store owner who traditionally spent time creating static collections like "Summer Wear" or "Winter Collection." Now, they're creating experience flows like:
- "First Job Interview Look" that adapts based on industry, climate, and budget
- "Weekend Getaway Wardrobe" that changes based on destination and trip style
- "Special Occasion Outfit" that considers event type, venue, and personal style
Implementation Guide: Making It Real
Month 1: Building Your Foundation
Start small but strategic:
- Pick one customer journey to enhance (like "gift shopping")
- Document 10 common customer scenarios
- Create detailed attributes for your top 20 products
- Begin collecting customer stories and feedback
Month 2-3: Creating Your Framework
Focus on structure:
- Build your first AI conversation templates
- Set up tracking for one new success metric
- Create a basic product context library
- Test different personalisation approaches
Month 4-6: Scaling Up
Expand thoughtfully:
- Roll out AI interactions for key customer journeys
- Implement comprehensive success metrics
- Refine and expand your prompt library
- Monitor and adjust brand voice consistency
Common Challenges
1. Overwhelming Data
Challenge: Where do you even start with all this data?
Solution: Begin with your best-selling products and most common customer scenarios. Expand from there.
2. Maintaining Personal Touch
Challenge: How do you keep it feeling human?
Solution: Use AI for scale, but inject your expertise and brand personality into the frameworks you create.
3. Resource Constraints
Challenge: Limited time and budget for this transformation
Solution: Start with one customer journey or product category. Prove the concept, then expand.
Your Next Steps
- Choose one customer journey to transform
- Document 5-10 common customer scenarios
- Create rich descriptions for your top products
- Set up one new success metric
- Start collecting customer context data
Or, outsource it to me and I’ll work with you directly to build this into your business!