E-commerce engagement and retention audit — wishlists, account value, email capture, notifications, loyalty, personalization, and AI chat utility. Use when asked to audit engagement, review retention, assess repeat purchase potential, or improve customer loyalty.
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---
name: Audit Engagement Retention
description: >
E-commerce engagement and retention audit — wishlists, account value, email capture,
notifications, loyalty, personalization, and AI chat utility. Use when asked to audit
engagement, review retention, assess repeat purchase potential, or improve customer loyalty.
---
# Audit Engagement Retention
Systematic audit of features that drive repeat visits and purchases.
## Prerequisites
- Read `frontend/src/app/[locale]/(app)/wishlist/` for wishlist functionality
- Read `frontend/src/app/[locale]/(app)/profile/` for user account
- Read `frontend/src/app/[locale]/(app)/orders/` for order history
- Read `frontend/src/components/storefront/` for engagement components
- Check for email/notification related code in `frontend/src/app/api/`
## Workflow
### Phase 1: Account Value Proposition
1. **Registration incentive**:
- Why should a user create an account? Is it communicated?
- Is there a welcome discount for first-time buyers?
- Is registration friction-free? (social login, minimal fields)
2. **Account dashboard**:
- What does the user see after login?
- Order history — complete and useful?
- Saved addresses — for faster checkout?
- Profile customization — avatar, name, preferences?
3. **Wishlist functionality**:
- Can users add products to wishlist?
- Is wishlist accessible from product cards and detail pages?
- Does wishlist persist across sessions?
- Is there "notify on price drop" or "back in stock"?
- Can wishlists be shared? (social, gift registry)
### Phase 2: Communication Channels
4. **Email marketing**:
- Is there newsletter signup? Where? (footer, popup, checkout)
- Is there a welcome email sequence?
- Are there abandoned cart recovery emails?
- Are order status update emails sent?
- Is there a back-in-stock notification system?
- Is Resend configured and working?
5. **Push notifications**:
- Are web push notifications implemented?
- What events trigger notifications?
- Can users manage notification preferences?
6. **Transactional emails**:
- Order confirmation email — exists, well-designed?
- Shipping confirmation — with tracking link?
- Delivery confirmation — with review prompt?
- Return/refund confirmation?
### Phase 3: Personalization
7. **Product recommendations**:
- Is there a recommendation engine?
- "Recently viewed" products?
- "Based on your purchases" suggestions?
- "Customers also bought" on product pages?
- Are recommendations powered by pgvector embeddings?
8. **AI chat utility**:
- Does the AI chat help find products?
- Can it answer product questions? (size, material, shipping)
- Does it recommend products based on preferences?
- Can it assist with order issues?
- Is the chat prominently accessible?
9. **Content personalization**:
- Is the landing page personalized for returning users?
- Are category pages sorted by relevance to user?
- Is there geo-based personalization? (language, currency)
### Phase 4: Loyalty & Repeat Purchase
10. **Loyalty program**:
- Is there a points/rewards system?
- Is there a referral program?
- Is there a VIP tier system?
- Are there birthday/anniversary rewards?
11. **Re-engagement**:
- Are inactive users contacted? (win-back emails)
- Is there seasonal/holiday marketing?
- Are there limited editions or drops? (creates urgency to return)
12. **Community building**:
- Is there social media integration?
- Is there user-generated content? (customer photos)
- Is there a brand community or forum?
## Output Format
Generate `AUDIT_ENGAGEMENT_[DATE].md` at workspace root with:
```markdown
# Engagement & Retention Audit — [DATE]
## Engagement Feature Matrix
| Feature | Exists | Working | Quality (1-5) | Impact |
|---|---|---|---|---|
## Critical Gaps
[Missing features that directly impact repeat purchases]
## Quick Wins
[Easy implementations with high retention impact]
## Recommendations
[Prioritized by customer lifetime value impact]
```