Conversational Commerce
Framework
IRON LAW: Conversation First, Commerce Second
Conversational commerce works because it meets customers WHERE THEY
ALREADY ARE (messaging apps). Forcing a sales pitch into a chat channel
kills trust. The conversation must provide genuine value (answering questions,
solving problems) BEFORE introducing products or purchases.
The sequence: Help → Trust → Recommend → ConvertPlatform Comparison (Asia-Pacific Focus)
| Platform | Users (Taiwan) | Commerce Features | Best For |
|---|---|---|---|
| LINE | 21M+ (95% penetration) | LINE Shopping, Rich Menu, LIFF, payment | Taiwan, Japan, Thailand primary channel |
| Instagram DM | ~10M | Shop tags, quick replies, product stickers | Visual products, younger demographic |
| Facebook Messenger | ~18M | Shops integration, automated responses | Broad reach, older demographic |
| Limited in Taiwan | Catalog, cart, payment (select markets) | SEA, India, Brazil | |
| ~1M (Taiwan) | Mini Programs, WeChat Pay | China-connected businesses |
Conversation Flow Design
1. Entry Points — How customers start the conversation
- QR code in store, ad click-to-message, website chat widget, social media link
2. Welcome Flow — First 3 messages
- Greet warmly, set expectations, offer navigation options
- Rich menu (LINE) or quick reply buttons — don't ask open-ended questions early
3. Product Discovery — Help them find what they need
- Guided questions: "What are you looking for?" → category → product
- Product cards with image, price, and "Buy" button
- AI-powered recommendations based on conversation context
4. Purchase Flow — Minimize friction
- In-chat checkout where possible (LINE Pay, in-app payment)
- If redirecting to website, deep-link to the specific product (not homepage)
- Order confirmation message with tracking
5. Post-Purchase — Retain and upsell
- Shipping updates via message
- Follow-up: "How's the product?" (7 days after delivery)
- Personalized recommendations based on purchase history
Chatbot vs Human Handoff
| Scenario | Handle with Bot | Hand off to Human |
|---|---|---|
| FAQ (hours, shipping, returns) | ✓ | — |
| Product recommendations (simple) | ✓ | — |
| Complex product questions | — | ✓ |
| Complaints / issues | — | ✓ (immediately) |
| High-value purchases | Bot assists → human closes | ✓ |
Key metric: Bot containment rate (% resolved without human) — target 60-70% for mature bots.
Output Format
# Conversational Commerce Plan: {Business}
## Channel Selection
- Primary: {platform} — rationale: {why}
- Entry points: {QR / ad / social / website}
## Conversation Flow
1. Welcome: {message template}
2. Discovery: {question flow}
3. Product Card: {template}
4. Checkout: {in-chat / redirect}
5. Post-purchase: {follow-up sequence}
## Bot vs Human Split
| Scenario | Handler | SLA |
|----------|---------|-----|
| {scenario} | Bot/Human | {response time} |
## KPIs
| Metric | Target |
|--------|--------|
| Response time | < {X} seconds (bot) / < {X} minutes (human) |
| Containment rate | > 60% |
| Conversation-to-purchase rate | > {X%} |
| Customer satisfaction (CSAT) | > 4.0/5 |Gotchas
- LINE Official Account tiers matter: Free tier limits monthly messages. If you exceed, messages are throttled. Budget for premium tier if customer base > 500.
- Don't over-automate: A bot that can't understand the question and loops "I didn't understand, please choose from the menu" destroys trust faster than no bot at all. Always offer a human escalation path.
- Messaging is asynchronous: Unlike phone calls, customers expect to message and come back later. Design flows that work with interruptions — save cart state, remember context.
- Privacy in messaging: Chat history is personal. Don't share conversations internally without consent, and be transparent about data usage.
- Social commerce is exploding in SEA/Taiwan: LINE Shopping, Instagram Shopping, TikTok Shop — these blur the line between social and commerce. Treat them as primary channels, not add-ons.
References
- For LINE Official Account setup, see
references/line-oa-setup.md - For chatbot NLU design patterns, see
references/chatbot-design.md