| name | chatbot-automation |
| displayName | Chatbot Automation |
| tagline | Build and manage automated chatbot workflows for customer support and self-service. |
| description | Creates intelligent chatbot workflows that handle common customer
queries, collect information, and route complex issues to human agents.
Designs conversation flows, configures response templates, and tracks
chatbot performance metrics like resolution rate and handoff rate.
|
| department | ["Customer Support","Product"] |
| use_cases | ["Chatbot Design","Customer Self-service","Support Automation"] |
| tools_required | ["Intercom MCP","Slack MCP"] |
| agents_compatible | ["Claude / Claude Code","Cursor","Windsurf","ChatGPT","Any MCP-compatible agent"] |
| author | Webrix |
| verified | true |
| updatedAt | "2026-05-08T00:00:00.000Z" |
| version | 1.0.0 |
| exampleInput | Build a chatbot for our SaaS product that handles:
- Password resets
- Billing questions
- Feature requests
- Bug reports
|
| exampleOutput | Chatbot Configuration — SaaS Support
CONVERSATION FLOWS
1. Password Reset: Self-service (link to reset page)
2. Billing Questions: Check subscription -> show invoice -> escalate if needed
3. Feature Requests: Collect details -> create ticket -> thank user
4. Bug Reports: Collect repro steps -> priority assessment -> route to eng
PERFORMANCE (last 30 days)
Conversations: 1,840
Bot Resolved: 1,104 (60%)
Handed to Human: 736 (40%)
Avg Resolution: 2.3 minutes (bot) vs 18 minutes (human)
CSAT (bot): 4.1/5.0
TOP QUERIES HANDLED BY BOT
1. "How do I reset my password?" — 320 conversations
2. "What's my billing date?" — 180 conversations
3. "How do I upgrade my plan?" — 145 conversations
|
Chatbot Automation
Build and manage automated chatbot workflows for customer support and self-service.
Integrations: Intercom, Slack
When to Use
- The user wants to build chatbot flows for customer support
- Common queries should be handled without human intervention
- The user mentions "chatbot", "automated support", or "self-service"
Steps
Step 1: Identify Common Queries
Analyze support tickets to find the most frequent customer questions.
Step 2: Design Conversation Flows
Create decision trees for each query type with response templates.
Step 3: Configure Handoff Rules
Define when and how to escalate to human agents.
Step 4: Track Performance
Monitor resolution rate, CSAT, and handoff metrics.
Output
Deliver:
- Chatbot conversation flows
- Response templates
- Performance tracking dashboard
