0 Interaction
0 Views
Views
0 Likes
Day 19
Week 3 · authority Chatbot expert
Custom chatbots OpenAI API Lead gen Support

Custom chatbots – AI assistants for lead gen, support, and sales

Build intelligent chatbots using OpenAI API that qualify leads, answer support questions, and book meetings – fully integrated with your automation systems from Days 1-18.

Multi-platform
Custom personas
Memory & context
Connects ALL days

🔗 Knowledge graph – Day 19 brings chatbots to every system

Day 1

Prompt engineering for chatbot personalities

Day 2

Zapier webhooks for chatbot triggers

Day 3

Make.com for chatbot logic flows

Day 4

OpenAI API core engine

Day 5

Lead qualification prompts

Day 6

Sales/support use cases

Day 7

3 builds practice

Day 8

BANT qualification via chat

Day 9

Sales assistant conversations

Day 10

Content for chatbot answers

Day 11

Support router via chat

Day 12

Niche-specific chatbots

Day 13

Workflow analysis for chat

Day 14

CRM data for personalization

Day 15

API security for chatbots

Day 16

Scraped data for chatbot knowledge

Day 17

Dashboard chatbot performance

Day 18

Proposals from chat conversations

Day 19

Custom chatbots

Shared link: Every system you've built can be accessed via chat. Day 19 teaches you to build conversational interfaces that qualify leads (Day 8), answer support questions (Day 11), and even generate proposals (Day 18) – all through natural conversation.

🎯 Why build custom chatbots?

📌 24/7 AI assistants that feel human

Custom chatbots using OpenAI API are different from rule-based bots. They:

  • Understand natural language, not just keywords
  • Adapt to each user's unique situation
  • Qualify leads using BANT (Day 8) through conversation
  • Answer support questions from your knowledge base (Day 10)
  • Book meetings and send proposals (Day 18)
  • Learn from every interaction
Analogy: Rule-based chatbots are like vending machines – press a button, get a product. AI chatbots are like knowledgeable sales associates who listen, understand, and help you find exactly what you need.

🏗️ Chatbot architecture – 5 layers

Layer 1: Interface

Website widget, WhatsApp, Messenger, Slack, SMS

Layer 2: Logic

Make.com / Zapier – routes messages, manages context

Layer 3: AI Engine

OpenAI API with custom prompts (Day 1, 4)

Layer 4: Knowledge

CRM data (Day 14), KB articles (Day 10), case studies

Layer 5: Actions

Create lead (Day 8), send proposal (Day 18), book meeting

📱 No-code chatbot platforms

ChatSimple

Website widget, OpenAI integration

WhatsApp Business API

Via Make.com or WATI

Messenger

ManyChat, Chatfuel

Slack

Internal chatbots for teams

SMS

Twilio + Make.com

Custom web widget

Embed anywhere

Telegram

Bot API + Make.com

Intercom

Via API

🤖 Build #1: Lead qualification chatbot (using Day 8 BANT)

Conversation example

👤 User: Hi, I need help with marketing for my real estate agency.
🤖 Bot: I'd be happy to help! To understand your needs better, could you tell me what's your monthly marketing budget?
👤 User: Around $2,000-3,000 per month.
🤖 Bot: Great! And are you the decision maker, or would others be involved?
👤 User: I'm the owner, I decide.
🤖 Bot: Perfect. What specific marketing challenges are you facing right now?
👤 User: We need more listing leads and better social media presence.
🤖 Bot: Thanks! When would you like to start? Immediate, next month, or just exploring?
1

System prompt (Day 1)

You are a lead qualification chatbot for [Company]. Your goal is to gather BANT information: - Budget: What's their budget range? - Authority: Are they the decision maker? - Need: What specific problem do they need solved? - Timeline: When do they want to start? Be friendly and conversational. Ask one question at a time. After gathering all four, summarize and confirm.
2

Make.com flow

Webhook receives message → OpenAI with conversation history → Store context in Data Store → If BANT complete, create lead in CRM (Day 14)

🎫 Build #2: Support chatbot with knowledge base (Day 10)

Conversation example

👤 User: I forgot my password and can't log in.
🤖 Bot: I can help with that! Go to our login page and click "Forgot Password". You'll receive an email with reset instructions. Would you like me to send the link?
👤 User: Yes please!
🤖 Bot: Sent! Check your email. If you don't see it within 5 minutes, check spam folder. Can I help with anything else?
// System prompt with KB access You are a support chatbot. Use the following knowledge base to answer questions. If you don't know, say "I'll connect you with a human" and escalate. KB Articles: {{kb_articles}}

📅 Build #3: Appointment booking chatbot

Conversation example

👤 User: I'd like to schedule a consultation.
🤖 Bot: Great! I can help with that. What date works best for you?
👤 User: Next Tuesday afternoon.
🤖 Bot: I have availability at 2 PM and 4 PM. Which works better?
👤 User: 2 PM works.
🤖 Bot: Perfect! I've scheduled your consultation for Tuesday at 2 PM. You'll receive a calendar invite shortly. Anything else?
Integration: Use Calendly API or Google Calendar to actually book appointments based on availability.

🧠 Chatbot memory – managing context

Stateless chatbots forget previous messages. You need to maintain conversation history.

Option 1: Make.com Data Store

Store conversation history by user ID. Append each message. Send last 10 messages to OpenAI.

Option 2: Airtable/Sheets

Log each message with timestamp, user ID. Query recent history.

Option 3: OpenAI Threads

Use Assistants API with persistent threads (advanced).

Option 4: Session cookies

For web widgets, store session ID in browser.

// Make.com Data Store structure Key: user_12345 Value: [ {"role": "user", "content": "Hi"}, {"role": "assistant", "content": "Hello! How can I help?"}, {"role": "user", "content": "I need pricing"} ]

🔄 Chatbots enhance every previous system

Day 8 – Lead qualifier

Chatbot gathers BANT naturally, creates lead in CRM.

Day 9 – Sales assistant

Chatbot handles initial conversation, hands off to email sequence.

Day 10 – Content engine

Chatbot pulls relevant articles from KB to answer questions.

Day 11 – Support router

Chatbot resolves 60% of tickets, escalates complex ones.

Day 14 – CRM

Chatbot creates/updates contacts, logs conversations.

Day 18 – Proposals

After chat, trigger proposal generation based on needs.

8 hands-on practice exercises

🤖 Exercise 1: Lead qualification prompt

Write a system prompt for a real estate lead qualification chatbot. Include BANT.

📱 Exercise 2: WhatsApp chatbot

Set up a Twilio WhatsApp sandbox. Connect to Make.com webhook. Test with simple echo.

🧠 Exercise 3: Memory with Data Store

Build a Make scenario that stores conversation history and sends last 5 messages to OpenAI.

🎫 Exercise 4: Support KB chatbot

Create 5 KB articles. Build a chatbot that answers from them. Test with questions.

📅 Exercise 5: Appointment booking

Integrate Calendly API. When user confirms time, create event.

📊 Exercise 6: CRM integration

When BANT complete, create contact in HubSpot with custom fields.

📄 Exercise 7: Proposal trigger

After chat, trigger Day 18 proposal generator with collected data.

📈 Exercise 8: Dashboard for chatbot

Log all conversations to Sheets. Build a Day 17 dashboard showing chats, qualified leads, etc.

📄 Client proposal – Custom AI chatbot

🤖 Custom AI Chatbot – Service Overview

What I'll build:

  • ✅ 24/7 AI chatbot on your website/WhatsApp/Messenger
  • ✅ Qualifies leads using BANT (budget, authority, need, timeline)
  • ✅ Answers support questions from your knowledge base
  • ✅ Books appointments directly into your calendar
  • ✅ Integrates with your CRM – creates contacts automatically
  • ✅ Escalates to humans when needed
  • ✅ Dashboard showing conversations, qualified leads, satisfaction

Platform: Website widget, WhatsApp, or both

Investment: $2,500 setup + $400/mo (includes AI costs)

ROI: Qualify 100+ leads/month without extra staff, 24/7 availability

📚 Resources

Day 19: You're now a custom chatbot expert

✔ Built 3 chatbots (lead qualification, support, appointment booking)
✔ Integrated with Day 8 BANT, Day 10 KB, Day 11 support, Day 14 CRM
✔ Mastered memory/context management
✔ Connected to multiple platforms (web, WhatsApp, Messenger)
✔ 8 hands-on practice exercises
✔ Client-ready chatbot service proposal

Week 3 · Day 19 – Custom chatbots (connected to Days 1-18)

You need to be logged in to participate in this discussion.

×
×
×