How rule-based (keyword) chatbots work

A rule-based chatbot operates on if/then logic:

• If message contains "PRICING" → send pricing message
• If user comments "FREE GUIDE" → open DM and deliver guide
• If user sends first DM → send Instant Reply
• If message contains "BOOK" → send booking link

Everything outside these rules falls to a default reply ("I didn't quite catch that — type PRICING or BOOK for quick answers") or goes unanswered by the bot.

Tools: ManyChat, Chatfuel, and most comment-to-DM platforms are primarily rule-based.

Strengths:

• Highly predictable — you know exactly what the bot will say in every situation
• Excellent for specific campaign flows (lead magnet delivery, contest entries)
• No risk of unexpected or inaccurate AI-generated content
• Can guide users through structured journeys (qualify → inform → book)

Limitations:

• Cannot handle questions outside its programmed scenarios
• Requires building and maintaining flows for every scenario
• Falls short on conversational, natural-language questions
• Any variation in phrasing ("what does it cost?" vs "pricing?" vs "how much?") may break keyword matching

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How AI chatbots work

An AI chatbot reads each incoming DM in full and generates a response using a language model, drawing on your configured business knowledge base.

• Customer asks anything → AI reads the full message and intent → AI generates a contextual response using your business information → customer receives an accurate, relevant reply

Tools: ReplyMind (Claude AI), ManyChat's AI Step (adds AI to specific flow branches), Respond.io's AI agent.

Strengths:

• Handles any question, any phrasing, any combination of topics
• No flows to build — just a knowledge base to configure
• Responses feel like a knowledgeable human wrote them
• Scales without maintenance — the AI handles new questions without needing new flows

Limitations:

• Less predictable — responses can vary based on how the AI interprets the message
• Requires a thorough, accurate knowledge base to produce good responses
• Cannot follow structured campaign paths as precisely as rule-based flows
• Needs human oversight for unusual edge cases

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Which one to use

Choose rule-based if:

• Your primary use case is a specific campaign (comment-to-DM for a lead magnet, contest, or offer)
• Every DM scenario is predictable and you want exact control over every response
• You're running a high-volume marketing campaign with a defined flow structure

Choose AI if:

• You receive varied customer enquiries that don't follow predictable patterns
• You want DM automation that handles your full customer service load, not just specific triggers
• You want setup to take hours, not days (no flows to build)
• You want responses that feel like a knowledgeable human reply

Choose both if:

• You want AI for general DM handling (any incoming customer question answered automatically)
• Plus keyword triggers for specific campaigns (comment-to-DM on Reels, BOOK keyword)
• This is the highest-coverage setup and the most common for businesses that take both DMs and campaigns seriously