They are everywhere: on websites, in apps, on WhatsApp. Chatbots have become a mainstay of modern customer service. But not all chatbots are created equal.
In this guide, discover what a chatbot is, the different types that exist, and how to get the most out of them for your customer service.
A chatbot (a combination of "chat" and "robot") is a computer program capable of conversing with humans, usually in writing, by simulating a natural conversation.
The chatbot can:
In customer service, chatbots have become the first point of contact, filtering and handling simple requests, freeing up agents to deal with complex cases.
These are the simplest chatbots. They follow predefined scenarios: if the user says X, respond with Y.
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These chatbots use natural language processing to understand what the user is saying, even when phrased in an unusual way.
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The new generation. These chatbots use Large Language Models (LLMs) to generate natural and contextual responses.
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The main use case. The chatbot answers recurring questions: schedules, prices, return procedures, order tracking, etc.
The chatbot collects essential information before transferring to an agent: name, customer number, nature of the problem, etc.
The chatbot guides the user step by step: changing passwords, changing addresses, canceling orders, etc.
Even when agents are asleep, the chatbot responds. Simple requests are processed, while others are saved for the next day.
The chatbot proactively engages: "You seem hesitant, can I help you?" based on browsing behavior.
Klark enables you to deploy an AI chatbot that truly understands customer requests and provides accurate answers based on your knowledge base.
Percentage of conversations where the customer found their answer without human escalation. Target: 40-70% depending on complexity.
Post-conversation feedback. Target: 80%+ satisfaction.
Percentage of conversations escalated to a human. A rate that is too high indicates a poorly configured chatbot.
Percentage of users who abandon the conversation. Sign of frustration.
Average duration. Too short may indicate dropouts, too long may indicate a difficulty to resolve.
What questions should the chatbot handle? Be realistic: a chatbot that does everything often does everything poorly.
The chatbot must know when to hand over. A "Talk to an agent" button must always be accessible.
Give it a personality that is consistent with your brand. Formal or casual tone? Informal or formal address?
The chatbot must draw its answers from your knowledge base, not invent them.
What seems obvious to you may not be obvious to your customers. Test, observe, adjust.
Analyze conversations, identify failures, enrich scenarios.
Be transparent. "I am a virtual assistant" builds trust. Pretending to be human creates mistrust.
Hiding the way to reach a human frustrates customers. The chatbot should be an option, not a barrier.
A chatbot that asks 10 questions before answering will lose the user. Get to the point.
"I don't understand, can you rephrase that?" repeated over and over kills the experience. Offer concrete alternatives.
If the customer has to repeat everything to the agent after the chatbot, there is no point. Provide context.
The chatbot handles volume, the agent handles value.
No. It handles simple, repetitive requests, but humans remain indispensable when it comes to complexity, emotion, and exceptions.
From free (basic solutions) to several thousand dollars/month (advanced AI with integrations). ROI is measured in tickets avoided.
From a few days (simple chatbot) to a few months (custom AI chatbot with complex integrations).
Modern AI chatbots are generally multilingual. Rule-based chatbots require configuration for each language.
Chatbots have become an essential tool for modern customer service. When well designed, they improve the customer experience while reducing the workload for teams.
The keys to a successful chatbot:
Ready to deploy an intelligent chatbot? Discover how Klark can assist you.
