AI Chatbots: AI in Customer Service
We explain how to design a chatbot that answers frequently asked questions accurately, relies on your knowledge base and hands the conversation to a human when needed.
Aurora YazılımEditorial team
6 min read
An AI chatbot is a chat assistant that understands a customer's question with a language model and answers based on the business's own information. It works 24/7 on your website, WhatsApp or social media channels. A good bot resolves frequent questions, looks up information such as orders or reservations from your systems, and hands off to a human what it can't resolve.
Rule-Based Bot vs. AI Bot
Older-generation bots worked with buttons and keywords: if a customer typed "shipping," the shipping menu opened, and if they phrased something unexpected, the bot got stuck. An AI chatbot, on the other hand, understands a freely typed question, tolerates typos and goes to the right topic even if you ask the same question in different ways.
This flexibility brings a risk too: on a topic it doesn't know, a language model can invent a fluent but wrong answer. That is why a well-designed bot is built to rely not on the model's general knowledge but on the business's approved knowledge base.
| Criterion | Rule-based bot | AI bot |
|---|---|---|
| Understanding questions | Keywords and menus | Free text, context |
| Setup | Every scenario is drawn by hand | A knowledge base and rules are defined |
| Flexibility | Low | High |
| Type of error | Says it doesn't understand | May invent a wrong answer |
| Best suited for | Simple, fixed flows | Varied and open-ended questions |
What Can a Chatbot Handle?
The right starting point for customer service automation is to analyze the questions you receive. In most businesses, the bulk of questions cluster around a few topics; the bot should take on those first.
- Information questions: Opening hours, address, return terms, payment options, delivery times.
- Status inquiries: Where is my order, is my reservation confirmed, has my invoice been issued.
- Product and service guidance: Recommending the right product or package for the need.
- Lead collection: Taking the name, phone number and need for a quote or callback request and passing it to the team.
- First step of appointments and bookings: Showing availability and leaving final confirmation to the system or a human.
Examples by industry
In an online store, the bot handles mostly shipping, return and size questions. In a hotel, questions about availability, check-in and check-out times, parking and breakfast stand out. At a travel agency, tour programs, payment plans and paperwork dominate; at a real estate office, it is listing details and appointment requests.
In every industry, what determines how useful the bot will be is the same: the information its answers rely on must be current and in one place in the system. That is why industry-specific software solutions that manage reservation, listing or tour information are the backbone of a good bot. When information is updated in one place, the bot and the website both say the same true thing.
The Knowledge Base: The Bot's Memory
The key to the bot answering correctly is the information it is fed. The common method is an approach known as RAG (retrieval-augmented generation): when a customer asks a question, the system first finds the relevant document passages in the knowledge base, and then the language model produces an answer based only on those passages.
The knowledge base consists of frequently asked questions, return and delivery policies, product information, price lists and campaign terms. Documents should be written to be short, current and to state one truth. Two documents that contradict each other lead the bot to give contradictory answers as well.
The instruction layer defines the bot's boundaries: which topics it talks about, which topics it answers with "I'm passing this on to our team," and which information it never gives. It should be stated clearly that it must not make things up if it doesn't know.
A Chatbot Connected to Your Systems
A bot that only reads documents answers general questions. What the customer is really curious about, though, is information specific to them: their order, reservation or invoice. For this, the bot needs to connect to your business systems through an API.
If order, shipping and invoice information in an online store are collected in a single panel, the bot can read the correct status from one source. That is why an e-commerce integration built without middleware software is also the foundation of chatbot projects. In accommodation, the same role is played by hotel software, which manages reservation and room information; in restaurants, menu and price information is kept current with a QR menu system.
Security must come first in these connections. The bot should not share personal data without verifying the customer with details such as an order number and phone number, and it should start with read-only access. To connect recurring background jobs, the tools in our workflow automation article can also be used.
Website and WhatsApp Chatbot
Website chatbot
A website chatbot usually works as a window that opens in the corner of the page. Because it knows which page the visitor is on, it can offer context-appropriate help: a size question on a product page, an installment question on the payment page. The window design should not cover content on mobile and should be easy to close; these details are planned in the UI/UX design process.
WhatsApp chatbot
In Türkiye, a significant share of customers prefer to message businesses on WhatsApp. To build a WhatsApp chatbot, the official WhatsApp Business Platform infrastructure that Meta offers to businesses is used. This platform has message templates, a customer service window and pricing rules; check the current terms in the official documentation before setup.
Connecting a personal WhatsApp account to automation with unofficial tools can get the account shut down; for businesses, the right path is the official infrastructure.
How to Design the Handoff to a Human
A chatbot's quality is measured less by the questions it answers than by how it handles the moment it can't answer. A bot that traps the customer in a loop creates a worse experience than having no bot at all.
- The handoff should start immediately when a customer uses a phrase like "agent," "human" or "manager."
- If the bot can't resolve the question in two attempts, it should offer a handoff.
- At handoff, the conversation history should be passed to the agent so the customer doesn't have to explain everything again.
- If handoff isn't possible outside business hours, the bot should say so clearly and give a time for follow-up.
- New questions the agent resolves should be added to the knowledge base.
Data Protection, Security and Measurement
A chatbot processes personal data: name, phone, address, order history. So the privacy notice, which service processes the data and how long it is kept should be planned from the start, in line with KVKK (Turkish data-protection law, comparable to GDPR). Transferring data to an AI service operating abroad also needs separate evaluation. On these matters, check current legislation and your legal counsel.
On the measurement side, a few core indicators are enough: the share of conversations the bot resolves on its own, the handoff rate, resolution time after handoff and the end-of-conversation satisfaction score. Reading the conversations with wrong or incomplete answers every week is the most effective way to improve the knowledge base.
To see the chatbot as part of a broader AI plan, take a look at our article on using AI in business, and for the basics of chat use, our guide on how to use ChatGPT.
- Make it clear to the customer that the bot is an AI assistant.
- Never ask for data such as card details and passwords inside the chat.
- Limit access to conversation records to authorized people.
Frequently Asked Questions
01Do I need to redesign my website to add a chatbot?
A simple chat window can be added to most sites. But if the bot will read order or reservation information, the site and the system behind it need to be suitable for integration. With old and scattered infrastructure, it is more efficient to deal with the data structure first.
02How many languages can a chatbot serve in?
Language models can understand and answer in many languages, which is a big advantage for businesses with foreign guests or customers. Still, the knowledge base must be correct in the main language, and critical information must be checked after translation.
03Does a chatbot replace customer service agents?
It reduces the agents' load by taking on repetitive questions, but conversations that involve complaints, persuasion and special cases stay with humans. The best results come from a setup where the bot does the first greeting and agents focus on difficult cases.
A well-designed AI chatbot gives customers instant answers and frees your team from repetitive questions; what determines its success is the right knowledge base and solid system connections. Explore our industry-specific software solutions that keep your data in one place and our e-commerce integration infrastructure, and get in touch to discuss your project.
