In customer service, an AI chatbot primarily takes on three types of tasks: answering recurring questions using company knowledge, capturing customer inquiries through dialogue and routing them in a structured way, and handling transactions when connected to the appropriate systems. Anything that does not fit into these three patterns is handed over to the team with full context. This article walks through 15 use cases that arise daily in almost every service team and shows what the chatbot needs for each of them.
At a Glance
Information delivery requires a well-maintained knowledge base. It is the quickest way to get started.
Capturing inquiries requires a dialogue flow that requests and validates the necessary details.
Handling transactions requires integration with CRM, ERP, or ticketing systems.
Human handover is an essential part of every use case, including the previous chat history.
The best starting point are the use cases that occur most frequently and touch the fewest systems.
Three Patterns Covering Almost Every Task
Before looking at specific use cases, it is worth examining the underlying pattern. Almost every recurring task in customer service follows one of three patterns.
Answering. The customer asks a question, and the chatbot responds using manuals, spec sheets, websites, and FAQs. For this, it only needs access to knowledge—no system integrations required.
Capturing. The customer has an inquiry that requires human handling. The chatbot requests the necessary information, validates it, and forwards the complete request—for example, via email to the specialist department or as a ticket.
Executing. The chatbot accesses a system, reads a status, or updates records. This is the most impactful, but also the most complex part, as it requires system integration.
15 Use Cases from the Service Team
Information Delivery
1. Questions about products and services. What a product can do, which variant fits best, what is included in the contract: The chatbot answers using product data and documentation, complete with source citations. This is usually the use case with the highest volume.
2. Technical questions from manuals. Installation, operation, maintenance intervals. The answer is hidden in a PDF the customer cannot find. The chatbot locates the relevant section and explains it in the customer's language.
3. Questions regarding invoices, deadlines, and terms. When payment will be debited, warranty duration, express shipping costs. The answers remain the same; only the questions are phrased differently.
4. Finding documents and forms. Data sheets, certificates, return forms: The chatbot provides the link or file directly, eliminating the need to search within service operations.
5. After-hours availability. Evenings and weekends, the chatbot answers the same questions as during the day and records everything that needs to wait until the next morning. Learn more in our article on availability outside of service hours.
Capturing Inquiries
6. Complaints and damage reports. The chatbot prompts for the order number, product, and error description, verifying the details before forwarding the inquiry. The team receives a complete case without needing to ask follow-up questions.
7. Service requests and technician appointments. Equipment, location, urgency, preferred date: The dialogue gathers everything dispatch needs and forwards the request.
8. Address and master data changes. New address, new contact person, updated billing address. The chatbot captures the change conversationally and submits it—or writes it directly to the system if integrated.
9. Callback requests. When an issue requires a conversation, the chatbot records the topic, availability, and phone number. The callback can then address the matter right away.
10. Cancellations and contract modifications. Contract, date, reason. A structured editorial dialogue reliably guides users through the steps required to ensure legal completeness.
11. Pre-qualifying new inquiries. What is the customer looking for, for which product, in what quantity? The chatbot clarifies these points before handing over to sales or service. Discover how this improves lead quality in our article on the B2B website chatbot.
Handling Transactions
12. Order and shipping status. Where is my shipment? With integration into ERP or e-commerce systems, the chatbot checks the status and replies immediately. Without integration, it can only route the request.
13. Ticket status. What is the status of my complaint? The chatbot queries the ticketing system and provides the current progress.
14. Creating tickets directly. The chatbot creates the ticket with all captured details directly in the system and provides the ticket number to the customer.
15. Booking and rescheduling appointments. With access to the calendar, the chatbot offers available slots and books the selected appointment. Read our guide on integration with CRM and ERP to see how integrations with SAP, Salesforce, or HubSpot work.
What Each Use Case Requires
Use Case | Knowledge Base | Dialogue Flow | System Integration |
|---|---|---|---|
1 to 5, Information delivery | yes | rarely | no |
6 to 11, Capturing inquiries | partially | yes | optional, otherwise routing via workflow |
12 to 15, Handling transactions | partially | yes | yes |
The table explains why many projects begin with information delivery. These use cases deliver immediate relief and only require access to knowledge. Inquiry-capturing cases follow as soon as the key dialogue flows are established. Executing transactions comes next, once system integrations are in place.
Where the Chatbot Hands Over
No chatbot should resolve every single case on its own. When an answer is not in the knowledge sources, a customer is upset, or a decision is needed, it hands over to a human agent—along with the previous chat history and captured data. Our article on What a Chatbot Shouldn't Answer outlines the types of questions a chatbot should avoid answering altogether.
How to Get Started
Collect customer inquiries from recent weeks and categorize them into the three patterns.
Select three high-volume use cases that do not require system integration.
Verify whether the required knowledge is available in existing documents or on your website.
Define who the chatbot should hand over to when it cannot resolve an issue.
After launch, expand to inquiry-capturing use cases, followed by automated transactions.
How Mercury.ai Implements This
Mercury.ai consolidates manuals, spec sheets, websites, and FAQs into the Knowledge Hub, answering questions strictly from these approved sources with clear references. Editorial dialogues in the No-Code Studio capture inquiries, validate details such as email, phone number, or dates, and forward them via workflow. Through integrations, the chatbot reads and writes data in CRM, ERP, and ticketing systems directly during live conversations. If it reaches its limits, it hands over to your team in Agent Desk with the full chat history. Learn more on our page about the AI Chatbot for Customer Service and in the guide to Automating Customer Service with AI.
Conclusion
Most recurring tasks in customer service fall into one of three patterns: answering, capturing, or executing. This naturally determines the ideal implementation sequence. Starting with information delivery provides quick relief for your team and builds a solid foundation for everything that follows.
Want to know which use cases make the most sense for your service team to start with? Talk to us.
