Practice 04 · Artificial intelligence & automationCustomer support chatbot: absorb the repetitive, keep people for the complex
A support team rarely drowns because of hard cases. It drowns under the simple requests that arrive by the hundred: where is my order, how do I change my address, what do I do if the product will not switch on. A customer support chatbot handles that volume accurately and recognises straight away the situations that need an agent.
A review of your most frequent requests, no commitment
Our positionWhy we refuse to hide the “talk to a person” button
Some chatbots are tuned to hold the customer as long as possible before transferring. That damages the relationship: a customer who has been going round in circles reaches the agent angry, and the agent loses the time the chatbot was supposed to save. The right setting is the opposite: resolve quickly what can be resolved, and transfer just as quickly, with the context already captured, what cannot.
Who it is for, and whenSigns your support team needs a chatbot
When your agents spend the day pasting answers that already exist in your FAQ, or when first-response times keep stretching, support needs an intelligent filter rather than another hire.
- Order and delivery tracking makes up a large share of tickets and could be resolved by looking up your management system.
- Product usage questions are covered in a guide that few customers read before writing in.
- Contact spikes after an update or an outage swamp the team for a few days, then subside.
- Customers write through several channels and get different answers depending on which agent picks them up.
The scopeWhat Kopus puts in place for your support
The foundation is a structured knowledge base built from your documentation, your procedures and the standard replies of your best agents. Where possible, we add read access to your systems: order status, subscription history, ticket state. The chatbot can then answer on the customer’s specific case once their identity has been verified.
Every conversation is linked to your ticketing tool, for example Zendesk, Freshdesk or a module built into your CRM. When the chatbot cannot resolve a request, it creates or enriches the ticket with a summary of the exchange, and the agent picks up without making the customer repeat themselves. Escalation rules are explicit: a complaint, a refund request, visible frustration, or simply asking to talk to someone.
We also deliver tracking of the resolution rate by reason for contact, the share of conversations transferred, and the topics where the chatbot fails, which guides the decision on what else to entrust to it.
What you get
- Immediate answers to routine requests.
- Advisers focused on the cases that matter.
- Reliable indicators to steer customer service.
Sample request triageThree possible outcomes for every request, decided from the first message
The chatbot answers on its own only when the answer exists in your data or your approved knowledge base. Everything else reaches your agents as an already qualified ticket, and signs of tension jump the queue. This split is set reason by reason, and revised as the indicators come in.
Triage: reason, customer record, urgency signals
Resolved automatically
Tier 1 · answer grounded in your data
Request 1Order trackingChat
“Where is the order I placed on Monday?”
Status and delivery date read from the management system
Source: customer record, identity verified
Request 4Change of addressEmail
“How do I change my delivery address?”
Procedure sent with the link to the customer area
Source: knowledge base, approved article
Qualified, then passed on
Tier 2 · ticket ready for an agent
Request 2Technical questionWeb form
“The device will not switch on since the update.”
- Summary
- Will not start after the update, reset already attempted
- Category
- Technical · fault
- Priority
- Normal · under warranty
Request 5Product returnChat
“I would like to return an item I received forty days ago.”
- Summary
- Return outside the standard period, item unused
- Category
- Return · exception
- Priority
- Normal
Urgent: adviser straight away
Escalation · context handed over
Request 3ComplaintEmail
“Third message with no reply, I am asking for a refund.”
- Complaint
- Refund
- Frustration
Immediate transfer to the priority queue, history attached
Request 6Asks for an adviserChat
“I would rather talk to someone.”
- Explicit request
Transfer with no further questions
What we track afterwards
- Resolution rate by reason
- Share of conversations transferred
- Reasons that fail
- Satisfaction after the exchange
The methodThe stages of a support chatbot project
Contact reason analysis
We classify a sample of your tickets by reason, volume and complexity to identify those the chatbot can resolve end to end.
Resolution path design
For each reason retained, we write the dialogue, the checks and the exit point, whether resolution or transfer.
System connections
Read access to order or account data, link to the ticketing tool, customer identification rules.
Shadow testing
During an observation period, the chatbot suggests replies to your agents, who approve or correct them before anything is sent.
Opening to customers on one channel, then extension to the others once the first indicators have been read.
Your questionsFrequently asked questions about this service
Can a chatbot replace customer service?
No. It takes on well-defined, repetitive requests and must always allow an agent to step in when the situation calls for it. Its success is measured as much by the quality of its handovers as by the requests it resolves.
How do you stop the chatbot giving false information about a customer’s account?
By never letting it guess: order data comes from your systems, procedural answers from your approved knowledge base. If the information exists in neither, the chatbot transfers.
What happens to the conversations with customers?
They are kept in your ticketing tool under your existing rules. We check with you where the model provider processes data and what needs adding to your privacy policy.
Do customers know they are talking to an AI?
Yes, always. It is a matter of trust and, increasingly, a regulatory requirement. The assistant introduces itself as such and offers a human at any time.
Which support tools can you connect?
The main ticketing and messaging solutions on the market, as well as your internal tools through their APIs. We check compatibility during framing.
What share of requests can a support chatbot handle alone?
It varies by business; simple requests, tracking, status, practical information, often represent a large share of volumes. Kopus measures this rate from the first weeks rather than announcing it in advance.
How are unhappy customers handled?
The chatbot detects signs of dissatisfaction and immediately transfers to an adviser, with the conversation history. It never tries to handle a dispute alone.
Go furtherPages related to this service
- Your challenges · 03I want to bring AI into my companySpot the AI uses that make sense and keep control of decisions.
- Practice 04Artificial intelligence & automationUse new technologies to simplify operations, save time and create new opportunities. We integrate AI where it does a concrete job, with your teams in control.
- 04 · AI & automationAI chatbot for businessA chatbot is only worthwhile if it answers better and faster than a FAQ page. We build conversational assistants grounded in your real content, that know their limits and hand over to a person at the right moment.
- 04 · AI & automationBusiness process automationEvery company has processes everyone does by hand because “it has always been this way”. We spot them, simplify them, then automate them, with or without AI depending on what is most reliable.
Our workProjects built on this expertise
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A review of your most frequent requests, no commitment