Chatbots in online retail

Digitization Chatbots in online retail

Published on 01.09.2021 by Sophie Hundertmark, PhD candidate at the Institute of Financial Services Zug IFZ

Most Swiss online retailers still don’t use chatbots. This article explains how and why e-commerce companies should be changing that.

When you look at the websites of Swiss online retailers, you will soon notice that most providers do not yet offer their customers a chatbot service – i.e. an automated messenger channel.

Companies such as,, and others offer their customers a live chat service during specific opening hours, but most e-commerce companies still lack the courage to operate a computer-controlled chatbot service.

Live messengers vs. chatbots

Chatbots and live messengers have at least two things in common: both communicate with customers via text-based chat and both can be easily integrated with messenger apps, such as WhatsApp or on your own website.

While a live messenger always requires a person in the background, the chatbot can communicate autonomously with its users 24/7.

It should be noted, however, that the chatbot does not always understand or answer all user inquiries in the same way that a human advisor could. Chatbots can only answer the questions they have been trained for in advance. As a rule, they are also trained to deal with specific user queries. If a user asks a question in a different way or uses non-standard language, such as dialect or slang, the chatbot can experience difficulties in finding an answer. Chatbot responses are also fixed in advance. In the event of a complaint, users cannot “negotiate” with a chatbot in the same way as with a person, but must accept the defined parameters of the chat.

Chatbots in action

When we look at other industries, such as the financial sector, it becomes obvious that chatbots are mainly used for repetitive queries. Questions such as “How long is the delivery time?” or “Do you also deliver abroad?” are some of the standard inquiries in most online shops that can be answered simply and easily by a chatbot. By handling simple and repetitive inquiries, the chatbot relieves the workload for customer service staff, who then have more time for complex inquiries.

Hybrid chats are seeing increased use in some industries. Many insurance companies, for example, first provide their customers with general advice via chatbot, and when the topics become more specific, the chat is transferred directly to a human customer advisor. Here too, the chatbot handles the simple, repetitive questions while the person is responsible for more complicated matters.


1. Find a use case

Many online retailers would like a chatbot to be a digital product advisor who can ideally answer any questions about their entire online range. But this use case is very complex and is usually not implemented as expected. It is important to ensure the initial use case focuses on a specific category of questions. The question categories can then be continuously expanded.

2. Define the target group

The next step is to define the target group more precisely. It is important to consider the situations in which the bot is used by the users and their expectations of the chatbot at the time of use.

3. Define tone

Depending on the company’s image, the target group and the actual situation, it is important to define the right tone to be used in the chat. Depending on the use case, the chatbot should react with empathy, express more emotion, or appear very neutral.

4. Generate content

Most online retailers these days track customer inquiries and know exactly which questions are being asked and which answers users want. These data serve as the basis for the chatbot. The dialogues are written depending on the previously defined chat tone and some general chatbot best practices.

5. Choice of technology and implementation

As soon as all the key points, including the desired features for the chatbot, have been determined, a suitable technology is selected and the chatbot can be implemented. But before this new employee can be made available to the general public, it should be tested internally and optimized, if necessary.

The chatbot can then be further developed in subsequent sprints to become a successful digital touchpoint of the online shop step by step.


Due to the current situation, Connecta Bern will again be held as a digital event in 2021. Connecta is renowned for shining a light on the diverse nature of digitization and this year will be no different with content presented across the three formats of Connecta Blog, Connecta TV and Connecta Talk. Find out more here:


Sophie Hundertmark (PhD candidate and chatbot advisor) Institute of Financial Services Zug

Sophie Hundertmark is a PhD candidate at the Institute of Financial Services Zug IFZ, and also works as an independent consultant for the strategic support and implementation of chatbot projects. She is doing her doctorate on the use of chatbots in the banking and insurance sectors.

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