Chatbots make customer communication more efficient
Simple or recurring questions are unfortunately, but also fortunately, the rule in customer service. Unfortunately, because your service employees are both underchallenged by such questions and prevented from doing higher-quality work. And fortunately, because chatbots can solve such questions efficiently. Chatbots have long since ceased to be a niche offering and are now a service that is valued by customers. Read below what you should know about chatbots in customer service.
What is a chatbot?
A chatbot is a programmed system that conducts automated dialogues with customers. Rule-based chatbots work using structured questions and answers and defined rules. Machine learning-based chatbots are supported by artificial intelligence (AI) and have the medium-term ability to learn from customer interactions and constantly improve. At the same time, chatbots are currently best suited for dealing with simple questions. When used here, customer acceptance is particularly high because the customer appreciates the speed and all-time availability of the chatbot.
Possible uses for a chatbot?
The chatbot implements synchronous communication and can be used in live chat on the website, but also in messenger apps such as WhatsApp or Facebook Messenger. Once configured correctly, chatbots can really drive the interaction between customers and companies. They are available around the clock, faster and can access customer data more reliably than human service agents. A chatbot can therefore solve the following customer communication challenges:
- 24/7 in use
- Offer direct contact
- Improve customer satisfaction
- Generate up-selling and cross-selling
Possible application variants are:
- Waiting field communication (low-threshold information transfer "Did you already know....")
- Pre-qualification (clarify topic, request and remember key data e.g. name, customer number, contract number, order number) before handover to human chat agent
- Autonomous service chats for
a) recurring standard enquiries (FAQ)
b) dynamic bidirectional clarifications and process initiation in combination with CRM
(order, delivery status, cancellation, change of address, meter reading data)
c) personel advice
- product e.g. camera: options, scope, experience, objects, price
- service e.g. trip: type, climate, when, how long, where to, price
- coaching e.g. health, career guidance.
The right choice of a chatbot
Although chatbots, contrary to flowery marketing statements, are not yet suitable for in-depth communication with customers, they already significantly relieve the burden on customer service. Integrating a chatbot today is important, not least for reasons of gradually getting your customers used to virtual service experiences. If chatbots are really ready to go thanks to technological advances achieved, there will be less fear of contact among your customers as well as colleagues in customer service.
Identifying marketing bubbles
There is no such thing as a universally suitable chatbot. As with your staff, a chatbot cannot be a perfect travel advisor AND an expert in travel law. Introducing chatbots does not make humans redundant in customer service. Chatbots are not your superheroes. They do not replace humans, but expand their scope of action. For complex tasks, for intuition, empathy and creative problem solving, employees will be indispensable for a long time.
Chatbots can be operated without large IT resources. Of course, it requires thorough planning by all parties involved in the customer dialogue, but not a large IT department or even data scientists.
Your customer will rate the capabilities of a chatbot based on how well it imitates a human. If the customer cannot distinguish between a human response and that of the chatbot, the chatbot is considered intelligent. Currently, a chatbot that sounds like a human falls into one of two categories:
Rule-based chatbots work similarly to the Interactive Voice Response (IVR) in telephone service. We all know this "dial 1 for account information, 2 for transfer and so on". When the customer starts a chat, the chatbot presents a selection of options. The customer selects one of them and the chatbot responds with a pre-programmed answer. The further dialogue is structured via a set of rules using menus, questions, evaluations and information. The rule-based chatbot is very efficient in collecting basic information and then passing the chat enriched with data to a human colleague or triggering a defined automated process (change of address, order, booking, cancellation, etc.).
Rule-based chatbots are ideal as an introduction to the topic and for gaining initial experience. They are inexpensive to introduce, both in terms of the software and the required human resources. Due to rapid technological development, it is important to ensure that chatbots can be expanded to include machine learning at a later stage. Because sooner or later, your company will also use artificial intelligence (AI).
AI-based chatbots can ideally recognise the customer's intention from a free-text conversation. In doing so, they also see and understand connections that arise from spatially distant sentences, from previous events with this or even other customers. Machine-learning chatbots support the customer from additional resources. And the system continuously learns from the course of the dialogue. At least on paper, this already works. But in daily practice, it currently requires a bevy of highly specialised experts to constantly readjust the chatbot's knowledge and language. Without this help, AI-based chatbots "drift off".
What else needs to be considered?
- Your employees must be prepared. This applies to both administrators and chat agents. Both are upgraded because greater expertise is needed.
- The appropriate way of addressing customers must be identified so that it goes hand in hand with the company's service and communication strategy.
- Relevant information must be formulated and chatbot dialogues created. You should rely on long-term service employees who, thanks to their dialogue experience, can routinely recognise initial bot errors.
- Using AI, you can filter out relevant information from free-text customer statements.
- A soft launch of the chatbot, i.e. an offer only for selected customers, is recommended in order to recognise and correct basic errors.