AI in customer service - how can you use it effectively? How does it become a win-win situation?
The use of artificial intelligence is undoubtedly one of the hottest trends currently driving manufacturing companies and service providers in the development of Industry 4.0. It promises greater efficiency with a reduced cost structure. This makes it exactly the right target in times of increased cost pressure. Now, the use of AI in industrial operations is by no means new. It has long been used successfully in production lines. In addition, a large number of everyday electronic products have AI components. Many production steps are completely taken over by these systems, such as assembly robots, pick-and-place machines, and so on.
Let's step out of the manufacturing realm with the notion of relying on AI. Instead, let's turn to its use in industrial service. This involves a whole new set of challenges, and its use can become a balancing act. Because on the one hand, there are the corporate goals of cost savings and processing service cases as efficiently as possible. On the other hand, there is the customer, with his or her desire and habit of receiving individual and personal service from a human being.
This is a classic conflict of interest that particularly affects companies and service providers that have traditionally placed little emphasis on professionally organized and standardized online contact with their customers. Their behavior in this area was and is quite different from that of large online retailers or manufacturers of consumer products, whose clientele has been used to processes controlled via artificial intelligence for years.
But that's no reason to view artificial intelligence in customer service as a contradiction that can't be solved. If AI is used correctly and in a results-oriented manner, it can open up new opportunities and not only support but strengthen customer relationships.
Artificial intelligence - what is it in general?
AI is a programming concept that enables machines - including not only computers - to "think" like a human and imitate human behavior. As a rule, machines or systems equipped with AI perform tasks for which human intelligence is required, but which are strongly determined by routines. This can be speech recognition, translation services for languages or visual perceptions. We know them from many areas such as online games.
In their simple version - then called "weak AI" - they draw on large amounts of data fed into the system and use their information for the tasks. The more data you feed into your model, the more accurate and helpful it becomes. Almost all AI currently in use is "weak AI."
Most chatbots today, for example, use "static" AI that learns not from interaction but from clearly predefined paths. Based on this database and defined decision paths, they can trigger actions such as forwarding calls or chats to a service employee or generate multiple choice questions and offer corresponding answer options.
Another AI variant is machine learning. They have been used successfully by larger internet platforms for a long time. Again, there are extensive data sets. They are analyzed via algorithms that learn from them. They classify and make predictions about platform users' preferences and interests. At the other end of the scale is strong AI. It has programmed human intelligence that allows it to do almost any task that would otherwise be done by a human. As of today, however, we are still very much in the realm of science fiction here. Strong intelligence learns, plans, weighs and communicates, develops an enormously high intelligence quotient and communicates with human voice in understandable language.
Here we are in the sub-area of AI that makes people uncomfortable, downright scares them. But in contrast to these reservations, AI will most likely not take over the world and cost service employees their jobs. But it will change it, and in many places it will probably make it easier. The implementation of strong AI, on the other hand, is still primarily a vision, even after decades of research.
Artificial and human intelligence in customer service - the combination is decisive
Let's now move on to a meaningful AI deployment in CRM. If it is to be used successfully in a company, it must meet its targets at least to some extent. However, it is much more important that they are accepted by your customers. He must be able to reach his destination quickly, appreciate the high level of accessibility of 24 hours a day, 7 days a week, and, if in doubt, be passed on to a "real" service employee relatively quickly.
This is when the use of artificial intelligence can be of benefit by answering frequently recurring questions about deadlines, delivery times or known problems. If the questions are complex and require human intelligence, the system quickly passes them on to an employee who can deal with the issue in depth. This also adds value to the company.
In advance or in parallel, AI can support service staff in tracking order data, etc. Here, AI with its algorithm is faster in processing. Service employees, on the other hand, no longer have to deal with labor-intensive routine processes. They use the AI's information on the customer's order history, emotional state and needs when advising and supporting customers. This is a quality of service that customers also appreciate. If this scenario can be realized, it is a successful AI project.
An absolute prerequisite - a clean, comprehensive set of data
The road to this goal can be long and also arduous. The functionality of AI based on machine learning depends on quantity and quality of data. Data hygiene is a very crucial factor. This is because AI is much easier to implement with well-cleansed and organized data. Incomplete customer records or duplicate customer accounts have no place here and complicate the project immensely. The data needs to be reviewed and manually cleansed upfront in order to use it in the AI environment and get accurate results. After that, it requires constant updating to maintain the entry quality. This means a lot of work up front, but then pays off with a much more accurate AI. Here, most companies require various tests in purpose-built test environments to define the right parameters.
Unternehmenswachstum durch KI im Kundenservice?
AI in customer support increases the productivity of the entire department and individual employees. The efficiency of the contact center increases and the personal advice given to customers is supported with individualized information. Customers perceive this as a personal result, an encounter at eye level, and appreciate it. Thus, AI in customer service can take on a supporting role in the development of sales and marketing measures, with the goal of further increasing customer satisfaction.
During the introduction, the question must always be asked whether the installed AI support in the service department passes the everyday test. Is it beneficial for everyone involved? Is the solution accepted by the customer? Where are there problems that need to be fixed? This phase requires experimenting, simply trying something out once and then critically scrutinizing it. It is the phase to gain experience in dealing with AI. Valuable experience that companies in the industry can use to gain an edge in the medium and long term.
If you have any questions about this extensive range of topics, please do not hesitate to contact us. Simply contact us by phone or via our contact form: