A bouquet of possibilities
“Always stay in touch!” – Nowadays, this motto no longer only applies to the countless stars, starlets, influencers or local politicians who inform us almost continuously about news from their lives on various channels. It also applies to all service-oriented companies that place value on customer proximity and want to perfect their customer journey. The old motto “Click, buy and forget” has long since become a thing of the past. On the one hand, because companies always want to keep their customers up to date on new products, current offers and promotions. On the other hand, because existing and potential new customers also demand this communication.
Over the past three decades, the range of communication options available for this purpose has expanded dramatically. Traditional options such as personal contact, letters, telephone calls and faxes have been supplemented by e-mails, chats or social media posts. Sometimes the channels are even tangled up in a wild, unpredictable mix.
But how do companies react to the new requirements in the area of customer communication? Apart from the simple offer of contacting via a special channel, are there other technologies and methods to make contacting and communication as profitable as possible for both the customer and the company? Fortunately, this question can be answered with a resounding “Yes!” However, it should be noted that each of the numerous communication channels must be considered individually in order to be able to develop tailor-made solutions for each channel. Communication channels can basically be divided into two classes: synchronous and asynchronous. Customers who make contact via synchronous channels usually expect an immediate response: calls should be answered immediately. For chat requests – via webchat or messenger app on the smartphone – a fast, at best immediate response is required. And, of course, customers also expect to be served quickly and satisfactorily in personal contact, for example when visiting a branch office.
The asynchronous channels include letters, faxes, but also e-mails or social media posts. Of course, reactions are expected here as well, but they do not have to be immediate. Instead, a certain delay seems not only to be tolerated but usually even expected. In the case of the classic letter request, this waiting time is probably the highest (in some cases weeks may pass until the response is received). For e-mails the accepted duration is already much lower (rather days) and on some social media channels an even faster response is expected (even hours).
Bots as helpers in synchronous customer dialog
The transition between synchronous and asynchronous channels is particularly fluid on the threshold between chat and social media. In the following, the focus is on synchronous channels. Here, companies face the challenge of meeting high customer and service demands. They must have sufficient competent personnel on hand to be able to respond to customer enquiries not only appropriately but also as quickly as possible.
Many companies meet this challenge by providing their customers with an artificially intelligent contact person in certain situations. So-called bots are able to make telephone calls as well as enter into a customer dialog via chat.
Basically, dialog on both channels – speech and text – is based on an almost identical principle. The only major differences are in the preprocessing of the input and in the formatting of the output: While the voicebot deals with mumbling callers or dialects in the input, the chatbot has to be able to deal with spelling mistakes and symbolic inputs (emojis). The voicebot must again make sure that the output is very fast, because even the shortest pauses in a phone call are perceived as unpleasant. The chatbot, on the other hand, should be able to symbolically signal and transmit messages, if this is desired.
Consequently, each of these two variants of human-machine communication has its own special features. This article focuses on the chatbot and the opportunities and risks associated with its integration into the customer dialog.
The art of conducting a conversation
The first question is how communication via chat works in general. Classically, the conversation here is initiated by the customer, who sends a corresponding request to the company. The contact is linked to the expectation of receiving a quick answer. Conceptually, at this point it does not matter whether the responding contact person is a human being or an automat. A free contact person will accept the chat request, greet the customer in the interest of the company and inquire about their delivery with a specific question. Based on the customer’s answer, a dialog will then be initiated in which his request will be defined more precisely and all general data for the fulfilment of this request will be clarified.
The dialogs always follow the same steps. While the chatbot reveals information and asks further questions, the customer provides answers and – if necessary – makes selections. In addition, the chatbot draws supplementary information from backend systems and can make decisions based on this information, which are important, sometimes even elementary, for the dialog. For example, if a customer inquires about the whereabouts of a long-awaited order, the bot asks for the corresponding order number and uses it to check the delivery status. If a tracking number is also available, it can also be transmitted, so that the customer can keep himself informed about the further progress of his order.
How does the bot tick?
In order to find out which technology enables chatbots to conduct intelligent dialog, it is essential to look behind the facade. Here, too, there are basically two variants. Either the course of the entire dialog is manually designed so that the chatbot ultimately only has to process a dialog script and follow a strict if-then logic. Or the bot relies on special machine learning algorithms to provide appropriate answers based on the broadest possible information base. In this case, the term Artificial Intelligence (AI) is often used, even if the keyword certainly applies to both variants of automated dialog guidance.
Of course, both types have their respective advantages and disadvantages. In the case of the scripted variant, the operators of the bot face the challenge of anticipating all eventualities in the dialog processes and planning adequate responses. The choice of words and the logical sequence of events should not be based on internal company practices, but should be conceived from the perspective of a customer who lacks extensive knowledge of internal processes and contexts.
On the other hand, those who rely on self-learning bots face a completely different challenge. In this case, a sufficiently large amount of data must be prepared and processed from which the chatbot can feed its knowledge. For example, existing chat dialogs conducted by employees could be collected and analysed. In the post-processing phase, it would then be necessary to manually note whether the individual dialog steps are to be classified as correct or incorrect. In the next step, the algorithm can use the data generated in this way to learn how it should behave in comparable situations in the future.
If such a chatbot with automatically learned behavior is then used in practice, there is a chance that it will pull itself out of the swamp by its own hair – similar to the famous Münchhausen baron of lies. This means that the dialogs he conducts are saved and individual dialog steps are evaluated by employees in order to increase the database and improve the reliability of the bot. However, once the chatbot has insisted on always handling certain situations incorrectly, the learned misbehaviour cannot be prevented so easily – in contrast to the scripted version. Instead, the database must be enriched with examples of the desired behavior pattern until the bot changes its learned understanding of “right” and “wrong”.
Optimization of customer communication
But how can chat offers be used sensibly in customer communication? And how should their service be dosed? Regardless of the chosen variant, the question arises how to deal with misunderstandings and where the limits of the bot lie in communication. So when is the point reached where the chatbot can no longer solve a problem on its own, but has to hand it over to a human colleague?
While bots don’t know when to stop working and are generally available 24/7, human service staff are often not available around the clock. Therefore, it has to be decided whether the chatbot is only used when the handover to a human colleague is possible or whether the dialog is aborted outside service hours if necessary. In the latter case, the bot could refer to the service hours or initiate the arrangement of a personal appointment with an employee. The decisive factor for this decision is the extent to which the chatbot can cover self-services. If a reasonably complete portfolio of frequently used services can be achieved, round-the-clock operation seems to make sense.
In order to avoid misunderstandings, ambiguities and ambiguities in the dialog with the chatbot, there is the option to refrain from entering free text and instead provide the customer with a limited selection of answers. In this way, linear dialog can also be used to limit the response options of the bot – and thus the effort required by the operator. The selection options can be displayed in different formats. In addition, they can be enriched with graphical information – for example, product images – to visualize the various options.
In summary, the automation of the customer dialog is an extremely complex field of application in which it is necessary to analyse and weigh up in detail for what kind of requests a certain approach can be profitably implemented and used. Bots are one of several ways in which companies can efficiently handle one of the most difficult tasks in the business environment, namely communicating with customers. After careful analysis and taking into account the specifics described above, bots can become a decisive factor in optimizing customer communication. Their integration into the customer dialog leads to significant savings of two valuable resources: time and money. While previously stressed employees are relieved of routine tasks and gain new capacities, customers are happy to receive assistance that is as fast as it is uncomplicated.