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RESEARCH
collected from the customer and data from similar Sentiment analysis: AI can ANALYSIS
customers, it is possible to determine the probabilities help to assess the mood of TRENDS
of how successful the respective measure will be. In the customer, for example
combination, you can contact customers long before whether he is angry or in
they decide to bail out of a purchase or bind them to the mood to buy. The AI-
the company with the right offer or the right strategy. based sentiment analysis,
for example, can be used
Certainly, not every customer inquiry has to be dealt excellently in the field of
with immediately, but there are requests for which chatbots. It can be used to
every second counts to prevent a bail out or a negative identify whether a customer
experience. With the help of AI, the ticket system can has problems interacting in the chat. This also makes it
learn which requests (from which customers) need to possible to determine the optimum point in time at
be classified as more urgent than others. The which a call center employee should take over
employees in this case do not work chronologically and communication.
thus risk that an important case must wait longer but
can work on the cases according to priority and Predictive customer service: AI can help identify
urgency. problems and concerns of customers before they even
contact customer service - for example, a DSL
With the use of AI in customer service, companies aim customer who has not had an Internet connection for
to achieve an optimized customer experience across several hours is very likely to contact technical
channels in real time. Above all, AI technologies are an customer service in a timely manner.
important tool for merging different touchpoints quickly
and easily in an integrative approach. Intelligent routing: AI can also help optimize the
distribution of customer inquiries in the call center and
Application scenarios that can be implemented in customer service and helps in the classification of the
customer service using AI and machine learning concern and the identification of the most appropriate
methods include: service employee - for example in terms of expertise or

availability.
Realtime ‘next best action’: based on predictive
analysis and machine learning, AI engines can However, a typical obstacle to a consistently positive
automatically suggest the “next best action”. An optimal
solution not only evaluates historical data, but also customer experience is customer data that gets stuck
in data silos. Here AI can help to clear the complexity of
takes into account contextual information that arises at
the moment of the specific interaction - for example the the data or measure customer interactions, recognize
reason for a customer call to the call center or the time behavioral patterns, and then evaluate them. The
results obtained can then be made available to
during which he was on hold. Since AI predicts the
current needs of each individual customer across employees in marketing, sales, or service across all
communication channels. This enables a 360-degree
channels, it can make a decisive contribution to cross-
selling or up-selling. It is important that the system view of the customers and provides them with a basis
reacts in real time: if the customer rejects the cross- for personalized offers with a positive effect on the
customer experience.
selling offer, for example, the system should
immediately submit an alternative proposal. But one thing remains certain: a high-quality and
personalized customer experience is not possible
Automated dialogues: AI-based text analytics helps
answering customer questions in chat rooms or email. without human involvement. Against this background,
With chatbots, i.e. through dialogues automated with the path to success for companies is not to replace
employees with AI, but to train them in such a way that
algorithms, answers can be found automatically for a
large number of customer questions - possibly even they understand their own key role within the customer
journey. ◊
better than those provided by the call center staff.
However, clearly defined tasks should be defined for By Daniela La Marca
chatbots; in principle, they are most efficient when they
address a defined topic.

5 November 2020: voice search & digital voice assistants as storyteller