The assembly line was a great idea! But it was automation that made it human-friendly: Artificial intelligence frees employees from monotonous tasks and processes and creates free capacity for more challenging tasks. Optimized processes first increase employee satisfaction, then the quality of the work performed – and finally your business success.
Repetitive processes require little intelligence, but a lot of time. Do not slow down your employees unnecessarily: State-of-the-art technology can already handle a large proportion of repetitive tasks today.
Bots communicate across all channels, for example via phone, email or chat. No matter on which channel you want to automate your customer dialog – we help you! You decide which tasks the bot shall handle and to what extent it shall support its human colleagues.
Our web-based monitoring shows you, clearly and in real time, the availability and workload of your Contact Center – and provides access to daily data of your system.
All statistical data on the workload and operation of your Contact Center is collected in regular reports. The advantage: detailed insights into service quality and resource usage. The perfect basis for quickly optimizing existing processes – and achieving your goals.
Bots based on deep learning algorithms make intelligent connections and take Artificial Intelligence to the next level. We show how it’s done!Read now
With the help of chat and voice bots, you can save time and money in customer dialog, increase the availability of customer service, and reduce the workload of your employees. At the same time, you achieve higher customer satisfaction thanks to shorter waiting times.
Bots communicate on all channels. No matter on which channel you want to automate your customer dialog – we provide you with a customized solution: On premises or from the cloud!
The use of bots reduces the average call duration of your service center agents. In addition, the call forwarding rate decreases. Your employees no longer have to do monotonous work and can focus on value-added tasks.
Chat and voice bots provide a cost-effective 24/7 service. The bots communicate on all channels and are available around the clock. If required, they are even capable of proactively contacting your customers.
Chat and voice bots take over part of the customer dialog and are highly efficient in doing so. They store all important information, find the right contact person for each customer, and easily handle heavy workloads.
Customers are friendly greeted by bots, receive quick assistance, and do not have to repeat their concerns several times. Thanks to the short waiting times and direct access to standardized information, customer happiness increases significantly.
You want to set up a chatbot or a voice portal – or even both? With our Dynamic Dialog, we automate your customer communication. Completely customized according to your requirements. By combining our technology and expertise with suitable third-party and partner solutions, we achieve the optimal result for you.
Microsoft voice recognition enables voice-driven interaction between your customers and your applications. The Microsoft solution recognizes spoken words and generates artificial speech (text-to-speech). In addition, Microsoft voice recognition enables you to achieve the goal of digital accessibility.
Nuance Recognizer enables seamless self-service and optimizes your customer experience. The integrated engine understands and processes natural dialogic speech. The Recognizer learns from mistakes and thus works more and more accurately over time.
Sympalog’s SymDialog5 can control different types of dialogs: as an IVR application, as a chatbot or as a dialog-oriented backend module to control applications. The module combines intelligent and user-friendly dialog control with knowledge from your backend systems.
aiaibot offers a cloud-based, easy-to-integrate chatbot. The platform features an intuitive story builder that allows for both guided dialogs and open-ended questions. The story builder also allows integration of images, GIFs, videos, file uploads and polls. This way, the easy-to-manage chatbot can be customized according to your needs.
The new voice portal reduces the workload for Signal Iduna employees, lowers internal forwarding rates and shortens waiting times for callers.Learn more
By automation, we mean the independent handling of various tasks or processes by IT solutions. The need for human intervention is thereby limited as far as possible or eliminated completely. Depending on the degree of automation, we speak of partially or fully automated solutions. Automation serves to accelerate certain work processes, increase productivity and minimize sources of error.
The advantages for your company are obvious. But your employees also benefit from automation solutions. Since repetitive manual processes are particularly suitable for automation, your employees are relieved of recurring standard tasks. As a result, they gain time and can focus on activities that require more attention. And because colleagues who are challenged more enjoy their work, their working atmosphere automatically improves as well.
In principle, automation is an option in numerous application areas in the IT sector. In the Contact Center environment, for example, the routing of contacts and the distribution of work are automated. If, for example, the machine takes over the query of basic data for each caller and connects them quickly and accurately with the right contact person, the service employees have more time for the qualitative consultation. The internal transfer rate drops, and caller satisfaction increases.
Until today, the term “Artificial Intelligence” has been associated with all kinds of vague ideas about what AI can and cannot do. Yet the technology has long been an integral part of our everyday lives. However, we usually associate AI with complex machines or human-like robots and ignore the fact that the technology can also be found in small applications and tools. In other words, we use a variety of AI-based applications and services without even realizing it. Every day, smart voice assistants read all our wishes from our lips, web stores suggest suitable products, thanks to sophisticated algorithms, our cars maneuver themselves into the smallest parking spaces, and our inquiries on various websites are answered by friendly chatbots.
The majority of such supporting systems are mostly rule-based and are limited to a clearly defined area of application. However, AI can do much more. So-called deep learning algorithms are able to independently link learned content with new content due to a large information base and the structure of neural networks. In addition, they make analogies without being confronted with certain key terms in the context of a question. In other words, they can “think around corners.” The more relevant data such systems process, the more reliable they become. In this way, the “learning effect” ideally leads to continuous self-optimization.
Companies can benefit significantly from the use of Artificial Intelligence. In the Contact Center environment, part of the customer communication can be automated with the help of artificially intelligent systems. Thanks to deep learning methods, even relatively flexible dialog guidance is possible. In production control, processes can be automated with the help of artificially intelligent solutions.
Most artificially intelligent systems we currently see are based on the principle of machine learning. The aim of this method is to recognize correlations or patterns by intelligently linking or statistically evaluating data in order to derive conclusions or make forecasts. To do this, the learning machine must be provided with a sufficiently large database. In addition, it must be enabled to process this data by programming special algorithms. This means that human action is necessary before the machine can develop its Artificial Intelligence.
Deep learning is in turn a subarea or a further development of machine learning. It is based on artificial neural networks whose structure and function are modeled on the neurons of the human brain. Thanks to a large information base and the structure of the neuronal networks, a system based on Deep Learning should be able to link learned content with new content independently and, in the long term, across different areas. In this way, new learning processes are to be continuously initiated. The goal is that the machine does not simply learn, but that it learns to learn. In theory, human intervention in the learning process is no longer mandatory.
For example, a deep learning-based voice bot does not need to think through all potential dialog paths in advance and take into account the entire range of customer formulations. The bot simply needs a sufficient database to be able to work completely independently.
The concern that jobs will be lost as a result of automation is widespread. After all, activities that were previously performed by humans are now being carried out by machines. In fact, however, the technology behind the bots is miles away from making humans unnecessary. And apart from that, it is not even aimed at replacing them completely. In the Contact Center environment, automation is only intended to relieve human employees, but by no means to replace them.
For example, voice bots are not used to avoid customer meetings with employees, but to prepare them in the best possible way. As soon as the bot hands over a contact to the employee, it provides him or her with the previously queried information. In practice, it has been shown that chatbots only develop their full effect in customer dialog in interaction with human agents. In the ideal case, humans and machines go hand in hand thanks to a sensible division of tasks.
Once the concerns and reservations have been overcome, voice and chatbots enjoy great popularity with their human colleagues. No wonder, after all, the machine helpers in the service center take over a large part of the tedious and monotonous routine tasks.
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