Using AI for UCC
Customer satisfaction is critical for a company to thrive on the market. However, the many interfaces and the flood of information make it difficult to communicate with customers.
Emma is a digital native. She thinks intuitively, makes decisions quickly, multitasks effectively and is mobile. Working? Whenever, wherever. Shopping? At the touch of a button while at home. A question or a complaint? A direct and quick response from customer services if you please. Too many contact persons and over-long waiting times and Emma changes service provider.
Companies sometimes find it hard to respond to customers like Emma and their requirements. Employees dealing directly with customers are often overwhelmed with inquiries and information. The customer service employee receives hundreds of e-mails and phone calls every day. Added to this are chat messages from work colleagues asking for information via private or business messaging services. Each incoming inquiry generates more information, and when this is stored in different locations, it makes processes more difficult and it becomes harder to retain an overview. Knowledge gets lost as a result, and employees are stressed and customers dissatisfied.
Companies can bundle different communication channels and systems with solutions from the field of Unified Communications & Collaboration (UCC). Customer service employees use their devices solely as an interface and have applications such as telephony, e-mail and instant messaging in one single tool. This makes customer communication simpler. They can receive and send instant messages via chat, deal with inquiries and solve problems. A video call can replace a personal consultation and save on time-consuming travel. And if somebody needs support from a colleague, the colleague can simply give them access to a document on their own screen.
Customers are increasingly using mobile devices to communicate and companies need to meet this requirement with applications such as instant messaging. So far, so good. Exchanging information with the customer faster also means that there is more information in the system. The amount of data grows apace, information gets lost, knowledge remains unused – a world away from the efficiency required. Artificial intelligence (AI for short) can help out here. AI analyses data, recognises previously undiscovered interrelations, learns as the process proceeds and generates solution proposals. A few examples:
The intelligent application “Marmo” searches for solutions automatically across sources in an existing infrastructure. For example, in customer services: The call agent types in a few key terms and the system starts searching automatically for similar inquiries from the past and makes a suggestion for a solution within seconds. The call agent evaluates the proposed solution, allowing the system to improve continuously. Customer enquiries are thus dealt with in a manner that is constantly becoming better, faster and more personalised.
Existing chats between the company and the customer are automatically analysed, and information is extracted. This information is used to create a chatbot that identifies the chat inquiries and decides whether the automatic chat itself can answer, or whether the customer needs to be connected to a consultant. Thus, the customer consultant only deals with inquiries for which he or she is actually required.
Efficient expert search
With the aid of application programming interfaces (API), chatbots can access self-learning knowledge systems such as Starmind. If a user is searching for an expert or specific knowledge with the chatbot, the bot accesses Starmind and forwards the information. This means that a customer consultant can answer questions faster and better.
Users can quickly find suitable appointments thanks to algorithms and access to calendar data. Intelligent systems such as the Meekan chatbot from Doodle or the digital assistant Amy from X.ai not only have a scheduler but also functions such as appointment surveys, appointment invitations and reminder notifications. Employees become more efficient and have more time for their core tasks.
AI can be married to a UCC solution if the latter is accessed from a public cloud. These so-called Workstream Collaboration solutions (which include Microsoft Teams, Circuit by Unify and Cisco Spark) can be further developed in an agile manner. This means that the technology manufacturers can quickly expand the functionality of the solutions, for example if the users need more or different services. This allows AI to be integrated in a Workstream Collaboration in a relatively simple way. Together with the centralised communication data, this has enormous potential with regard to customer interaction.
Employees who deal directly with customers no longer need to arduously analyse and organise information and generate solution proposals – thanks to an intelligent system this can be performed fully automatically within the cloud-based Workstream Collaboration solution.
And what about our customer Emma? She’s happy. She is getting the right solution quickly and directly from customer services. She feels she is being treated like a princess at such a company.
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