Write your customers something personal

Any time a customer gets in contact with a company is a valuable opportunity for that company to check whether the quality of service it advertises in its marketing matches the service that it actually delivers. Companies invest large sums of money into meeting customer expectations in terms of individual communication. This is because the customer service department is the main advertisement for your company and the starting point for your customers. Handling queries quickly and to the satisfaction of customers is a time and labour-intensive task. In the worst-case scenario, your employees even get side-tracked from their primary day-to-day tasks because they have to handle incoming correspondence. Instead of getting on with their professional activities, they are reading texts, working out what the customer’s issue is and delegating the resulting tasks to the relevant colleagues, who then in turn take over communication with the customer and come up with the appropriate response.

A system supported by AI can automate a large part of this communication process. The software first analyses incoming messages from various sources. It automatically detects important metadata such as sender information, customer or invoice numbers and uses it to categorise the information. The application identifies the content of the communication as the decisive factor: What issues is the sender raising? What answers are they looking for? The application finds the factually accurate elements in a company-specific database using this text analysis and autonomously creates personalised replies.

The choice and quality of the answer elements defines the overall quality of the answers generated in this manner. A team of customer service employees continually maintains and expands this data pool. The team uses their expertise to effectively optimise the quality of service across every channel instead of dealing with individual cases.

Customers and potential customers receive informative and factually accurate answers to their queries and the processing time for them is shorter than ever. Consistent communication is ensured across every channel thanks to centrally managed answer elements. The self-learning system continually improves the accuracy of the answers in the background, which in turn improves the quality of them.