There’s only one affordable way to provide truly global customer support in many languages: deploy a Multilingual Knowledge System (MKS) to access your (primarily monolingual) knowledge base and use the MKS as an information infrastructure for the process and its tools.
The requirements list for global customer support is long. In fact, a product for real global customer support is yet to be built. The solution architecture below illustrates how it can be done, however. The chart shows the data flow, the different building blocks, and how an MKS makes them work multilingually.
Listen and Speak to Your Customer
In the support section of your website, customers often describe their problems in their mother tongue. Younger customers in particular might instead simply write about their issues on social media. Mobile customers want to use either voice or chat to communicate with support. No matter how a customer contacts you, they expect to be answered via the same channel, and in the same language.
Cross-Language Semantic Search
The textual data (in the case of a voice interaction, this can be acquired through automatic speech recognition) must be tokenized for the following analytics into words, numbers, special characters, etc. Named entities, measurements, product names, corporate terminology, etc. need to be marked. When retrieved from social media, text analytics decides how the information has to be further processed. Ideally the author and customer can be identified in the structured customer data. Advanced Linguistic Search (ALS) then finds the relevant information in the Knowledge Base. ALS, combined with a Knowledge System, searches semantically; combined with a MKS it can also search cross-language.
One Corporate Language, Many Customer Languages
A Multilingual Knowledge System enables companies to retrieve knowledge from many languages. On top of Advanced Linguistic Search and MKS, an analytic component can answer questions. Only ontology/taxonomy combined with advanced search provides the intelligent responses that customers and agents need. Machine Translation is used when the solution, a question, or dialogue is passed back to the customer in their language.
Support the Support Agent
In many standard cases a Question & Answering System can detect that crucial information is missing. It then formulates the respective questions. A dialogue system is customized with domain and company-specific templated dialogues. It can talk with the customer. Today’s maturity level of speech technologies, natural language processing, artificial intelligence, dialogue systems, machine translation, and text analytics cannot handle all situations without human intervention. Luckily, it knows when it needs help. It then simply hands the case over to a human agent. By that point, however, most standard stuff is already dealt with. The agent has all the relevant information at hand and can focus on solving the customer’s issue.
MKS, Information Infrastructure for Customer Support
A Multilingual Knowledge System is the central information infrastructure for a global customer support solution. The product knowledge stored in the MKS is used to customize speech recognition, voice generation, NLP, text analysis, and dialogue systems. It tunes the Machine Translation and provides the multilingual terms and knowledge for the semantic cross-language search in the Knowledge Base.
In order to enhance the company’s Knowledge Base, multilingual Text Analytics combined with the intelligence of the MKS provides quantified information about a product and process defects reported in different languages on any media. This helps Product Management to prioritize features or even come up with new ones. It supports Marketing departments in positioning new product capabilities and understanding customer use cases. For all customers, globally!
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