Record the entire call content. Semantic context recognition automatically

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What is easier to do is the analysis of standardized data such as call volume, satisfaction rate, the proportion of each fixed category, and the proportion of each undertaking unit; the difficulty lies in the analysis of non-standardized data, such as which companies and which companies are mainly concentrated in the classification of arrears of wages. Industry; a certain town or street reflects which category of problems, etc. What kind of product manager is needed on the B-side? B-side product managers are all aiming to improve the work efficiency of the supply side, so B-side needs are mainly oriented to business issues. This is a more important point of B-end products.


B-end products serve one subject. View details > This type of analysis usually relies on manual help. After fixed classification and screening, manual judgment is performed to assist with labeling and statistics again, which requires a huge amount of manual work. The formation of a regular monthly report often  Brazil Email List requires business staff to prepare for a week. Citizen hotline data digitization needs After understanding the hotline business process and pain points, what are Party A’s needs? What do you want to do? How to make use of such rich data assets? How to solve Party A’s pain points? First of all, a stable and flexible hotline reception system is very important to the entire hotline business. How to use the system to flexibly and accurately record and standardize non-standardized demand data? Standardized data is an important prerequisite for data analysis applications.



Answering: Intelligent customer service Intelligent customer service introduces filtering of consultation, routine, and knowledge base categories that are not handled manually to take on part of the hotline pressure. Instant text conversion: With natural language processing as the core module, text conversion, semantic judgment, and automatic content extraction tools realize instant text conversion of the caller's verbal expression. identifies the caller's basic information and automatically extracts key fields based on further inquiries based on the information for further filtering, editing, and selection by the operator, greatly improving the operator's classification efficiency. Identify the semantics and context of the caller and automatically provide the operator with real-time speaking instructions to reduce communication costs and work pressure.