Natural Language Processing is more and more popular. However, not all of businesses are aware of how natural language processing is being applied and whether it is appropriate for their business model. So today VNLP will share with you all the applications of Vietnamese natural language processing (VNLP)!
1. Enterprise Chatbot
Chatbot keyword today is almost everywhere from fanpage to website with many thousands of names according to the products of the business.With consulting service, 24/7 feedback, keyword chatbot is a care assistant effective customers for the business. A good customer service will help create a good impression for the company to increase sales.
But with chatbots appearing in too many places, users are becoming more and more difficult to ask for more accurate responses. And the Chatbot keyword, though really useful, still has drawbacks such as:
- Only answer right in case customers ask the right keyword.
- The second thing is that if the sales / consulting scenario is not good, the chatbot will become silly.
In an environment where nearly every business is capable of creating chatbots, a smarter chatbot with more accurate answers will create competitive advantages for the business.
Chatbot built on the foundation of VNLP was the solution to overcome all limitations of keyword chatbot. By being trained to handle human natural language, chatbot AI is able to understand users’ intent through speech and give accurate feedback without having to set up a keyword. Currently VNLP provides both specialized chatbot-building services by industry / business and NLP training platform to help improve the quality of chatbot keyword of the current business.
2. Auto Agent Evaluation
The quality of a call center is highly dependent on the staff (Agent). Assessing the competence of call center staff becomes important in ensuring the quality of the call center as well as improving the customer experience. However, due to too many calls, the evaluation becomes more difficult and the results are likely to be inaccurate because sometimes reviewers are dominated by personal feelings. The unfair assessment easily makes employees angry, affecting the quality of the call center.
VNLP’s automatic call center evaluation system allows to assess agent competence through grading based on specific standards or a combination of criteria to provide appropriate scoring.
The system also supports a number of features such as converting speech into text through Speech To Text technology, automatically monitoring performance, marking errors and alerting management to solve promptly. It’s time for businesses to choose a more optimal solution, and VNLP’s automated call center evaluation system may be an appropriate option.
3. Social Listening
In the era of rising competition, listening to customers on social channels to capture trends that target customers are interested in and conduct appropriate marketing campaigns is considered extremely necessary. However, analyzing thousands of thousands of customers comments on fanpage, website … has never been easy. Not to mention the analysis results will be less accurate because there is too much junk data and spam.
The limitations of the old Social Listening system will no longer be a concern for VNLP’s natural language processing technology:
- Filter junk / spam data: optimize data quality, increase processing performance and accuracy of analysis results.
- Intent / Entity / Sentiment Analysis: Detects and notices abnormalities, problems, and scandals that businesses may encounter.
- Insight Extraction, automated reporting: through Entity Classification, the system recognizes frequently mentioned topics and is shaping the trend of the social community.
VNLP provides natural language processing for the current Social Listening system.
Helpdesk is an service support department, Helpdesk has a role to provide information and support services to handle internal and customer requests. Helpdesk is currently used in many businesses have Customer Service. Helpdesk software will help businesses solve customer requests more effectively through the Ticket management system. However, if the ticket volume is too large, it will lead to problems such as:
- Staff are unable to handle all customer requests
- Unrecognized requests are prioritized for processing.
- Distributed to specialize staff.
- Spend a lot of time processing repetitive problems.
VNLP system with pure Vietnamese natural language processing technology can help the enterprise Helpdesk system with features such as:
- Automatically analyze requests with Vietnamese NLP then classify and prioritize requests with VNLP Sentiment Analytics.
- Automatically route customer requests to employees with the right expertise.
- Support quick response to customer requests.
Do not let customers turn away from your business to find better services. Let prepare the tools to bring customers the best quality service.
5. Document Management System
Many businesses are having a headache finding information among tens of thousands of printed and archived documents. Besides, not controlling printing activities of enterprises will lead to wasting printing paper.
Businesses can completely save up to 80% of the time looking for documents and tightly control printing activities in the business with Document Management System of VNLP.
Some features of VNLP Document Management system can be listed as:
- Content analysis: NLP and AI applications in text content analysis.
- Content summary: extract important content to help manage and support quick access.
- Additional content: allows access to online documents, additional information, code without the original file.
- Content Classification: Classify text by main content, help organize and extract easily and quickly.
- Subject encoding: convert topics into QR codes / barcodes for managing, extracting data / printing documents.
VNLP Document Management system can connect with existing physical printers of the enterprise to use the above features. Highly applicable for most businesses that regularly print and store document in large volumes.