Future of Work News

AI System Solves Customer Information Overload

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Data is king. That’s a simple fact is today’s business environment. Data collection is one of the most valuable aspects for any company as they look to improve customer experiences and communications – and for good reason. Customer service improvements, advertising models, and personal recommendations are just a few examples of how data plays into the development of business strategy. The information can be used in an endless number of ways to help companies better understand their customers.

But, what good is data if it can’t be sorted out? Why bother collecting data if it’s unusable? Most companies have no problem collecting data, but figuring out how to effectively use it is where things are getting tricky. 

To help solve that issue, Hitachi, a leader in the field of AI business solutions, has recently partnered with Allganize, an AI company focusing on search automation, to create solutions for sorting and searching through valuable customer data for businesses.

“The initiative provides a powerful arsenal of enterprise-level tools that help businesses increase productivity by integrating information and communication, RPA and more,” said Changsu Lee, CEO of Allganize.  “We look forward to bringing AI strategies to life with our expertise.”

Both companies believe that, by combining their expertise, they can use their artificial intelligence system to organize business data into a cleaner, easy-to-use format. The new system is called “Business Efficiency Solution by Natural Language Processing (NLP) AI.”

The following are solutions that the new AI software can implement to help businesses with their data:

  • Katsubun Intellectual Information Mining analyzes clients’ operational processes and enables them to identify bottlenecks for process improvement.
  • Alli AnswerBot streamlines customer service and automates business processes.
  • Cognitive Search enriches and extracts structured knowledge from unstructured data sources to make content more searchable.
  • Named Entity Recognition (NER) locates and classifies named entities such as brand names, people, product names, purchase order and account information from unstructured data sources.
  • Review Analysis automatically converts opinions such as user feedback and reviews into measurable data for analysis.
  • Text Classification assigns custom predefined categories to free-text for managing content. 
  • Sentiment Analysis is an emotional AI that categorizes text by emotional state such as happy, angry or sad.
     

Along with these features, what makes this combined system exceptional is the simplicity of its integration. Because of the advanced nature of the AI, businesses do not have to concern themselves with manually tagging data. The system is able to take raw data and sort it automatically, dramatically cutting down time for businesses to get results. The NLP AI system also speeds up customer inquiries with Allganize reporting it can automatically resolve 50-80% of customers’ questions and free up  time to handle four to five times more high priority issues. The partnership of Hitachi and Allganize could be a giant leap forward for data automation, with both customers and businesses reaping the benefits.




Edited by Erik Linask

Future of Work Contributor

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