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Hitachi

Enterprise Application Services

Predicting the Future Based on Voice of the Customer (VoC)

Sentiment Analysis Service

Our Sentiment Analysis Service provides
a highly accurate visual representation of customers’ opinions and sentiments
about a company or a product, based on an analysis of text data.
We can analyze the data from a variety of media, such as social media,
customer reviews, mass media including newspapers and television,
and business data from questionnaires and call centers.

And then supporting future planning activities like sales forecasting.

Features of the Service

Accurate Analysis

The service utilizes an AI technology that can analyze Japanese-language text and classify the text data based on approximately 1,300 topics, sentiments, and intentions. The data is classified into three major categories (Positive, Neutral, and Negative) and then further classified as representing one of a total of 81 feelings.
The service can also analyze other languages like English, Thai, and Chinese by using a sentiment dictionary that can be customized to suit your business operations.

Insightful Viewer

This service tags not only information about customer sentiment, but also information about relationships between words. This allows you to search for specific topics as well as particular words. In addition, the search viewer gives insights by analyzing text data in combination with business data, and provides an interactive user interface.

Easy Maintenance

Through the machine learning of highly relevant words and technical terms contained in collected data, the AI automatically updates the refining conditions used for the filtering dictionary. This makes it possible to maintain and improve the accuracy of search refinement without additional maintenance work.

01

Product planning to comprehensively meet market needs

category :
  • Planning
  • Development

Perform sentiment analysis of data that includes both business data, such as product functions and performance, and information from social media. Based on customer complaints about the product, this analysis clarifies areas in need of improvement, which allows you to identify customer needs. This, in turn, enables you to perform product planning in a way that comprehensively meets market needs, thereby contributing to your efforts to increase sales and reduce lost opportunities.

e.g.
Analysis of data for vacuum cleaner planning

Analysis for vacuum cleaner planning : [Business Data、Social Media]→[Sentiment Analysis]→[Positive, Negative, Neutral]→[Negative : noise, storage, stock, color, dust, stand、air, How to empty dust container]→[How to empty ust container : ]→[Needs Identification]→[Product planning to improve the usability]→[Sales expansion. Opportunity loss prevention]

02

Implementation of prompt measures against risks, such as social media flaming and recall

category :
  • Public Relations
  • Publicity
  • Sales
  • Quality Assurance
  • Call Center

Perform sentiment analysis of data that includes both business data (such as product specifications and information about the state of business when the product was released) and information from social media. This enables you to detect negative feelings about the product before they spread, and to identify words that indicate risks. This helps you to improve your brand image by promptly implementing measures against the risk, such as preventing accidents that may be caused by defects in the product or announcing a recall.

e.g.
Implementing measures against risks related to a washer/dryer

e.g.Measures against risks related to a washing machine

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