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Enhancing Customer Acquisition/Retention and Improving Sales Promotions

NEC's advanced customer analysis solutions analyze customer relations in real time to provide effective feedback and maintain optimal, up-to-date data for improving customer satisfaction.

Voice of Customer (VoC) Analysis

Features

NEC's original Recognizing Textual Entailment Technology automatically classifies and organizes customer feedback to enable better customer satisfaction and promote service innovations.

NEC's original Recognizing Textual Entailment Technology analyzes massive amounts of text such as feedback in questionnaires and SNS word-of-mouth communications and extracts, organizes, and classifies information according to meaning, irrespective of forms of expression. This technology aggregates and quantifies free-form texts to enable efficient, high-performance analysis and knowledge discovery.

Customer needs

  • To understand client feedback in detail so as to improve customer satisfaction.
  • To analyze sales reports to discover real customer needs.

Key benefits

  • Precisely extract and classify the meanings of huge amounts of text generated every day.
  • Raise customer satisfaction by utilizing customer feedback for improving products and services.
  • Constantly monitor for potential issues to enable thorough risk management and quality control.

Key technologies

Rapidly searching for text containing similar meanings in vast amounts of data

Related cases

Sumitomo Mitsui Banking Corporation

This solution instantaneously analyzes and visually represents a huge amount of customer feedback, allowing the bank to implement activities to improve customer satisfaction that exceed expectations.

Voice of Customer (VoC) Analysis (call analysis)

NEC combines voice/emotion recognition and text analysis technologies to analyze not only service memos but also conversations with customers so customer needs can be effectively met and customer relations issues resolved.

Human Resources Matching

Features

Applicants matching specific criteria can be quickly pinpointed by identifying regularities in massive amounts of varying recruitment and human resources data.

Not only numeric data but also text and images are used to learn patterns relating to job offers and applicants and generate a "match score" between a company and an applicant in real time, allowing recruitment and human resources processes to be streamlined.

Customer needs

To find applicants matching job requirements from massive amounts of data.
To streamline recruitment processes while identifying all talented applicants.

Key benefits

  • Target applicants are extracted based on past recruitment and human resources data so that no talented applicants are overlooked.
  • Recruitment is streamlined by allowing hiring managers to focus initially on the most suitable applicants.
  • Ideal matches can be found in real time.

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