Overview

OpenText™ Contact Center Analytics is a voice of the customer (VOC) analytics solution that allows organizations to collectively view cross-channel interactions for insights into customer behaviors, sentiments and relationships.

How OpenText Contact Center Analytics can benefit business

Listen, analyze, act

Uncover opportunities, streamline processes and alleviate bottlenecks with Voice of the Customer analysis of interactions across touchpoints.

Personalize customer experiences

Understand and respond to individual customer experiences based on multi-channel insights.

Action big data

Leverage data at every level of decision-making to enhance service and fuel strategic decisions.

Visualize customer insights

Identify trends and isolate errors using easy-to-understand visualizations and comprehensive dashboards.

Enhance the customer experience

Employ AI to automatically analyze clustered conversational data at scale for visibility into cross-channel interactions.

Improve customer satisfaction

Discover themes across customer contact services or agent engagements and take corrective actions to better respond to customer needs.

Why OpenText Contact Center Analytics?

Multi-language solution

Leverage an industry leading speech engine with support for more than 40 languages and dialects to listen to the worldwide customer voice.

Extend CCaaS capabilities

Integrate AI-driven analytics with leading Contact Center as a Service (CCaaS) providers to analyze recorded customer voice experiences and drive engagement.

Accurate voice transcription

Receive high-quality caller transcriptions to run scalable speech analytics for insights that help drive operational improvements.

Comprehensive Quality Assurance

A complete toolset of cost-effective VOC tools, including AI-powered Quality Assurance analytics.

Key features

Voice of the Customer surveys

Captures important customer feedback with interactive surveys sent directly to customers’ mobile devices.

Speech analytics

Accounts for speech variables, such as language, dialect, accent or emotion, to form a contextual hypothesis of the content.

Text analytics

Provides insight into text-based communications, including open-end verbatim and CRM notes, with automatic classification and categorization of the content based on meaning, not keywords.

Autoscore interactions

Leverages agent and customer behavior scoring models to automatically define and calibrate every call.

Artificial Intelligence

Utilizes artificial intelligence to summarize and classify calls, detect sentiment and identify breaking topics.

Social media analytics

Integrates social media data to identify trends and prevailing sentiments with URL expansion/matching, format normalization, language detection and GEO-IP.