Overview

Get Richer Insights into Operational Efficiency and Customer Sentiment

Aspect Engagement Analytics is a powerful speech and text analytics engine designed for quality analysts, business analysts and other advanced users to surface valuable insights into quality, operational efficiency and customer sat across all customer communication channels.

  • Compatible with all major voice and screen recorders
  • Categorize 100% of customer interactions (speech or text) against KPIs and capture sentiment
  • Rated #1 by Forrester for AI-Fueled Speech Analytics Solutions
  • Fastest speed-to-intelligence on the market means your organization will start seeing valuable benefits from day one

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Capabilities

Full-Transcription LVCSR Speech Technology

When you consider acquiring a new speech analytics system, you have two technologies from which to choose: Phonetic systems, or Large Vocabulary Continuous Speech Recognition (LVCSR), also known as Speech-to-Text or Full-Transcription.

  • Aspect Engagement Analytics uses the superior LVCSR technology which uses nearby words to establish context and eliminate ambiguity in word recognition
  • LVCSR provides higher speech recognition accuracy, faster searches and a full transcript, among other advantages

Organic Trend Discovery

Use the benefits of full transcription available with LVCSR technology to identify key issues that analysts would not otherwise know to look for.

  • Use AI techniques to recognize language patterns and surface findings without any analyst intervention
  • Automate the identification of important new topics for any set of conversations or parts of conversations
  • Apply cluster analysis by grouping similar sets or portions of conversations together to create word clouds

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Glossary

What is Engagement Analytics/Speech Analytics?

Until recently, contact centers have been unable to cost-effectively review customer interactions in large enough quantities to ensure better agent quality for all agents, nor could they easily spot operational issues that affected many agents. Most quality monitoring processes currently review only a small percentage of the total interactions that a company handles on a monthly basis. Such a small sample size can’t properly capture and identify the many quality issues faced by hundreds of agents. It would be cost prohibitive to manually review enough customer interactions to get an accurate view of agent performance.

Speech and text analytics uses modern technology to convert unstructured voice and text data into a structured form that can be analyzed using statistical and data manipulation tools. The challenge of converting a speech waveform recording of a customer interaction into usable data has been particularly challenging, but new techniques that examine word phonemes in the context of surrounding words have enabled speech recognition accuracy in the neighborhood of 95%.

This new technology enables contact centers to get a 360-degree view of conversations across channels. Each interaction can be automatically monitored for key phrases that are indicative of important conversational characteristics such as whether a proper greeting was used, agent empathy, politeness, customer dissatisfaction and many others. With that data, the contact center can easily identify individual agent quality issues as well as operational issues that exist across the contact center.