With vast amounts of information about customers, interactions, agent performance, and more, contact center leaders often feel overwhelmed by the sheer volume of data at their fingertips. Within this data lie valuable insights that can help create differentiated customer experiences, identify root causes of issues, and uncover opportunities to reduce operational costs. However, Aberdeen’s research shows that only 35% of companies are fully satisfied with their ability to use data for CX programs.
To stand out from the competition, you must clearly understand how interactions flow through your contact center. Traditional analytics solutions rely on a rules-based approach to categorizing interaction data, which is time-consuming, complex, and often misses key insights. Additionally, to be effective, these solutions require continuous tuning by a skilled analyst. As a result, they fail to provide a complete picture of customer interactions.
NiCE Interaction Analytics significantly enhances productivity, improves analysis accuracy, and expands coverage by replacing manual analytic category building with the Topic AI Editor. This tool automatically classifies and quantifies interaction intents, events, and outcomes into a three-level hierarchy of categories, topics, and subtopics. By leveraging generative AI combined with pre-built, industry-specific intent and activity models—developed from 30 years of labeled CX datasets—Topic AI Editor enables fast and accurate analysis, saving valuable time.
Gain better insights with the following benefits:
Easy-to-Use, Guided Process: Automatically structure your data—no expertise required.
Drive Ongoing Value: Monitor topic frequency and correlate insights with key performance indicators (KPIs).
Increase Coverage: Utilize generative AI to analyze all interactions, delivering more comprehensive insights.
Reduce Manual Effort: Minimize time spent structuring interaction data, allowing more focus on acting upon valuable insights.
Improve Business Agility: Respond quickly to CX initiatives and improvement opportunities.
Customize Your Data: Align data structure with your organization’s processes and terminology.
