With a massive amount of information about customers, interactions, agent performance and more, contact center leaders are often overwhelmed by the amount of sheer volume of data at their fingertips. Within this information lie valuable insights that help create differentiated customer experiences, identify root causes of issues, and uncover opportunities to reduce operational costs. Yet, Aberdeen’s research shows only 35% of companies are fully satisfied with their ability to use data for CX programs.
To stand out from the competition, you must have a clear understanding of how all interactions flow through your contact center. However, traditional analytics solutions use a rules-based approach to categorizing interaction data which is time consuming, complex, and often misses key insights. And to be effective, it requires continuous tuning by skilled analyst. As a result, it fails to provide a complete picture of your interactions.
NICE Interaction Analytics significantly increases productivity, analysis accuracy, and coverage by replacing manual analytic category building with Ontology Studio. It automatically classifies and quantifies interaction intents, events, and outcomes into a three-level hierarchy of categories, topics, and subtopics. By leveraging Gen AI combined with pre-built, industry-specific intent and activity models derived from 30 years of labeled CX datasets, Ontology Studio ensures fast analysis, saving valuable time.
