Semantic Intelligence (Si)

Speech Analytics Product that analyzes ongoing changes in customer behavior through spoken interactions with the customer, and drives effective organizational changes needed to address challenging market conditions. goes beyond surfacing and analyzing just words and phrases. By leveraging Semantic Intelligence, a new and innovative technology, Speech Analytics surfaces key concepts and relations Two terms found in close proximity to each other in one interaction, used in Speech and Text Analytics. that represent the main ideas and processes discussed in interactions.

These expressions are more meaningful and clearly point to specific topics discussed in customer-employee interactions.

Because you can discuss similar topics in different ways, Semantic Intelligence groups relations and concepts that have similar meaning into themes Groups of expressions used in Speech and Text Analytics that help users understand what is happening in their calls, without the need to know what to look for in advance.. Themes include items that convey higher-level concepts. Themes help users to drill down to interactions that convey significant issues, or create a category Grouping of calls in Speech Analytics that pertain to specific business issues among all transcribed interactions. for deeper analysis and longer term One to five words that are meaningful to a specific type of business, or phrases that stand out in interactions in Speech and Text Analytics. monitoring.

Themes represent interactions that contain the same:

Relations: two terms that are used close to each other and that convey a concept that is meaningful for your business. For example, an action on a business object, or the status of that object. For example, cancel > internet-service, or internet-service > canceled.
Concepts: terms that are meaningful to a specific type of business or phrases that stand out in the interactions.

Speech Analytics continuously analyzes your data and surfaces new concepts and relations. This process ensures that themes are up-to-date and relevant to the current data set.