I’ve heard of speech analytics to analyze phone calls; what’s used for the new digital channels?
Interaction analytics (IA), which combines speech and text analytics capabilities, enables enterprises to gain insights from both voice and digital channels. IA solutions convert unstructured recorded and/or live-stream audio and digital customer conversations into transcripts. Once transcribed, structured output files can be categorized, filtered, searched and analyzed. These solutions extract business intelligence from omni-channel interactions and report on what is happening throughout the enterprise. IA enables companies to better understand customer needs, wants, trends and opportunities, as well as measure and quantify the impact of enterprise actions on their customers and prospects. These solutions can also discern nuances in customer communications, including emotion, sentiment, intent and more.
Interaction analytics solutions range from basic (e.g., key word/phrase spotting) to feature-rich, robust platforms. Leading applications capture and analyze omni-channel voice and text-based interactions, and automatically provide previously unknown insights to contact center and enterprise managers. Common IA capabilities include recording, speaker-separated analysis, talk/silence analysis, categorization, transcription, search, and emotion detection. While these are typically “standard” functionalities, prospects should be aware that even common features can differ from one IA solution to another. For example, recording may include audio-only or audio and screen recording; speaker-separated analysis may be available for mono and stereo recordings or only stereo sources; and emotion detection may be based solely on linguistics or be combined with acoustic events as well. More sophisticated IA functionality can vary even more, as artificial intelligence technologies are increasingly used to enhance advanced capabilities.