Text and speech analytics are technical tools that leverage artificial intelligence, such as natural language processing, to understand human speech and identify patterns, like frequent occurrences of keywords and phrases. Text and speech analytics, sometimes referred to as interaction analytics, can rapidly analyze huge amounts of data to provide users with real-time or near real-time insights.
Text and speech analytics are commonly used in contact centers to analyze customer service interactions. Voice recordings are transcribed and digital interactions are recorded, after which text and speech analytics software combs through 100% of the contact data from every channel (including phone, chat, email, text (SMS), and social media). Interaction analytics can provide valuable insights, including:
These insights allow contact centers to provide more proactive customer experiences, know their customers better, quickly address new problems, and gain a more comprehensive view of interaction quality. The information produced by text and speech analytics can also be used to identify targeted training opportunities. And when that information is combined with other customer feedback, such as survey scores, organizations get a more holistic voice of the customer (VOC).
Text and speech analytics tools can also determine customer sentiment based on keywords and conversational characteristics such as voice volume and pitch. Knowing customer sentiment allows contact centers to take closed-loop actions with dissatisfied customers to try to rescue the relationships. Additionally, agents can be measured and rewarded on their customer sentiment scores.
The best text and speech analytics tools are cloud-based, for maximum flexibility, and don’t require a data science degree to use or understand their output.
