What is Engagement Analytics/Speech Analytics?
Until recently, contact centres have been unable to cost-effectively review customer interactions in large enough quantities to ensure better agent quality for all agents, nor could they easily spot operational issues that affected many agents. Most quality monitoring processes currently review only a small percentage of the total interactions that a company handles on a monthly basis. Such a small sample size can’t properly capture and identify the many quality issues faced by hundreds of agents. It would be cost prohibitive to manually review enough customer interactions to get an accurate view of agent performance.
Speech and text analytics uses modern technology to convert unstructured voice and text data into a structured form that can be analysed using statistical and data manipulation tools. The challenge of converting a speech waveform recording of a customer interaction into usable data has been particularly challenging, but new techniques that examine word phonemes in the context of surrounding words have enabled speech recognition accuracy in the neighborhood of 95%.
This new technology enables contact centres to get a 360-degree view of conversations across channels. Each interaction can be automatically monitored for key phrases that are indicative of important conversational characteristics such as whether a proper greeting was used, agent empathy, politeness, customer dissatisfaction and many others. With that data, the contact centre can easily identify individual agent quality issues as well as operational issues that exist across the contact centre.