Contact centre analytics involve collecting and analysing data related to agent performance, customer experience, operations, and more within a contact centre. These analytics encompass various metrics and tools, such as agent KPIs, customer satisfaction scores, predictive analytics, and real-time monitoring.

Different types of contact centre analytics

Contact centre analytics provide insights not just into what is happening in the contact centre but also what you can expect to happen next. Here are the different types of contact centre analytics and their uses.

Advanced Analytics

Advanced analytics, including AI and machine learning, are increasingly utilised to gain deeper insights from contact centre data.

Predictive Analytics

Predictive analytics helps in identifying and solving problems that can potentially happen in the future. For instance, predictive analytics can help you determine the number of people required to handle call volumes during the holiday season

Voice Analytics

Voice analytics analyses the audio for parameters, such as tone, pitch, stress, and rhythm, of both the caller and the agent and is a necessity for contact centre managers.
Voice analytics gives them the necessary tools to predict in real time if a call is progressing in an undesirable way. 

Speech Analytics

Speech analytics focuses on the words used in a conversation. Using artificial intelligence (AI) and machine learning (ML) techniques, speech analytics tools can identify the key phrases and words used during the conversation. This helps gain customer experience insights and understand customer sentiment trends.

Customer Satisfaction Analytics

Almost all contact centres send out customer satisfaction surveys immediately after a call has ended. The very fact of whether the customer fills out the survey or not provides valuable information about customer satisfaction levels. An expertly designed customer satisfaction survey can be used to gain further insights into product performance, agent performance, and customer experience.

Interaction Analytics

Every customer interaction is an opportunity to understand your customer better so that you expand not just your customer base but also understand how to reach out to them.
Customer interaction analytics offer insights into customer behaviour, their unique needs, and brand expectations.

Omnichannel Analytics

Any customer that contacts your contact centre may already have interacted with the brand via other channels, such as social media, email, or self-serve portal. Having omnichannel analytics data helps agents provide a highly customised experience to the callers, improving contact handling times as well as customer satisfaction levels.