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Real-time customer analytics is a type of analytics which concentrates on real-time data captured from customers as they are performing their actions rather than on older historical data like traditional analytics, which use historical data to predict future trends. Real-time customer analytics also gives more emphasis to customer interaction and usage data rather than page views and other similar statistics, giving a more customer-centric view rather than a demographic one.
Real-time customer analytics software and techniques make use of all available enterprise data and other resources, specifically data, in order to combine both dynamic analysis and reporting based on customer data that has been recorded from the last few minutes. This allows a business to make up-to-the-minute business decisions that may affect the user-base currently using the organization's systems.
Real-time customer analytics can support instant and up-to-date information in company dashboards as well as reflect business decisions and changes throughout the day. It can also be used to track critical system bugs that are affecting a large portion of an organization's customers or even predict a DDoS attack based on the activity of the perceived customers. The system can see if the behavior is similar to that of regular customers or if the group is acting in a very coordinated way, indicating an attack.