Intelligent monitoring systems and methods for Wi-Fi metric-based predictions for cloud-based Wi-Fi networks

A method comprising:

• obtaining Wi-Fi network data, over the Internet, associated with a plurality of Wi-Fi networks each Wi-Fi network having one or more access points and each Wi-Fi network being associated with a customer of one or more service providers and obtaining customer data for each customer associated with the plurality of Wi-Fi networks;
• aggregating and filtering the Wi-Fi network data for the plurality of Wi-Fi networks;
• analyzing the aggregated and filtered data, and determining, based on the analysis, correlations made between previous actions by the customers and the Wi-Fi network data, the correlations include a call-in rate to at least one of alarm conditions, coverage and congestion of the plurality of Wi-Fi networks, a classification of the customers, a number of previous call-ins made by the customers, a number of devices connected to the plurality of Wi-Fi networks, a service type associated with each of the plurality of Wi-Fi networks, and a number of nodes within each of the plurality of Wi-Fi networks;
• predicting, based on the determined correlations, customer action for each of the customers, the predicted customer action corresponding to each customer's respective Wi-Fi network, the predicted customer action is a call-in to the one or more service providers;
• and
• displaying a list of the predicted customer actions.

An apparatus executing a cloud-based monitoring service for a plurality of Wi-Fi networks, the apparatus comprising:

• a network interface communicatively coupled to the plurality of Wi-Fi networks via the Internet;
• a processor communicatively coupled to the network interface;
• and
• memory storing instructions that, when executed, cause the processor to:
• obtain Wi-Fi network data, over the Internet, associated with a plurality of Wi-Fi networks each Wi-Fi network having one or more access points and each Wi-Fi network being associated with a customer of one or more service providers and obtaining customer data for each customer associated with the plurality of Wi-Fi networks;
• aggregate and filter the Wi-Fi network data for the plurality of Wi-Fi networks;
• analyze the aggregated and filtered data, and determining, based on the analysis, correlations made between previous actions by the customers and the Wi-Fi network data, the correlations include a call-in rate to at least one of alarm conditions, coverage and congestion of the plurality of Wi-Fi networks, a classification of the customers, a number of previous call-ins made by the customers, a number of devices connected to the plurality of Wi-Fi networks, a service type associated with each of the plurality of Wi-Fi networks, and a number of nodes within each of the plurality of Wi-Fi networks;
• predict, based on the determined correlations, customer action for each of the customers, the predicted customer action corresponding to each customer's respective Wi-Fi network, the predicted customer action is a call-in to the one or more service providers;
• and
• display a list of the predicted customer actions.