A computer-implemented method of training and employing predictors for improving the service quality of a telecom service provider network, the telecom service provider network providing subscribers access to a data network, the method comprising: obtaining network conditions data indicating a connection quality of the subscribers with the data network; obtaining subscriber feedback data based on interactions of subscribers with a set of business support systems of the telecom service provider network; correlating the network conditions data with tags extracted from the subscriber feedback data to obtain tagged network conditions data; training one or more predictors for the service quality of the telecom service provider network, the training of the predictors employing the tagged network conditions data, further comprising: obtaining second network conditions data indicating a current connection quality of the subscribers with the data network; generating predictions for the service quality of the telecom service provider network by providing the second network conditions data to a trained predictor of the one or more predictors; and employing a rule-based engine to, based on the predictions, propose actions to improve the service quality of the telecom service provider network and further comprising extracting an explanation from the one or more trained predictors allowing an interpretation of the predictions, wherein extracting the explanation comprises analyzing top impacting factors that impact the predictions generated by the one or more predictors. obtaining network conditions data indicating a connection quality of the subscribers with the data network; obtaining subscriber feedback data based on interactions of subscribers with a set of business support systems of the telecom service provider network; correlating the network conditions data with tags extracted from the subscriber feedback data to obtain tagged network conditions data; training one or more predictors for the service quality of the telecom service provider network, the training of the predictors employing the tagged network conditions data, further comprising: obtaining second network conditions data indicating a current connection quality of the subscribers with the data network; generating predictions for the service quality of the telecom service provider network by providing the second network conditions data to a trained predictor of the one or more predictors; and employing a rule-based engine to, based on the predictions, propose actions to improve the service quality of the telecom service provider network and further comprising extracting an explanation from the one or more trained predictors allowing an interpretation of the predictions, wherein extracting the explanation comprises analyzing top impacting factors that impact the predictions generated by the one or more predictors. obtaining second network conditions data indicating a current connection quality of the subscribers with the data network; generating predictions for the service quality of the telecom service provider network by providing the second network conditions data to a trained predictor of the one or more predictors; and employing a rule-based engine to, based on the predictions, propose actions to improve the service quality of the telecom service provider network and further comprising extracting an explanation from the one or more trained predictors allowing an interpretation of the predictions, wherein extracting the explanation comprises analyzing top impacting factors that impact the predictions generated by the one or more predictors.