Abstract: The present teaching relates to forecasting a campaign performance using predictive modeling. In one example, a request for forecasting a campaign performance is received from a user. A plurality of parameters associated with the request are retrieved. A predictive score is generated based on the plurality of parameters. A variable vector is constructed based on one or more of the plurality of campaign parameters selected by the user. A key performance indicator (KPI) matrix is generated in accordance with the predictive score based on the variable vector.

Abstract: The present teaching relates to forecasting a campaign performance using predictive modeling. In one example, a request for forecasting a campaign performance is received from a user. A plurality of parameters associated with the request are retrieved. A predictive score is generated based on the plurality of parameters. A variable vector is constructed based on one or more key performance indicators (KPIs) selected by the user. A campaign data matrix is generated in accordance with the predictive score based on the variable vector.

Abstract: The present teaching relates to online user engagement measurement. In one example, user activities with respect to a piece of content are detected. The user activities include visiting a web site in association with the piece of content. A plurality of variables are determined based on the detected user activities. The plurality of variables include a number of web pages loaded in the web site. An engagement scoring model is obtained. An engagement score of the piece of content is estimated based on the plurality of variables and the engagement scoring model.