Method and system for media initialization via data sharing

An apparatus, comprising:

• a storage device;
• and
• a processor coupled to the storage device, wherein the storage device stores a program for controlling the processor, and wherein the processor, being operative with the program, is configured to:
• select a plurality of media cells that share one or more common attributes with a target media cell;
• estimate a mean revenue per impression of the selected media cells;
• and
• estimate a mean revenue per impression of the selected media cells, the processor being further configured to:
• compute an approximation of an error associated with the mean revenue per impression of the selected media cells, the error approximation being indicative of at least numbers of impressions associated with the selected media cells;
• determine a threshold value associated with the error approximation, based on at least a revenue model of the selected media cells;
• determine whether the error approximation exceeds the threshold value;
• and
• when the error approximation does not exceed the threshold value, compute the estimated mean revenue per impression of the selected media cells based on a distribution of revenue per impression associated with the selected media cells;
• and
• predict a revenue per impression of the target media cell based on the estimated mean revenue per impression of the selected media cells.

A tangible computer readable medium comprising a set of instructions that, when executed on a processor, perform a method for estimating media performance on advertising space inventory, the method comprising:

• selecting a plurality of media cells that share one or more common attributes with a target media cell;
• estimating, using a processor, a mean revenue per impression of the selected media cells, the estimating comprising:
• computing an approximation of an error associated with the mean revenue per impression of the selected media cells, the error approximation being indicative of at least numbers of impressions associated with the selected media cells;
• determining a threshold value associated with the error approximation, based on at least a revenue model of the selected media cells;
• determining whether the error approximation exceeds the threshold value;
• and
• when the error does not exceed the threshold value, computing the estimated mean revenue per impression of the selected media cells based on a distribution of revenue per impression associated with the selected media cells;
• and
• predicting a revenue per impression of the target media cell based on the estimated mean revenue per impression of the selected media cells.