Abstract: In a video delivery context, collection and analysis of viewing data can provide insight into viewer interaction with video and the Internet. The viewing data can be transmitted in a controlled manner to a data repository. Disclosed herein are system, method, and computer program product embodiments for optimizing inventory based on predicted viewership. An example embodiment operates by evaluating past viewership data for a periodic event, determining a tendency of a market segment to view the periodic event, and predicting viewership for a future event based on the determined tendency.

Abstract: Embodiments utilize viewership data collected via a set top box (STB) at individual households (HHs) to enable a network operator to recommend ad spots to customers based on a percentage of HHs that are likely to view the ad spots (e.g., the % of HHs reached by the ad spots), and/or based on the average number of times (e.g., average frequency) that the reached HHs are likely to view the ad spot. Embodiments compile the available network/daypart ad spots per broadcast week, and determine a number of ad spots for each network/daypart that satisfy a reached threshold of HHs, and/or satisfies the minimum frequency threshold.

Abstract: In a video delivery context, collection and analysis of viewing data can provide insight into viewer interaction with video and the Internet. The viewing data can be transmitted in a controlled manner to a data repository. Disclosed herein are system, method, and computer program product embodiments for optimizing inventory based on predicted viewership. An example embodiment operates by evaluating past viewership data for a periodic event, determining a tendency of a market segment to view the periodic event, and predicting viewership for a future event based on the determined tendency.

Abstract: Embodiments utilize viewership data collected via a set top box (STB) at individual households (HHs) to enable a network operator to recommend ad spots to customers based on a percentage of HHs that are likely to view the ad spots (e.g., the % of HHs reached by the ad spots), and/or based on the average number of times (e.g., average frequency) that the reached HHs are likely to view the ad spot. Embodiments compile the available network/daypart ad spots per broadcast week, and determine a number of ad spots for each network/daypart that satisfy a reached threshold of HHs, and/or satisfies the minimum frequency threshold.