Ad-words optimization based on performance across multiple channels

A computer implemented method for optimizing online advertising, comprising:

• a processor configured for predicting user intent in the context of a plurality of channels with which the user performs a search;
• said processor also configured for predicting user intent by integrating a plurality of data sources to gain an enhanced understanding of user intent associated with each search term entered by the user;
• and
• said processor configured for selecting an advertisement for presentation to said user based on said user intent.

A computer implemented method for optimizing online advertising, comprising:

• a processor configured for using search term feature based models to identify a subset of search patterns to bid on based on predicted user intent in the context of a plurality of channels with which the user performs a search;
• wherein said models comprise any of purchase propensity models and channel affinity models;
• wherein purchase propensity concerns the propensity of user segments to purchase a particular product by taking into consideration factors that comprise any of purchase, mode of channel, specificity, recency and other factors and attributes that are used to predict intent;
• wherein said purchase propensity model outcome comprises a likelihood of a customer segment to take an action with regard to specific products, including which events that are likely to trigger said action.

An apparatus for optimization of ad-words, comprising:

• providing a processor for determining ad-word performance across multiple channels based upon user search terms;
• said processor integrating a plurality of data sources to determine said user's intent associated with said search terms;
• and
• said processor selecting an advertisement for presentation to said user based on said user intent.