Abstract: An automated network merchandising system provides a platform for delivering relevant retail offers to interested consumers online. A backend content pipeline analyzes and processes delivered catalog content into a merchandisable universe of products (MUP). On a user-facing end, corner stores—ad units appearing on pages of publishers' web sites—display offers from the MUP. Publishers deploy store scripts to their web pages. The script runs in the user's browser, causing display of an interactive ad unit featuring product offers. An adaptive targeting engine produces targeted product offers based on the ad's display context, including at least user data, page analysis and geographic location. A targeting console allows marketers to specify campaigns targeted to particular corner store ad contexts. Campaigns are defined by combinations of product categories, merchants, price ranges and key words. A store builder allows publishers to specify campaigns to be displayed to web site visitors.

Abstract: A method of network merchandising incorporates contextual and personalized advertising with human input to deliver relevant retail offers to interested online consumers efficiently and intelligently. Catalog content from retailers is downloaded, semantically analyzed and merged. The merged content is filtered using machine- and human-generated specifications to produce a merchandisable universe of products (MUP). Marketers and publishers create and modify corner store ad units and specify product offers from the MUP to display in those units. Publishers deploy the ad units on their web pages. Compensation of publishers by retailers can use a pay-for-performance model. Users visit the publisher's pages, viewing the product offers in the rendered ad unit.