INTELLIGENT OFFER FOR RELATED PRODUCTS WITH PREVIEW AND REAL TIME FEEDBACK
Recommendations for purchase are made based on customer behavior across multiple sessions. Correlations used for recommendations include: buy-to-buy (cross-session), view-to-view (same-session), view-to-buy (same-session), and abandon-to-buy (same-session) actions. A preview display allows a merchant to adjust recommendation algorithm weightings to achieve a desired result. A closed-loop system is provided with real-time feedback. The recommendations can be based on various segments of other users, including users of the same search engine.
1 . A method for recommending affinity products, the method comprising:
collecting, in a server system, data corresponding to monitored actions on a web site;
providing an identification of affinity products based on said monitored actions relating to a target product;
providing a preview of an identified affinity product;
modifying the selection of said identified affinity product; and
providing an updated preview showing any change in said affinity product due to said modifying.
2 . The method as recited in claim 1 further comprising:
providing a formula having weightings for identifying affinity products based on said monitored actions;
providing a preview of an affinity product identified according to said formula;
varying said weightings; and
providing an updated preview showing any change in said affinity product due to said varying of said weightings.
3 . The method as recited in claim 2 , wherein said formula includes an exclusion of selected products.
4 . The method as recited in claim 2 , wherein said formula provides at least two correlations of a browsing or buying action of a first product by a first user with browsing, abandoning or buying actions of a group of users who also browsed or brought said first product.
5 . The method as recited in claim 2 , wherein said monitored actions include keywords, and said affinity product is a product on which action was taken by a group of users who used the same keyword.
6 . The method as recited in claim 1 further comprising:
providing a plurality of affinity products for each target product.
7 . The method as recited in claim 1 , wherein said preview comprises a listing of a plurality of target products, with at least one affinity produce associated therewith.
8 . A method for tracking web usage data in real time, the method comprising:
collecting, in a server system, real time data corresponding to monitored actions on a web site, said monitored actions including buying a recommended product;
aggregating said real time data into aggregate groups desired for display;
storing said aggregated real time data in a hierarchical structure in a RAM in said server system; and
providing said real time data from said RAN to a client at a client computer.
9 . The method as recited in claim 8 further comprising:
providing an identification of affinity products based on said monitored actions relating to a target product;
providing a preview of an identified affinity product;
modifying the selection of said identified affinity product based on said real time data; and
providing an updated preview showing any change in said affinity product due to said modifying.
10 . A method for recommending affinity products, the method comprising:
collecting, in a server system, data corresponding to monitored actions on a web site;
providing a formula for identifying affinity products based on said monitored actions;
tracking said monitored actions for an identified segment of users; and
identifying said affinity product from monitored actions of said segment of users.
11 . The method as recited in claim 10 , wherein said segment is selected from the group of segments comprising product market segment, time related segment, user characteristic segment, geographical segment and browsing action segment.
12 . The method as recited in claim 10 further comprising:
providing an identification of affinity products based on said monitored actions relating to a target product;
providing a preview of an identified affinity product;
modifying the selection of said identified affinity product; and
providing an updated preview showing any change in said affinity product due to said modifying.
13 . The method as recited in claim 10 further comprising:
collecting, in a server system, real time data corresponding to said monitored actions on a web site;
aggregating said real time data into aggregate groups desired for display;
storing said aggregated real time data in a hierarchical structure in a RAM in said server system; and
providing said real time data from said RAM to a client at a client computer.