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US 11,080,721 B2Granted
Method and apparatus for an intuitive customer experience
Assignee7.ai, Inc.
InventorsPallipuram V. Kannan, Ravi Vijayaraghavan
Life of this patent
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Abstract
Improvement of customer experiences during online commerce is accomplished by providing unique experiences to customers as a result of anticipating customer needs, simplifying customer engagement based on predicted customer intent, and updating system knowledge about customers with information gathered from new customer interactions. In this way, the customer experience is improved.
Claims15
A method, implemented in a computer system comprising a processor and a memory, for reducing a time of navigation or number of interactions to navigate through an online commerce system, comprising:
- anticipating, by an anticipation engine, a target action to be taken by a first user with an online commerce system engine based on a machine learned model of recorded past interaction by the first user with the online commerce system using a set of current system conditions, the recorded past interaction including navigation choices between pages on the online commerce system;
- generating, by a simplification engine, a new navigation path between a first page on the online commerce system and a second page on the online commerce system, the second page including the target action, wherein the new navigation path is supported by a direct link embodied by a user interface object in the online commerce system, wherein the new navigation path navigates between the first page and the second page in a single click skipping any intermediate pages, and wherein all other navigation paths between the first page and the second page prior to said generating of the new navigation path and the direct link required users to visit other intermediate pages;
- integrating the user interface object to an instance of the user interface associated with the first user;
- measuring, by a learning engine, a user effort criteria for the first user, wherein the user effort criteria is measured using any of:
- time in a current online navigation path or number of interactions relative to a benchmark;
- and
- continuously updating, by the learning engine, the machine learned model interaction taken by the first user with the online commerce system under system conditions including:
- user IP, country, time of visit, day of visit, attributes of browser used, and any interaction taken by the first user with respect to the user interface object.
5 more elements
Dependencies are inferred from the claim text.