Intuit, Inc.

Joel R Minton

Massimo Mascaro

Yao H Morin

Carol Ann Howe

Joseph B Cessna

Jonathan Lunt

Preetam Kumar Ojha

Sharon E Hunt

A method and system adaptively improves potential customer conversion rates, revenue metrics, and/or other target metrics by providing effective user experience options, from a variety of different user experience options, to some users while concurrently testing user responses to other user experience options, according to one embodiment. The method and system selects the user experience options by applying user characteristics data to an analytics model, according to one embodiment. The method and system analyzes user responses to the user experience options to update the analytics model, and to dynamically adapt the personalization of the user experience options, at least partially based on feedback from users, according to one embodiment.

Method and system for providing personalized user experiences to software system users

A method and system provides personalized user experiences to users of a tax return preparation system, at least partially based on likelihoods of occurrence of life events for the users in a tax year, according to one embodiment. The method and system applies the user data to one or more predictive models to determine the likelihood that one or more available life events occurred in a user's life in a tax year, according to one embodiment. The method and system display life event icons that represent the one or more available life events, and the life event icons are ranked, sorted, and/or emphasized, based on the likelihood that the one or more available life events occurred in a user's life, to increase a user's confidence in the tax return preparations system's capability to address the user's life changes while preparing the user's tax return, according to one embodiment.

Method and system for providing a personalized user experience in a tax return preparation system based on predicted life events for a user

A method and system applies analytics models to a tax return preparation system to determine a likelihood of qualification for an earned income tax credit by a user, according to one embodiment. The method and system receive user data and applying the user data to a predictive model to cause the predictive model to determine, at least partially based on the user data, a likelihood of qualification for an earned income tax credit for the user, according to one embodiment. The method and system display, for the user, an estimated tax return benefit to the user, at least partially based on the likelihood of qualification for the earned income tax credit exceeding a predetermined threshold, to reduce delays in presenting estimated earned income tax credit benefits to the user during a tax return preparation session in a tax return preparation system, according to one embodiment.

Method and system for applying analytics models to a tax return preparation system to determine a likelihood of receiving earned income tax credit by a user

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La Jolla, CA, United States of America

Joel R Minton