Abstract: Techniques are disclosed for determining application experience of a user. One embodiment presented herein includes a computer-implemented method, which includes receiving, at a computing device, eye tracking data of a user interacting with at least a first page of an application. The computer-implemented method further includes determining, based at least on the eye tracking data, at least a current user experience regarding the first page. The computer-implemented method further includes predicting, based on evaluating the current user experience, that the user is likely to discontinue use of the application. The computer-implemented method further includes determining, based at least on the prediction, an intervention that reduces a likelihood of the user discontinuing use of the application, and interacting with the user according to the intervention.

Abstract: A method and system provides personalized search results to users of a data management system. The method and system receives a search query from a user and generate initial search results including a plurality of assistance documents relevant to the query data. The method and system utilizes natural language analysis and machine learning processes to analyze the query data, user attributes data, and the assistance documents in order to generate personalized previews of the assistance documents for the user. The method and system output personalized search results to the user including the personalized previews of the assistance documents.

Abstract: Disclosed methods and systems provide domain-specific type ahead suggestions for search query terms with a customer self-service system for a tax return preparation system, according to one embodiment. Type ahead suggestions include suggestions for completing a single search query term and/or suggestions for completing a search query having multiple search query terms. The customer self-service system receives one or more search query terms in a search text box, searches for potential search queries that are likely to complete the one or more search query terms, and provides a selected one of the potential search queries in the search text box as a type ahead suggestion, adjacent to the received one or more search query terms, according to one embodiment. The customer self-service system selects one of the potential search queries based on the received search query terms, the user's profile, and/or the user's tax data, according to one embodiment.

Abstract: Techniques are disclosed for adjusting a ranking of information content of a software application based on feedback from a user. One embodiment presented herein includes a method comprising receiving, at a computing device, an audio stream comprising audio of the user, the audio being indicative of feedback related to information content. The method further comprises analyzing the audio stream for paralinguistic information to determine an attribute of the user. The method further comprises adjusting a ranking of the information content based on at least one of the feedback and additional feedback and the determined attribute of the user.

Abstract: Embodiments presented herein provide techniques for inferring the current emotional state of a user based on paralinguistic features derived from audio input from that user. If the emotional state meets triggering conditions, the system provides the user with a prompt which allows the user to connect with a support agent. If the user accepts, the system selects a support agent for the user based on the predicted emotional state and on attributes of the support agent found in an agent profile. The system can also determine a priority level for the user based on the score and based on a profile of the user and determine where to place the user in a queue for the support agent.

Abstract: Disclosed methods and systems determine levels of search sophistication for users of a customer self-help system to personalize a content search user experience provided to the users, to increase a likelihood of users' satisfaction with the search experience. The customer self-help system analyzes submitted search queries and provides an advanced content search user experience to users who are determined to have an advanced level of search sophistication and provides a simplified content search user experience to users who are determined to have a basic or less-experienced level of search sophistication. Providing users with personalized content search user experiences that are based on users' levels of search sophistication allows less-experienced users to feel comfortable searching and allows advanced users to search more quickly or precisely.

Abstract: Techniques are disclosed for adjusting a ranking of information content presented to a user based on voice-of-customer feedback. In one embodiment, a user may provide feedback on information content presented to the user. Such feedback may be evaluated to identify at least one topic referenced in the received feedback. If an application determines that the at least one topic is related to topics of the information content, the application determines sentiment regarding the information content based on the feedback, and adjusts a ranking of the information content based on the determined sentiment.

Abstract: Disclosed methods and systems provide domain-specific type ahead suggestions for search query terms with a customer self-service system for a tax return preparation system, according to one embodiment. Type ahead suggestions include suggestions for completing a single search query term and/or suggestions for completing a search query having multiple search query terms. The customer self-service system receives one or more search query terms in a search text box, searches for potential search queries that are likely to complete the one or more search query terms, and provides a selected one of the potential search queries in the search text box as a type ahead suggestion, adjacent to the received one or more search query terms, according to one embodiment. The customer self-service system selects one of the potential search queries based on the received search query terms, the user's profile, and/or the user's tax data, according to one embodiment.

Abstract: Embodiments presented herein provide techniques for inferring the current emotional state of a user based on paralinguistic features derived from audio input from that user. If the emotional state meets triggering conditions, the system provides the user with a prompt which allows the user to connect with a support agent. If the user accepts, the system selects a support agent for the user based on the predicted emotional state and on attributes of the support agent found in an agent profile. The system can also determine a priority level for the user based on the score and based on a profile of the user and determine where to place the user in a queue for the support agent.

Abstract: Certain aspects of the present disclosure provide techniques for selecting a response to a self-support query. One example method generally includes receiving an audio stream query including spoken content from a user recorded by a mobile device and determining a set of paralinguistic features from the spoken content. The method further includes estimating an emotional state of the user based on the set of paralinguistic features and identifying subject matter of the spoken content in the audio stream query. The method further includes determining two or more query responses corresponding to the subject matter to present to the user and transmitting at least one query response to the mobile device.

Abstract: Systems of the present disclosure adjust an interface mode of an application based on paralinguistic features of audio input. The audio input is via a microphone associated with a computing device. A predictive model uses paralinguistic features of the audio input and additional features received from sensors or a user profile to predict an interface mode that a user would currently prefer to use. The interface mode specifies how output is provided and how input is received. The interface mode may also specify which elements of a graphical user interface are displayed, where the elements are placed, and how the elements are sized.

Abstract: Methods and systems are disclosed for finding and navigating information in financial management systems. In some implementations, a customer self-service system provides incremental search results that are based on user profile information, customer self-service content, and navigation history of a user within a financial management system. The user profile information may include one or more of an estimated income level of the user, an estimated education level of the user, business financial records of the user, tax return information of the user, or personal financial records of the user. The customer self-service system provides the search results incrementally, thereby allowing the user to receive references to transactions or transaction details in real-time as the user provides search query terms for the customer self-service system.

Abstract: Disclosed methods and systems improve search results by recency boosting customer support content for a customer self-help system associated with one or more financial management systems. The customer self-help system retrieves content relevance from a variety of sources, such as media outlets, taxation agencies and news feeds for the financial management system. The customer self-help system generates content relevance weights from the content relevance data, and applies the content relevance weights to customer support content maintained by the customer self-help system. In response to receiving a search query from a user, the customer self-help system provides relevant portions of customer support content that has been recency boosted (e.g., adjusted by the content relevance weights), to increase the likelihood that the customer support content provided to the user is relevant to the user's search query.

Abstract: Embodiments presented herein provide techniques for inferring the current emotional state of a user based on paralinguistic features derived from audio input from that user. If the emotional state meets triggering conditions, the system provides the user with a prompt which allows the user to connect with a support agent. If the user accepts, the system selects a support agent for the user based on the predicted emotional state and on attributes of the support agent found in an agent profile. The system can also determine a priority level for the user based on the score and based on a profile of the user and determine where to place the user in a queue for the support agent.

Abstract: Techniques are disclosed for determining application experience of a user based on paralinguistic information determined for the user. One embodiment presented herein includes a computer-implemented method, which includes receiving, at a computing device, one or more audio streams. Each audio stream includes audio from a user interacting with at least one page of an application. The computer-implemented method also includes generating paralinguistic information from at least one of the audio streams. The paralinguistic information characterizes acoustic aspects of the audio stream that are distinct from verbal content of the audio stream.

Abstract: Techniques are disclosed for adjusting a ranking of information content presented to a user based on voice-of-customer feedback. In one embodiment, a user may provide feedback on information content presented to the user. Such feedback may be evaluated to identify at least one topic referenced in the received feedback. If an application determines that the at least one topic is related to topics of the information content, the application determines sentiment regarding the information content based on the feedback, and adjusts a ranking of the information content based on the determined sentiment.

Abstract: Certain aspects of the present disclosure provide techniques for selecting a response to a self-support query. One example method generally includes receiving an audio stream query including spoken content from a user recorded by a mobile device and determining a set of paralinguistic features from the spoken content. The method further includes estimating an emotional state of the user based on the set of paralinguistic features and identifying subject matter of the spoken content in the audio stream query. The method further includes determining two or more query responses corresponding to the subject matter to present to the user and transmitting at least one query response to the mobile device.

Abstract: Disclosed methods and systems provide domain-specific incremental search results for search query terms with a customer self-service system for a financial management system, according to one embodiment. Incremental search results are search results that are generated for search query terms, as a user enters the search query terms as part of a search query to a customer self-service system, according to one embodiment. The customer self-service system receives search query terms (e.g., a partial search query) in a search text box, searches user content (e.g., business transactions, personal transactions, etc.) and customer self-service system content for content that is relevant to the search query terms, and provides incremental search results navigation links within a results text box to enable users to easily see search results (e.g., transaction records) and to enable users to navigate to transactions records or other user content, from the results text box, according to one embodiment.

Abstract: Disclosed methods and systems improve search results by recency boosting customer support content for a customer self-help system associated with one or more financial management systems. The customer self-help system retrieves content relevance from a variety of sources, such as media outlets, taxation agencies and news feeds for the financial management system. The customer self-help system generates content relevance weights from the content relevance data, and applies the content relevance weights to customer support content maintained by the customer self-help system. In response to receiving a search query from a user, the customer self-help system provides relevant portions of customer support content that has been recency boosted (e.g., adjusted by the content relevance weights), to increase the likelihood that the customer support content provided to the user is relevant to the user's search query.

Abstract: Embodiments presented herein provide techniques for inferring the current emotional state of a user based on paralinguistic features derived from audio input from that user. If the emotional state meets triggering conditions, the system provides the user with a prompt which allows the user to connect with a support agent. If the user accepts, the system selects a support agent for the user based on the predicted emotional state and on attributes of the support agent found in an agent profile. The system can also determine a priority level for the user based on the score and based on a profile of the user and determine where to place the user in a queue for the support agent.