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公开(公告)号:US11961109B2
公开(公告)日:2024-04-16
申请号:US16742386
申请日:2020-01-14
Applicant: ADOBE INC.
Inventor: Lei Zhang , Jun He , Tingting Xu , Jalaj Bhandari , Wuyang Dai , Zhenyu Yan
IPC: G06Q30/00 , G06F18/20 , G06N3/08 , G06N20/00 , G06Q10/107 , G06Q30/0207
CPC classification number: G06Q30/0239 , G06F18/295 , G06N3/08 , G06N20/00 , G06Q10/107
Abstract: Systems and methods for customer journey optimization in email marketing are described. The systems and methods may identify a plurality of messages for a first time period, wherein the plurality of messages are categorized according to a plurality of messages types, identify user information for a customer, wherein the user information includes user interaction data, determine a message type from the plurality of message types for the first time period based on the user information, wherein the message type is determined using a decision making model comprising a deep Q-learning neural network, select a message from the plurality of messages based on the determined message type, and transmit the message to the customer during the first time period based on the selection.
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公开(公告)号:US11645542B2
公开(公告)日:2023-05-09
申请号:US16384558
申请日:2019-04-15
Applicant: Adobe Inc.
Inventor: Lei Zhang , Jun He , Zhenyu Yan , Wuyang Dai , Abhishek Pani
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a target distribution schedule for providing electronic communications based on predicted behavior rates by utilizing a genetic algorithm and one or more objective functions. For example, the disclosed systems can generate predicted behavior rates by training and utilizing one or more behavior prediction models. Based on the predicted behavior rates, the disclosed systems can further utilize a genetic algorithm to apply objective functions to generate one or more candidate distribution schedules. In accordance with the genetic algorithm, the disclosed systems can select a target distribution schedule for a particular user/client device. The disclosed systems can thus provide one or more electronic communications to individual users based on respective target distribution schedules.
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公开(公告)号:US20230005023A1
公开(公告)日:2023-01-05
申请号:US17366910
申请日:2021-07-02
Applicant: ADOBE INC.
Inventor: Lei Zhang , Lijun Yu , Jun He , Zhenyu Yan , Wuyang Dai
IPC: G06Q30/02
Abstract: Methods and systems are provided for improved electronic communication campaign technologies, which can automatically balance objectives or goals of an electronic communication campaign against an overall opt-out rate for the electronic communication campaign. An electronic communications frequency optimizer can generate individual contact frequencies for individual email recipients. Embodiments can avoid unnecessary or counterproductive communications while achieving overall campaign goals, and can use processes to improve the efficiency of systems. In some cases, embodiments cluster communication recipients into different groups based on their past actions, then optimizes the communication contact frequency on different groups, to avoid performing optimization directly on millions of recipients. Some embodiments automatically self-update, for example with recipients' recent responses, to generate and/or implement campaign communication schedules on an individual level.
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公开(公告)号:US12229804B2
公开(公告)日:2025-02-18
申请号:US17366910
申请日:2021-07-02
Applicant: ADOBE INC.
Inventor: Lei Zhang , Lijun Yu , Jun He , Zhenyu Yan , Wuyang Dai
IPC: G06Q30/02 , G06Q30/0272
Abstract: Methods and systems are provided for improved electronic communication campaign technologies, which can automatically balance objectives or goals of an electronic communication campaign against an overall opt-out rate for the electronic communication campaign. An electronic communications frequency optimizer can generate individual contact frequencies for individual email recipients. Embodiments can avoid unnecessary or counterproductive communications while achieving overall campaign goals, and can use processes to improve the efficiency of systems. In some cases, embodiments cluster communication recipients into different groups based on their past actions, then optimizes the communication contact frequency on different groups, to avoid performing optimization directly on millions of recipients. Some embodiments automatically self-update, for example with recipients' recent responses, to generate and/or implement campaign communication schedules on an individual level.
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公开(公告)号:US20200327419A1
公开(公告)日:2020-10-15
申请号:US16384558
申请日:2019-04-15
Applicant: Adobe Inc.
Inventor: Lei Zhang , Jun He , Zhenyu Yan , Wuyang Dai , Abhishek Pani
Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a target distribution schedule for providing electronic communications based on predicted behavior rates by utilizing a genetic algorithm and one or more objective functions. For example, the disclosed systems can generate predicted behavior rates by training and utilizing one or more behavior prediction models. Based on the predicted behavior rates, the disclosed systems can further utilize a genetic algorithm to apply objective functions to generate one or more candidate distribution schedules. In accordance with the genetic algorithm, the disclosed systems can select a target distribution schedule for a particular user/client device. The disclosed systems can thus provide one or more electronic communications to individual users based on respective target distribution schedules.
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公开(公告)号:US20250068800A1
公开(公告)日:2025-02-27
申请号:US18455005
申请日:2023-08-24
Applicant: ADOBE INC.
Inventor: Lei Zhang , Jun He , Zhenyu Yan , Roger K. Brooks
IPC: G06F30/27
Abstract: Systems and methods for pre-deployment user journey evaluation are described. Embodiments are configured to obtain a user journey including a plurality of touchpoints; generate a simulation agent including a plurality of attributes; generate a probability score for the simulation agent for each of the plurality of touchpoints based on the plurality of attributes using a machine learning model; perform a simulation of the user journey based on the probability score; and generate a text describing the user journey based on the simulation.
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