A credit segment identifying device includes an extracting unit which extracts, from a first speech signal, a plurality of first partial speech signals which are each a part of the first speech signals and shifted from each other in time direction and an identifying unit which identifies a credit segment in the first speech signal by determining whether each of the first partial speech signals includes a credit according to an association between each of second partial signals extracted from a second speech signal and the presence/absence of a credit, so that credit segments can be identified more efficiently.

An image processing unit (110) acquires a position of an advertisement and a position of a product by analyzing an image in which the product and the advertisement are disposed on a shelf rack are captured. A determination unit (120) determines whether or not a relation between the position of the product and the position of the advertisement satisfies a criterion. An output unit (130) outputs information indicating a determination result obtained by the determination unit (120).

Embodiments of the present specification provide methods for performing marketing cost control by using a deep reinforcement learning system. One method includes the following: determining a cost of a marketing activity; determining a reward score of reinforcement learning that is negatively correlated with the cost; and returning the reward score to a smart agent of a deep reinforcement learning system, for the smart agent to update a marketing strategy, wherein the smart agent is configured to determine a marketing activity based on the marketing strategy and status of an execution environment of the deep reinforcement learning system.

A method including tracking first data including responses by users to email campaigns. The method also can include generating a user feature set for the users, the user feature set including personal features of each of the users and online activity history for each of the users across a first set of time periods. The method additionally can include generating an email feature set for the emails in the email campaigns. The method further can include training a logistic regression model to create a trained model using the first data, the user feature set, and the email feature set to provide a probability of a user of the users clicking on an email of the emails within each time period of a second set of time periods. The method additionally can include triggering sending a first email of the email campaigns to a first user of the users at a selected time period of the second set of time periods based at least in part on the trained model. Other embodiments are disclosed.

Systems, methods, and devices for affiliate marketing. A method of the disclosure includes receiving affiliate product data from a merchant account. The method includes determining intelligence sources for generating an affiliate product for a promoter account and determining rules for generating the affiliate product for the promoter account. The method includes determining the affiliate product for the promoter account based on the intelligence sources, the rules, and the affiliate product data from the merchant account. The method includes tracking consumer click-throughs on the affiliate product provided to the promoter account.

A method and apparatus for tracking a conversion of an advertisement provided through an application are disclosed. The method includes generating, in response to selection of an advertisement through a first application installed on a first user terminal, a click log including a first advertiser identifier corresponding to an advertiser of the advertisement and a first user identifier corresponding to the first user terminal, generating, in response to reading of an informational message through a second application installed on a second user terminal, a conversion log including a second advertiser identifier corresponding to a sender of the informational message and a second user identifier corresponding to the second user terminal, and tracking whether a conversion event occurs due to the advertisement by mapping the click log and the conversion log.

Systems and methods for data analytics are described. The systems and methods include receiving attribute data for at least one user, identifying a plurality of precursor events causally related to an observable target interaction with the at least one user, wherein at least one of the precursor events comprises a marketing event, predicting a probability for each of the precursor events based on the attribute data using a neural network trained with a first loss function comparing individual level training data for the observable target interaction, and performing the marketing event directed to the at least one user based at least in part on the predicted probabilities.

An auto-login system and process enable maintaining user accounts on a server without a user having to register or create a user name, password, or other authentication method. An account may be created without user knowledge. The server may transmit a content item to a target user, along with a link. A server identifies the target user from use of the auto-login link and collects interaction or “engagement” data while the user is logged in, to assess user interest in products, for example, a mutual fund investment product, which may be characterized by tags and/or categories. The system may quantify a product salience metric for a given product relative to a target user's interest profile to focus marketing efforts and support engagement with interested target users, especially securities funds and financial advisors.

Systems, methods, and computer readable storage media for controlling the transmission of electronic messages are provided. Aspects of the disclosure provide a method for controlling electronic transmission of electronic communications generated by authoring services. The method includes receiving a first message from a first authoring service of the plurality of authoring services, the first message comprising at least one recipient and content for at least one electronic communication, adding the first message to a message queue associated with the at least one recipient, determining one or more characteristics associated with the at least one recipient, evaluating the first message using the one or more characteristics to determine a first message state for the first message, in response to determining that the message state indicates the first message is to be transmitted, forwarding the first message to message transmission circuitry, and transmitting the first message to the recipient.

Aspects of the subject disclosure may include, for example, determining conversions associated with an advertising campaign, identifying consumers associated with the conversions. Further embodiments can include determining an attribution window for the advertising campaign, identifying first advertisements of the advertising campaign exposed to the consumers during the attribution window. Additional embodiments include identifying an advertising medium for each of the first advertisements resulting in a plurality of advertising mediums, and adjusting the advertising campaign according to the conversions and the plurality of advertising mediums resulting in an adjusted advertising campaign. Also, embodiments include delivering, over a communication network, second advertisements associated with the adjusted advertising campaign to communication devices associated with target households. A portion of the second advertisements is presented on each of the communication devices. Other embodiments are disclosed.