Disclosed is a method and system (collectively platform) of geolocation and time based advertising. The platform may include receiving, using a communication interface, a first geolocation from a client device. Further, the platform may include, receiving, using the communication interface, an advertisement content from the client device. Additionally, the platform may include creating, using the processor, an association between the first geolocation and the advertisement content. Further, the platform may include storing, using a storage device, each of the first geolocation, the advertisement content and the association. Furthermore, the platform may include receiving, using the communication interface, a second geolocation from a client device. Additionally, the platform may include comparing, using the processor, the second geolocation with the first geolocation. Further, the platform may include transmitting, using the communication interface, the advertisement content to the client device based on the comparison.

Systems and methods for getting and using reaction and feedback on contents presented at a device. In an aspect, viewing time of a user is measured by eye-tracking method, and used to conduct analysis, change contents, charge sponsors, award the user, or charge the user. Moreover, other methods are also used to detect user reaction and feedback and respond to user request. In other aspects, contents are provided partially free and free time periods are offered for multiple presentation segments of a program.

A computer-implemented method for selecting a digital content, comprising: receiving a plurality of samples, each comprises a request having a plurality of values of a plurality of attributes, and associated with a success value for a Bernoulli distributed event having a campaign and a bid rate (BR) of the campaign; clustering the plurality of samples in a plurality of homogenous nodes according to respective plurality of values; identifying a group campaign with a highest valuation for each one of the plurality of nodes using triangular approximation of the Bernoulli distribution of events in the node; receiving a query from a device including a plurality of other values of the plurality of attributes; selecting one of the plurality of nodes; selecting a digital content of the group campaign with highest valuation identified for the selected node; and generating a response to the query including the selected content.

An example method to adjust demographic data involves generating a first model based on reference demographic data corresponding to panelists, and based on first age data and a quantity of mobile webpage views from a database proprietor that is separate from a first entity, the reference demographic data collected from the panelists and stored by the first entity, and the first age data and the quantity of mobile webpage views corresponding to ones of the panelists having user accounts with the database proprietor; and based on determining that redistributing at least some of the first age data will increase an age data accuracy, redistributing the at least some of the first age data across age categories to generate a second model, the second model to facilitate adjusting second age data of the database proprietor to correct inaccuracies and/or misrepresentations in at least some of the second age data.

Systems and methods are disclosed for managing the display of online ad content consistent with one or more e-commerce objectives. A collection module may be operable to collect attribute values for a set of attributes characterizing user visits to a set of training webpages and subsequent attribute values for a subsequent user visit to a subsequent webpage. A model-generation module may be operable to train a probability model with the attribute values that predicts outcomes for at least one performance metric. A display module may be operable to determine whether to display ad content on the subsequent webpage for the subsequent user visit depending on whether a predicted outcome from the probability model that is relevant to the subsequent attribute values is consistent with one or more e-commerce objectives. The probability model may be a decision tree with different predicted outcomes for different combinations of attribute values.

Introduced herein are techniques for bringing scented advertisements into digital content (e.g., visual content and non-visual content). Such technology is able to address a fundamental challenge that is inherent in digital transactions, namely, an inability to accurately gauge different characteristics of a product. Several embodiments pertain to scent delivery systems that are able to produce scent(s) as part of a direct advertising campaign or an indirect advertising campaign. More specifically, a scent delivery system may be configured to produce scents that correspond to features of the digital content. For example, different scented materials can be dispensed based on characteristics of a product that is the subject of a scented advertisement.

Introduced herein are techniques for bringing scented advertisements into digital content (e.g., visual content and non-visual content). Such technology is able to address a fundamental challenge that is inherent in digital transactions, namely, an inability to accurately gauge different characteristics of a product. Several embodiments pertain to scent delivery systems that are able to produce scent(s) as part of a direct advertising campaign or an indirect advertising campaign. More specifically, a scent delivery system may be configured to produce scents that correspond to features of the digital content. For example, different scented materials can be dispensed based on characteristics of a product that is the subject of a scented advertisement.

Introduced herein are techniques for bringing scented advertisements into digital content (e.g., visual content and non-visual content). Such technology is able to address a fundamental challenge that is inherent in digital transactions, namely, an inability to accurately gauge different characteristics of a product. Several embodiments pertain to scent delivery systems that are able to produce scent(s) as part of a direct advertising campaign or an indirect advertising campaign. More specifically, a scent delivery system may be configured to produce scents that correspond to features of the digital content. For example, different scented materials can be dispensed based on characteristics of a product that is the subject of a scented advertisement.

Introduced herein are techniques for bringing scented advertisements into digital content (e.g., visual content and non-visual content). Such technology is able to address a fundamental challenge that is inherent in digital transactions, namely, an inability to accurately gauge different characteristics of a product. Several embodiments pertain to scent delivery systems that are able to produce scent(s) as part of a direct advertising campaign or an indirect advertising campaign. More specifically, a scent delivery system may be configured to produce scents that correspond to features of the digital content. For example, different scented materials can be dispensed based on characteristics of a product that is the subject of a scented advertisement.

A computer-implemented method for optimizing publisher profits in online advertising based on real market movements is provided. The method may include dividing an advertisement (ad) placement for an ad unit into a plurality of levels. The method may also include generating a plurality of variables that are configured to test for the real market movements between levels. The method may further include processing ad impressions based on the plurality of variables within a time period to evaluate the real market movements for the ad unit, and determining whether to adjust one or more of the minimum floor prices based on a score for each variable calculated within the time period.