The present disclosure relates to performing attribution modeling in real time using touchpoint data that correspond to arbitrary analytics parameters (e.g., a user-specified dimension) and are retrieved from a database using an attribution model. For example, in one or more embodiments, a system stores raw data in an analytics database that comprises an aggregator and a plurality of nodes. In particular, each node stores touchpoint data associated with a different user. Upon receiving a query, the system can, in real time, retrieve subsets of the touchpoint data that correspond to a user-specified dimension in accordance with an attribution model. The system then combines the subsets of touchpoint data using the aggregator and generates the digital attribution report using the combined data.

The present disclosure relates to systems, non-transitory computer-readable media, and methods to generate sketches for clearing-bid values and bid-success rates based on multi-dimensional targeting criteria for a digital-content campaign and dynamically determine predicted values for the digital-content campaign based on the sketches. To illustrate, the disclosed systems can use a running-average-tuple-sketch to generate tuple sketches of historical clearing-bid values and tuple sketches of historical bid-success-rates from historical auction data. Based on the tuple sketches, the disclosed systems can determine one or more of a predicted cost per quantity of impressions, a predicted number of impressions, or a predicted expenditure for the digital-content campaign—according to user-input targeting criteria and expenditure constraints.

Methods and apparatus to correct for deterioration of a demographic model to associate demographic information with media impression information are disclosed. An example method includes estimating first and second ages of audience members based on demographic information; estimating a third age of an audience member who is not included in the audience members; applying a window function to the second ages to determine a distribution of ages based on the third age; multiplying window values by the first ages to determine corrected first age components; dividing a total of the corrected first age components by a sum of the window values to determine an estimated age of the audience member at a first time; and determining the corrected age of the audience member at a second time based on the estimated age of the audience member at the first time and a time difference between the first and second times.

To increase the number of views on posting information through an improvement in the quality of the posting information, and thus to improve the utilization rate of advertisement information. A management server device in an SNS system includes a posting display instructor, an advertisement display instructor, an evaluation point receiver, a posting-specific evaluation point calculator, a user-specific evaluation point calculator, a reward point calculator, a total reward point calculator, an exchange rate calculator, and an exchange rate display instructor. The reward point calculator calculates, for each of users, reward points exchangeable for money from reward resources based on user-specific evaluation points. The total reward point calculator calculates total reward points by counting the reward points given to users eligible for rewards from the reward resources. The exchange rate calculator calculates an exchange rate by dividing a reward resource amount by the total reward points. The exchange rate display instructor instructs each of user terminal devices to display the exchange rate.

A method of utilizing Wi-Fi based passive motion detection to deliver targeted advertising through a smart TV is provided. The system uses an agent in connection with the wireless access point that the Smart TV uses to access the internet to make motion determinations. The CSI data of the access point is analyzed to identify if a user is present, if the user is stationary, the previous location of the user, and the activity the user is currently engaged in. An advertisement may be selected based on a last visited location and activity. Such advertisements may further be delivered to more engaged viewers when the advertiser pays a higher rate.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for adjusting physical location usage for a plurality of particular locations. Methods can include obtaining a three-dimensional (3D) representation of the given geographic area, wherein the 3D representation depicts a view of the given geographic area from a specified viewing perspective. For the given geographic area, traffic data is obtained indicating different traffic volumes during different time periods and one or more traffic characteristics. The 3D representation is segmented into a plurality of particular locations. For each particular location among the plurality of particular locations and based on the traffic data, a viewability score is determined that indicates an aggregate amount of time that the particular location is viewable by traffic passing the different locations. Physical location usage is then adjusted based on the viewability scores for the plurality of particular locations.

One or more computing devices, systems, and/or methods for generating dynamic content item recommendations are provided. Content item information, extracted from message data, is aggregated to calculate popularity and attributes of content items. The content items are ranked based upon the popularity and attributes to generate a ranked list of content items. Exploration traffic is served utilizing a set of eligible content items selected from the ranked list of content items. An eligible content item is promoted for participation in auctions for serving non-exploration traffic based upon the eligible content item being served a threshold number of times.

A conversion timing model is model is configured to predict a likelihood of conversion based on an entity's elapsed time since a qualified entry event and based on a funnel state. The conversion timing model is constructed based on a distribution of the conversion timespans of converters. A notification of an opportunity to expose a candidate entity to networked content is received. A time-based likelihood of conversion for the candidate entity is determined by applying the conversion timing model to the elapsed time. A response to the notification based on the likelihood of conversion for the candidate entity is prepared based on the time-based likelihood of conversion and based on the funnel state. Timely responses may include the selection of customized content or bid values.

Techniques to measure consumption of content pages comprising a plurality of distinct content assets are disclosed. In various embodiments, content consumption signal data gathered by a plurality of clients, the content consumption signal data reflecting for at least a subset of content pages user engagement by content asset comprising the content page, is received. The received content consumption signal data and content attribute data associated with each respective content page are used to compute for each content page a content consumption metric reflecting an amount of content determined to have been consumed.

A method of determining a fact of a visit of a user to a point of interest (POI) includes receiving a geo-track generated by a wireless device of the user, generating, based on the geo-track, a dwell profile indicative of the wireless device having been in a pre-defined vicinity of the location of the POI over a pre-determined timeframe, and inputting the dwell profile into a specifically trained Machine Learning Algorithm (MLA). Based on the dwell profile, the MLA returns an indication of whether the user visited the POI. A system and server for executing the method are also provided.