Systems and methods for using wireless communication devices to track the effects of advertising are described herein. In some embodiments, a method includes representing the identity of an advertising impression, that is, a specific advertisement, with an impression code. According to exemplary embodiments, the advertising impression is directed to at least one commodity, such as one or more products and services. The method may also further include receiving the impression into a computer-readable memory of a wireless communication device. The method further includes detecting the wireless communication device, and then providing the impression code during the purchase of the commodity. The method continues with obtaining the identity of the advertising impression from the impression code. The method additionally includes creating a transaction record, wherein the transaction record includes the advertising impression identity and an identity of the commodity, and storing the transaction record in a database.

Techniques for optimizing content item delivery for installations or activations of a mobile application are provided. In one technique, a machine-learned model is trained based on multiple training instances that individually indicate whether an entity performed a particular action relative to a mobile application. In response to receiving a content item request from a third-party content delivery exchange, it is determined whether a client device that initiated the content item request has activated a particular application. In response to determining that the client device has not activated the particular application, multiple feature values of the content item request are identified. Based on inputting the feature values into the model, a score is generated that indicates a likelihood that an entity of the client device will perform the particular action relative to the particular application. Based on the score, a content item is transmitted over a network to the client device.

An audience measurement service may monitor broadcasts in a region, ingesting closed captioning data, metadata, displayed text or logos, performing facial recognition on people, and/or generating audio/video fingerprints of broadcast content to create a database of content and associated keywords, along with times at which the content was broadcast. The audience measurement service may receive user search queries from a search provider and detect spiking queries. The audience measurement service may determine whether the spiking queries are related, contextually and temporally, to an item of content identified in the database, and infer that users generating the queries likely viewed the item of content. In some implementations, the audience measurement service may also infer that the users likely viewed other items of content (e.g. advertisements) displayed during the prior or subsequent few minutes on the same broadcast channel as the query-triggering item.

Embodiments of the invention overcome the shortcomings of prior art by transforming the understanding of how different creative placements and location helps drive sales and other KPIs to a computerized methodology that may allow advertising planners and buyers to generate plans that meet these expectations on effectiveness of their advertising campaign. Aspects of the invention fusing the probability of exposure estimates with segment level data to provide layers of intelligence in determining the probability estimates for sales conversion or other KPIs. Moreover, aspects of the invention may predict based on various models the reach and frequency relationship tradeoff for different impression levels.

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.

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.

A system and method for the presentation of advertisements is present. According to one embodiment, a number of impressions of an advertisement message are presented over a computer network such as the Internet to a variety of viewer computers. Depending on the actions taken by the viewers (e.g., whether the Viewer selects the advertising message and accesses a web-link to the advertiser's web-site), bonus exposure (e.g., an additional number of impressions provided to the viewers) of the advertising message is given.

The present disclosure relates to systems and methods for personalized recommendation. The systems may perform the methods to detect an application executing on the user terminal. The systems may perform the methods to communicate with the application with respect to a service request sent by the user via the user terminal. The systems may perform the methods to obtain one or more current context-related features and one or more current-user-related features with respect to the user, and a plurality of candidate recommendation items. The systems may perform the methods to select a target recommendation item from the plurality of candidate recommendation items based on the one or more current context-related features and the one or more current user-related features, using a trained recommendation model, and provide the target recommendation item to the application to generate a presentation, on a display of the user terminal of the user.

A system and process to determine the causal relationship between advertisement delivery data and sales data are disclosed. According to one embodiment, a method comprises importing advertisement data and sales data. The advertisement data and the sales data are joined to generate a joined data set. Customer journeys are generated for a timeframe from the joined data set. A first group of customers who saw an advertisement of interest are identified. A second group of customers who did not see the advertisement of interest are identified. Each customer of the first group is matched to a customer in the second group who is similar to the customer of the first group. An average treatment effect for the advertisement of interest is calculated.

The present disclosure may provide a stand-alone application, API, or SDK, configured to, for example, but not be limited to: i) register digital assets, physical assets, virtual assets, brand assets, media assets, and mobile assets associated with a platform user; ii) associate content to be delivered in response to an activation of those assets, including interactivity criteria, if applicable; iii) specify triggers for delivering the content and target consumer profiles for receiving the content; and iv) transmit content for engaging the consumer at the right time and/or place, with the targeted profile, and v) track user engagement and provide analytics on consumer engagement.