Abstract: A method is disclosed for tracking advertisement effectiveness. First information associated with desired advertising information is broadcast from at least one of a plurality of fixed information nodes. A mobile unit receives the broadcast information and outputs the desired advertising information. An advertisement counter is started at the time of receipt of the broadcast information and presence information is broadcast from at least one of a plurality of fixed monitoring nodes over a restricted broadcast range, which at least one fixed monitoring node is disposed in a predetermined fixed physical proximity with a vendor location. The broadcast presence information is received at the mobile unit and a presence counter is started in response to receipt of the presence information. At the mobile unit loss of receipt of the broadcast presence information, the presence counter is stopped.

Abstract: Methods and systems are described for dynamic ad selection of ads stored on a device. In one embodiment, a device includes a storage medium to store software programs including advertising services software and software applications. Processing logic is coupled to the storage medium and a display device. The processing logic is configured to execute instructions of at least one of the software programs to receive user input for initiating a software application on the device, determine attributes for the device including software applications currently operating in the storage medium and placement information for the initiated software application, and dynamically select one of the video ads stored on the device based on the attributes including software applications currently operating in the storage medium and placement information for the initiated software application.

Abstract: Techniques are provided that include targeting a user of a mobile electronic device with an interest-based advertisement, based at least in part on various call logs on a user device. Techniques are provided in which a set of calls from a user's call log from a mobile device are assigned to one or more categories indicative of potential user interests for the purposed of targeted advertisements. The usage pattern of the user's call log takes into account the time of the day, week, and/or month that the user tends to make particular calls to determine recurring patterns and calculate individual metrics for comparison with other users.

Abstract: Methods, apparatuses, and computer-readable media for serving annotations are disclosed. When a contact of a user recommends an ad, the score of the ad may be boosted in an ad auction. The amount of boosting depends on contact affinity. Contacts with greater contact affinity may be more influential, and ads that are recommended by such contacts may have a higher click-through rate. The greater the affinity between the user and contact, the greater the boost to the ad score. Affinity may be measured by a weight value, which is determined by, for example, social network interactions, e-mail/instant messaging communications, and phone logs and contact lists.

Abstract: Methods and apparatus to determine efficiencies of media delivery across platforms are disclosed. An example method includes measuring, with a sensor, first neuro-response data from a person when exposed to media output via a first media delivery platform type. Measuring second neuro-response data from the person when exposed to media output via a second media delivery platform type, different than the first media delivery platform type. Accessing a first and second performance metric for the respective media delivery platform type, the performance metrics based on a first and second reach of the respective media delivery platform types with respect to a target group of audience members. Accessing a first and second effectiveness metric for the respective media delivery platform types, the effectiveness metric based on the respective neuro-response data. Rating at least one of the first or second media delivery platform types based on the first and the second platform metrics.

Abstract: A location based router system comprises a router in communication with an ad hoc network of devices, including at least one mobile device. The router directs packets from the network to associated agents. The router receives queries from requesting clients, such as the mobile device, and provides location to the requesting client. Additionally, depending on preferences of the client, it also routes market packets for location based services back to the mobile device dependent on its location. A method of providing location based service to a mobile device in a wireless network. The method receives a query for location in the wireless network from the wireless device. The query includes an opt-in level for participating in offers for location based services. Mobile device location computed from packets transmitted between the mobile device and nodes in the wireless network is determined.

Abstract: Targeting advertisements to a user on multiple devices includes: selecting an access point; maintaining an internet access log to track web activity across multiple devices within said access point; identifying the multiple devices involved in the web activity; distinguishing patterns of web activity for the multiple devices to identify users of the devices; generating a user interest vector populated with user interests derived from the patterns of web activity; initializing a master log of user interest vectors for all users within the access point, wherein the master log maps the users with the multiple devices; and updating the master log.

Abstract: A social networking system user interacts with a terminal associated with a brand, such as kiosk included in a retail location associated with the brand. The terminal provides authorization information to a user device that identifies the terminal and the brand associated with the terminal. Information identifying the user and the authorization information is communicated to the social networking system, which retrieves interactions between the user and objects associated with the brand in the social networking system. The retrieved interactions are communicated to the terminal, which generates content describing the user's interactions with the objects and presents the generated content to the user. A description of the user interaction and/or of the generated content may be communicated to the social networking system for distribution to additional users.

Abstract: Systems and methods are disclosed herein for generating reminders to shoppers to purchase products. Using a customer's current location, products stocked at that location are identified and compared to the customer's purchase history. Items regularly purchased by the customer found among the products stocked at the location are identified. Upon departing the location without adding the product to an electronic shopping cart an alert may be generated to remind the customer to purchase the product. In some embodiment, an alert is generate for a product found in the purchase history if an elapsed time since purchase of the product exceeds an expiration period or purchase period for that product. The methods disclosed herein may be used in the context of a self-checkout using an electronic shopping cart and navigational aids to facilitate retrieval of items on a shopping list.

Abstract: Techniques are provided that include targeting a user of a mobile electronic device with an interest-based advertisement, based at least in part on various call logs on a user device. Techniques are provided in which a set of calls from a user's call log from a mobile device are assigned to one or more categories indicative of potential user interests for the purposed of targeted advertisements. The usage pattern of the user's call log takes into account the time of the day, week, and/or month that the user tends to make particular calls to determine recurring patterns and calculate individual metrics for comparison with other users.

Abstract: Methods and apparatus to determine efficiencies of media delivery across platforms are disclosed. An example method includes obtaining a first effectiveness metric for a first platform, obtaining a first reach of the first platform with respect for a target group of audience members, and calculating a first performance metric based on the first effectiveness metric and the first reach.

Abstract: A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires. In one aspect, the detailed technology concerns phone-based cognition of a scene viewed by the phone's camera. The image processing tasks applied to the scene can be selected from among various alternatives by reference to resource costs, resource constraints, other stimulus information (e.g., audio), task substitutability, etc. The phone can apply more or less resources to an image processing task depending on how successfully the task is proceeding, or based on the user's apparent interest in the task. In some arrangements, data may be referred to the cloud for analysis, or for gleaning. Cognition, and identification of appropriate device response(s), can be aided by collateral information, such as context. A great number of other features and arrangements are also detailed.

Abstract: Identifying on-line advertising conversions includes identifying, at a computer server system, a plurality of reports from one or more computing devices, wherein each of the reports indicates a clock skew between one of the computing devices and a clock server system; using the clock skews to determine that two or more of the reports are likely from a common computing device; determining that the two or more of the reports are common, in that they correspond to display of an advertisement on the common computing device and to purchase of on-line content with the common computing device; and indicating that a purchase conversion occurred based on determining that the two or more of the reports are common.