In some examples, a service provider may determine, for a time of day and a day of a week, orders received by individual merchants of a plurality of merchants over a past period of time. The service provider may further determine, for the time of day and day of the week, based at least in part on the orders received over the past period of time, a first merchant predicted to receive an order. Based at least in part on a pickup location of the first merchant, the service provider may send a communication to a first courier device associated with a first courier of a plurality of couriers. For example, the communication may include location information for a recommended location to which the first courier is to move to be in position for picking up an order from the merchant that is predicted to receive the order.

An intent score is assigned to users who are viewing online ads. Users define a bid-range and adjust pricing within the range at an individual user level, based on an intent score that is derived from user activity. An advertiser typically defines a bid range. If the user then interacts with ads or visits the advertiser's website then, based on user actions, the bid price is revised. This process of bid price revision is continuous and results in increased or decreased bid prices for individual users. All participating users and their intent scores are periodically uploaded to RTB platforms where they are used to purchase ad impressions. This increases the likelihood of winning bids for more valuable users with better precision without raising bid prices for entire segments of users.

For an advertising campaign, an ad scheduler receives input from a user. The input includes a region for an ad campaign, a start date for the ad campaign and an estimated number of impressions within a set period of time for the ad campaign. The ad scheduler schedules the ad campaign in an ad scheduling calendar. A plurality of digital billboards located within the region for the ad campaign displays ads for the ad campaign. The plurality of digital billboards is controlled by at least one billboard terminal.

In an embodiment, a reservation server runs a reservation service that allows users of diner clients to reserve reservations with one or more restaurants. In addition, the reservation server runs a self-serve promotion service that restaurant clients to request automatic or semi-automatic generation of content displays for promotions. In some cases, the reservation server uses statistics to predict future periods of time when covers for a restaurant will be below average. The reservation server then automatically generates a promotion that is likely to increase covers during the previously predicted future periods of time. In response to the promotion being selected by a user, the reservation server generates a content display that is subsequently published to the reservation service. As a result, the content display is presented to users of the diner clients when searching for criteria satisfied by the restaurant.

Access requests to a database are monitored for average time taken to fulfill the requests and whether a queue of unfulfilled requests is building up beyond an acceptable threshold. When the queue has built up beyond the acceptable threshold and/or when the average time taken to fulfill the requests has exceeded a delay threshold value, database access requests may be rejected. In one advantageous aspect, a graceful degradation in performance may be achieved by selectively rejecting access requests of a lower priority and favoring access requests of a higher priority for execution.

An online system selects content items for a user to increase probabilities of the user remembering the content items after presentation. The online system generates one or more models based on information describing amounts of time users have viewed previously presented content items. Hence, a model associated with a user predicts an amount of time the user will view a content item. When selecting content items for the user, the online system selects one or more content items that the user is predicted to view for an amount of time within a specific range, which may be based on amounts of times other users have viewed the content item or content items similar to the content item. For example, the online system increases a probability of selecting a content item the user is predicted to view for an amount of time within the specific range.

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 a platform Admin (e.g., an AppAddress), ii) associate content to be delivered in response to an activation of those assets (e.g., an AdDrop), including interactivity criteria, if applicable, iii) specify triggers for delivering the AdDrop (e.g., space/time/event) and target consumer profiles for receiving the AdDrop (e.g., Gender/Demographic/Propensity/Interest/Behavior/Etc.), iv) transmit interactive AdDrop for engaging the consumer at the right time/place, with the targeted profile, and v) track user engagement and provide analytics on consumer engagement.

An advertisement system and method of identifying targeted advertisements for presentation to one or more viewers. In one aspect, the invention may be a method of identifying targeted advertisements for presentation to one or more viewers, the method comprising: receiving a map based on one or more advertising groups and characterization information derived from at least one of the viewers; and transmitting to equipment associated with the viewers, one or more advertisements each having one or more advertising group identifier, wherein an advertising group identifier matches an advertising group within the map.

Techniques for scheduling deals based on predicted user locations are described herein. In particular implementations, a service provider may aggregate location information for multiple users. In one example, the location information comprises check-in information shared by a user through a location-based service. The service provider may utilize the aggregated location information to predict future user traffic for a geographical region associated with a deal or a merchant of the deal. In some instance, the deal comprises an offer of an item for acquisition at a discounted value for a period of time, such as a period of hours, days, or weeks. The predicted user traffic may be used by the service provider, merchant, or others to identify the time period and discounted value at which to offer the deal for acquisition.

Methods and systems for dynamically incorporating advertising content into multimedia environments, such as games, are provided. Example embodiments include a dynamic inserter, which selects content, based upon a set of criteria, to deliver to a receiving client system, such as a game client. The game client typically dynamically determines locations with the game where advertisements may be inserted. Associated with these locations are ad tags that specify criteria for the ads. For example, the criteria may include ad type, ad genre, and scheduling information. The game client then sends indications of these ad tags to the dynamic inserter to be used to select appropriate ads. The dynamic inserter selects ads based upon the criteria and sends them to the game client, which selects them for ad tags with conforming criteria. The game client then renders the selected ad in the appropriate location. In one embodiment, the dynamic inserter comprises a game client, game server, ad server, a communications channel, and, optionally, an ad client.