An attribution system aggregates and merges online data and offline chronologically. The attribution system examines merged data for unique visitor (UV) sessions initiated at an online medium (e.g., a website) within an attribution window for a spot that aired on an offline medium (e.g., a television network) and, for each conversion event that occurred in a UV session, assigns a session timestamp to it so that the conversion event is correlated to the spot. The attribution system then determines an overall conversion rate of UVs to the online medium in the attribution window and the attribution by the spot that aired on the offline medium to the overall conversion rate of UVs to the online medium in the attribution window. Results of the offline attribution to the online conversions can be visualized and presented on a client device communicatively connected to the attribution system.

A computing device provides shoppers with a frictionless commerce experience. The computing device determines, tracks, and stores certain physical characteristics and/or attributes of the products selected by a shopper for purchase. The device analyzes these attributes with respect to the shopper's particular purchasing habits and uses the results of that analysis to recommend products to the shopper. Additionally, the computing device may modify the sales price of the product, or augment the shopper's order with the same or similar products, based on the results of the analysis.

An on-demand mobile lawyer method includes receiving a live consultation request from a user, automatically receiving a live-stream of video images of the user and surroundings and storing the video images, automatically searching a plurality of records associated with a plurality of lawyers stored in a remote database, automatically identifying at least one lawyer licensed in a jurisdiction that corresponds to a current location of the user, automatically transmitting at least one notification to the identified at least one lawyer, live-streaming captured video images of the user for viewing by the identified at least one lawyer, automatically receiving and storing live-streaming video images of the identified at least one lawyer in the remote database, and automatically transmitting the live-streaming video images of the identified at least one lawyer to be displayed on a display screen viewable by the user.

Improvements to existing technologies associated with point-of-sale transactions and merchant ecosystems to, among other things, reduce in-person contact and, in some examples, improve the efficiency at which point-of-sale transactions are completed (i.e., reduce friction) are described. In some examples, such reduced in-person contact and/or improved efficiencies can limit transmission of infectious diseases. As such, techniques described are directed to modifying aspects of point-of-sale transactions such that they occur on different computing devices (e.g., customer computing devices instead of merchant computing devices), are automated, and/or occur at different times than with conventional point-of-sale transactions. Furthermore, in at least one example, techniques described can leverage a distributed, network-based merchant ecosystem—comprising multiple merchant computing devices and/or customer computing devices that are specially configured to communicate with a service provider—to facilitate social distancing, which can reduce in-person contact and, in some examples, improve the efficiency at which point-of-sale transactions are completed.

Improvements to existing technologies associated with point-of-sale transactions and merchant ecosystems to, among other things, reduce in-person contact and, in some examples, improve the efficiency at which point-of-sale transactions are completed (i.e., reduce friction) are described. In some examples, such reduced in-person contact and/or improved efficiencies can limit transmission of infectious diseases. As such, techniques described are directed to modifying aspects of point-of-sale transactions such that they occur on different computing devices (e.g., customer computing devices instead of merchant computing devices), are automated, and/or occur at different times than with conventional point-of-sale transactions. Furthermore, in at least one example, techniques described can leverage a distributed, network-based merchant ecosystem—comprising multiple merchant computing devices and/or customer computing devices that are specially configured to communicate with a service provider—to facilitate social distancing, which can reduce in-person contact and, in some examples, improve the efficiency at which point-of-sale transactions are completed.

Systems and methods for providing product samples to users in autonomous vehicles, thereby allowing businesses to advertise their products via the rideshare platform. A physical advertising platform is provided leveraging existing rideshare and delivery infrastructure to allow businesses to advertise their products by providing samples in rideshare vehicles and/or with rideshare vehicle deliveries. Consumers have the opportunity to try new products from local businesses that they may otherwise not be exposed to. In some implementations, a rideshare application interface can allow users to see what new local product samples are available. In some examples, a user can select one or more product samples to try.

Systems and methods for providing product samples to users in autonomous vehicles, thereby allowing businesses to advertise their products via the rideshare platform. A physical advertising platform is provided leveraging existing rideshare and delivery infrastructure to allow businesses to advertise their products by providing samples in rideshare vehicles and/or with rideshare vehicle deliveries. Consumers have the opportunity to try new products from local businesses that they may otherwise not be exposed to. In some implementations, a rideshare application interface can allow users to see what new local product samples are available. In some examples, a user can select one or more product samples to try.

An online system receives a content item including a link to a landing page and determines a likelihood the landing page violates an online system policy based on a structural similarity between the landing page and a web page violating the policy. To determine the likelihood, the online system determines a hierarchical structure associated with the web page violating the policy and an additional hierarchical structure associated with the landing page. The hierarchical structure represents a structure of at least a portion of the web page and the additional hierarchical structure represents a structure of a corresponding portion of the landing page. The online system compares the hierarchical structure and additional hierarchical structure. Based on the comparison, the online system computes a measure of dissimilarity between the hierarchical structure and additional hierarchical structure and determines a likelihood the landing page violates the policy based on the measure of dissimilarity.

An online system receives a content item including a link to a landing page and determines a likelihood the landing page violates an online system policy based on a structural similarity between the landing page and a web page violating the policy. To determine the likelihood, the online system determines a hierarchical structure associated with the web page violating the policy and an additional hierarchical structure associated with the landing page. The hierarchical structure represents a structure of at least a portion of the web page and the additional hierarchical structure represents a structure of a corresponding portion of the landing page. The online system compares the hierarchical structure and additional hierarchical structure. Based on the comparison, the online system computes a measure of dissimilarity between the hierarchical structure and additional hierarchical structure and determines a likelihood the landing page violates the policy based on the measure of dissimilarity.

Embodiments of systems and methods for the aggregation, analysis, display and monetization of pricing data for commodities in general, and which may be particularly useful applied to vehicles are disclosed. Specifically, in certain embodiments, historical transaction data associated with a particular vehicle configuration may be obtained and processed to determine pricing data associated with the vehicle configuration. The historical transaction data or determined pricing data may then be presented in an intuitive manner.