Abstract: An embodiment may involve receiving, from one or more server devices, representations of past amounts spent on paid search engine listings for a web site and representations of paid search conversions involving the web site that are attributable to the paid search engine listings. The embodiment may also involve receiving representations of past amounts spent on the display promotions for the web site and representations of display conversions involving the web site. The embodiment may also involve receiving a request for a graphical representation of the cross-channel performance of the web site with respect to conversions. In response to receiving the request for the graphical representation of the cross-channel performance of the web site, the computing system may transmit the graphical representation of the cross-channel performance of the web site.

Abstract: An embodiment may involve receiving input information related to an offered product or service, two or more layouts of a print advertisement for the offered product or service, demographics of potential buyers of the offered product or service, and online behavior of the potential buyers. The information may be normalized into a predefined schema for a machine-learning-based recommendation engine operated by a computing device. The embodiment may further involve determining respective selections of the two or more layouts for the potential buyers. The machine-learning-based recommendation engine may select a layout for a potential buyer based on the offered product or service, content and organization of the layout, demographics of the potential buyer, and online behavior of the potential buyer. The embodiment may also involve transmitting, to a printing system, one or more output files representing the offered product or service, the layout, and the potential buyer.

Abstract: An embodiment may involve receiving textual search queries that were entered into a web site. The embodiment may further involve generating a set of conforming textual search queries by removing, from the textual search queries, those that contain non-alphanumeric characters, more than a threshold number of characters, or are duplicates of another of the textual search queries. The embodiment may further involve applying pre-defined transformation rules to the conforming textual search queries to create records respectively associated with the conforming textual search queries, wherein each of the records contains a particular conforming textual search query, a reference to a web page on the web site containing content related to the particular conforming textual search query, and text describing a category of the particular conforming textual search query. The embodiments may further involve transmitting, to an Internet search engine, one or more files containing the records.

Abstract: An embodiment may involve receiving input information related to an offered product or service, two or more layouts of a print advertisement for the offered product or service, demographics of potential buyers of the offered product or service, and online behavior of the potential buyers. The information may be normalized into a predefined schema for a machine-learning-based recommendation engine operated by a computing device. The embodiment may further involve determining respective selections of the two or more layouts for the potential buyers. The machine-learning-based recommendation engine may select a layout for a potential buyer based on the offered product or service, content and organization of the layout, demographics of the potential buyer, and online behavior of the potential buyer. The embodiment may also involve transmitting, to a printing system, one or more output files representing the offered product or service, the layout, and the potential buyer.

Abstract: An embodiment may involve receiving input information related to an offered product or service, two or more layouts of a print advertisement for the offered product or service, demographics of potential buyers of the offered product or service, and online behavior of the potential buyers. The information may be normalized into a predefined schema for a machine-learning-based recommendation engine operated by a computing device. The embodiment may further involve determining respective selections of the two or more layouts for the potential buyers. The machine-learning-based recommendation engine may select a layout for a potential buyer based on the offered product or service, content and organization of the layout, demographics of the potential buyer, and online behavior of the potential buyer. The embodiment may also involve transmitting, to a printing system, one or more output files representing the offered product or service, the layout, and the potential buyer.

Abstract: An embodiment may involve repeatedly receiving, from one or more social network advertising service devices at which one or more social network advertising campaigns are or have been operated, updates to information related to social network advertisement placement and social network advertisement performance over a previous period of time. The embodiment may involve transmitting, for display on a graphical user interface of a client device, representations of the social network advertisement placement and the social network advertisement performance over the previous period of time. The embodiment may involve receiving, via the selectable graph menu options, a selection of two of the plurality of advertising metrics. The embodiment may involve transmitting, for display on the graphical user interface, data representing values of the selected two metrics over the previous period of time.

Abstract: An embodiment may involve receiving, from a third-party computing device, a bulk representation of textual search engine queries, and in response to receiving the bulk representation, processing each textual search engine query. The processing may include detecting non-conforming textual search engine queries and generating respective online advertising information for the conforming textual search engine queries. The embodiment may further involve transmitting, to a server device, at least one file representing the respective online advertising information for the conforming textual search engine queries. Reception of the at least one file and a subsequent command by the server device may cause a search engine device to carry out paid search advertising with the conforming textual search engine queries as keywords and in accordance with the respective online advertising information for the conforming textual search engine queries.

Abstract: An embodiment may involve receiving input information related to an offered product or service, two or more layouts of a print advertisement for the offered product or service, demographics of potential buyers of the offered product or service, and online behavior of the potential buyers. The information may be normalized into a predefined schema for a machine-learning-based recommendation engine operated by a computing device. The embodiment may further involve determining respective selections of the two or more layouts for the potential buyers. The machine-learning-based recommendation engine may select a layout for a potential buyer based on the offered product or service, content and organization of the layout, demographics of the potential buyer, and online behavior of the potential buyer. The embodiment may also involve transmitting, to a printing system, one or more output files representing the offered product or service, the layout, and the potential buyer.

Abstract: An embodiment may involve receiving, from a search engine device at which a web site is registered, updates to search engine performance information of the web site. The embodiment may further involve receiving, from one or more traffic tracking service devices, updates to traffic information for the web pages. The embodiment may further involve receiving, via selectable controls on a graphical user interface of a client device, a selection of two or more of a plurality of metrics related to the search engine performance information and the traffic information. The embodiment may further involve transmitting, to the client device, graph data representing values of the selected two metrics over a pre-defined period of time. Reception of the graph data may cause the client device to plot, on the graphical user interface, a graph indicating the values of the selected two metrics over the pre-defined period of time.

Abstract: An embodiment may involve repeatedly receiving, from one or more online advertising service devices at which one or more web-based display advertising campaigns are operated, updates to information related to display advertisement placement and display advertisement performance associated with the one or more web-based display advertising campaigns. The information may include a plurality of metrics. The embodiment may further involve receiving, via selectable controls on a graphical user interface of a client device, a selection of two of the plurality of metrics. The embodiment may also involve transmitting, for display on the graphical user interface, data representing values of the selected two metrics over a pre-defined period of time. Reception of the data may causes the client device to plot a graph indicating the values of the selected two metrics over the pre-defined period of time, where the values as shown in the graph for each of the selected two metrics are normalized to one another.

Abstract: An embodiment may involve receiving, from one or more server devices, representations of past amounts spent on paid search engine listings for a web site and representations of paid search conversions involving the web site that are attributable to the paid search engine listings. The embodiment may also involve receiving representations of past amounts spent on the display promotions for the web site and representations of display conversions involving the web site. The embodiment may also involve receiving a request for a graphical representation of the cross-channel performance of the web site with respect to conversions. In response to receiving the request for the graphical representation of the cross-channel performance of the web site, the computing system may transmit the graphical representation of the cross-channel performance of the web site.

Abstract: An embodiment may involve receiving, from one or more online advertising service devices at which one or more online advertising campaigns are operated, updates to information related to online advertisement placement and online advertisement performance associated with the one or more online advertising campaigns. The information may include a plurality of metrics. The embodiment may also involve receiving, via selectable graph menu options on a graphical user interface of a client device, a selection of two of the plurality of metrics. The embodiment may further involve transmitting, for display on the graphical user interface, data representing values of the selected two metrics over a pre-defined period of time. Reception of the data may cause the client device to plot a graph indicating the values of the selected two metrics over the pre-defined period of time.

Abstract: An embodiment may involve obtaining a recipient-specific record of interaction data for a particular recipient, the recipient-specific record including, for each of a plurality of electronic communications: (i) a respective timestamp indicating a time the respective electronic communication was transmitted and (ii) a respective indication of whether a client device requested a respective web resource using an individual identifier embedded in the respective electronic communication.

Abstract: An embodiment may include repeatedly receiving, from one or more online advertising service devices at which a plurality of advertising campaigns are operated, updates to advertising spending amounts on keywords associated with one or more particular advertising campaigns. The embodiment may also involve repeatedly receiving, from the one or more online advertising service devices, updates to respective quality scores associated with the keywords. The embodiment may further involve providing, for display on a graphical user interface, respective line items for the plurality of advertising campaigns. A line item for the one or more particular advertising campaigns may include one or more of: (i) a first representation of a total advertising spending amount for keywords associated with the one or more particular advertising campaigns, (ii) a second representation of a total number of the keywords, or (iii) a third representation of an average quality score for the keywords.

Abstract: An embodiment may include repeatedly receiving, from one or more online advertising service devices at which a plurality of advertising campaigns are operated, updates to an advertising spending amount for one or more particular advertising campaigns. The embodiment may also include repeatedly receiving, from one or more traffic tracking service devices, updates to an advertising conversion amount for the one or more particular advertising campaigns. The embodiment may further include providing, for display on a graphical user interface, a line item for the one or more particular advertising campaigns including: a first representation of the advertising spending amount compared to an advertising spending goal, and a second representation of the advertising conversion amount compared to an advertising conversion goal. The first representation may be highlighted when the advertising spending amount deviates by more than a threshold extent from the advertising spending goal.