Patent Application
20140040009
For online advertisers, advertising campaign performance information is vitally important. But displays of internet advertising metrics associated with an advertising campaign, or keywords associated therewith, are frequently limited to a textual or table format. Navigating such data to optimize keyword performance can be inefficient, time consuming, and even error prone. For example, users oftentimes obtain keyword data from a data table for keywords having one keyword per row. A typical advertiser may have 1500 keywords and, as such, will have 1500 data rows (approximately 50 pages) to decipher. Thus, it is difficult for the advertiser to gain a comprehensive view of how well, for example, a particular advertising keyword is performing relative to other keywords within an advertising campaign or an advertiser's advertising account.
This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
Embodiments of the present invention relate to systems, methods, and computer-readable media for, among other things, generating and presenting a graphical user interface that allows a user to view one or more metrics related to a discrete subject matter and filter such metrics. This is useful across a broad spectrum of fields. For example, a person in the financial field would like to view multiple financial metrics at the same time such as cost, spend, return on investment, and the like. More specifically, embodiments of the present invention enable an advertiser to view one or more internet advertising metrics related to an advertising campaign in a corresponding keyword stack. Each keyword stack is associated with a particular metric and is a distribution graph of keywords on the corresponding metric. A user can interact with one or more represented keywords within the keyword stack to filter additional keyword stacks associated other metrics so that such keyword stacks visually distinguish or display the corresponding keyword representations. Implementing embodiments of the present invention enables an advertiser to efficiently and accurately analyze keywords within an advertising campaign or account such that the advertiser can easily identify high-impact keywords and thereby optimize his or her advertisements.
The present invention is described in detail below with reference to the attached drawing figures, wherein:
The subject matter of the present invention is described with specificity herein to meet statutory requirements. However, the description itself is not intended to limit the scope of this patent. Rather, the inventors have contemplated that the claimed subject matter might also be embodied in other ways, to include different steps or combinations of steps similar to the ones described in this document, in conjunction with other present or future technologies. Moreover, although the terms “step” and/or “block” may be used herein to connote different elements of methods employed, the terms should not be interpreted as implying any particular order among or between various steps herein disclosed unless and except when the order of individual steps is explicitly described.
Various aspects of the technology described herein are generally directed to systems, methods, and computer-readable media for, among other things, generating and presenting a graphical user interface that allows a user to view one or more metrics related to a discrete subject matter and filter such metrics. This is useful across a broad spectrum of fields. For example, a person in the financial field would like to view multiple financial metrics of stocks or bonds at the same time such as cost, spend, return on investment, and the like. More specifically, embodiments of the present invention enable an advertiser to view one or more internet advertising metrics of keywords related to an advertising campaign in a corresponding keyword stack. Each keyword stack is associated with a particular metric and is a distribution graph of keywords on the corresponding metric. A user can interact with one or more represented keywords within the keyword stack to filter additional keyword stacks associated other metrics so that such keyword stacks visually distinguish or display the corresponding keyword representations. Implementing embodiments of the present invention enables an advertiser to efficiently and accurately analyze keywords within an advertising campaign or account such that the advertiser can easily identify high-impact keywords and thereby optimize his or her advertisements.
Accordingly, in one embodiment, the present invention is directed toward a graphical user interface for displaying keyword stacks, stored on one or more computer-readable media and executable by a computing device. The graphical user interface includes a keyword-stack display area configured to display one or more keyword stacks, each of the one or more keyword stacks associated with an internet advertising metric, wherein each keyword stack displays a keyword representation for each keyword within an advertising campaign with the keyword representation being vertically positioned in association with a corresponding value for the metric. The graphical user interface also includes a keyword grid display area configured to display a table of keywords and corresponding metric values for a plurality of metrics.
In another embodiment, the present invention is directed toward a computerized method. The computerized method includes receiving an indication to display a set of keyword stacks, each of the keyword stacks being associated with a different internet advertising metric. Keyword data associated with each of the internet advertising metrics is referenced. The keyword data associated with each of the internet advertising metrics are used to generate each of the keyword stacks. Each of the keyword stacks includes a plurality of horizontal bars vertically stacked with each horizontal bar representing a number of keywords falling within a particular metric measurement, or range thereof, corresponding with a vertical axis.
In yet another embodiment, the present invention is directed to one or more computer-readable storage media. The method includes presenting a first keyword stack and a second keyword stack. The first keyword stack and the second keyword stack are associated with a different keyword metric that indicates performance of keywords. Further, the first keyword stack and the second keyword stack include a representation of each keyword within an advertising campaign or an advertising account. Thereafter, an indication of a selection of a set of one or more keyword representations within the first keyword stack is received. Based on the selection, keyword representations within the second keyword stack are automatically filtered such that keyword representations within the second keyword stack that correspond with the selected one or more keyword representations within the first keyword stack are visually distinguished.
An exemplary computing environment suitable for use in implementing embodiments of the present invention is described below in order to provide a general context for various aspects of the present invention. Referring to
Embodiments of the invention may be described in the general context of computer code or machine-useable instructions, including computer-executable instructions such as program modules, being executed by a computer or other machine, such as a personal data assistant or other handheld device. Generally, program modules, including routines, programs, objects, components, data structures, etc., refer to code that performs particular tasks or implements particular abstract data types. Embodiments of the invention may be practiced in a variety of system configurations, including hand-held devices, consumer electronics, general-purpose computers, more specialty computing devices, and the like. Embodiments of the invention may also be practiced in distributed computing environments where tasks are performed by remote-processing devices that are linked through a communications network.
With continued reference to
The computing device 100 typically includes a variety of computer-readable media. Computer-readable media may be any available media that is accessible by the computing device 100 and includes both volatile and nonvolatile media, removable and non-removable media. Computer-readable media comprises computer storage media and communication media. Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, program modules or other data. Computer storage media includes RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computing device 100. Communication media, on the other hand, embodies computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. Combinations of any of the above should also be included within the scope of computer-readable media.
The memory 112 includes computer-storage media in the form of volatile and/or nonvolatile memory. The memory may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical-disc drives, and the like. The computing device 100 includes one or more processors that read data from various entities such as the memory 112 or the I/O components 120. The presentation component(s) 116 present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, and the like.
The I/O ports 118 allow the computing device 100 to be logically coupled to other devices including the I/O components 120, some of which may be built in. Illustrative components include a microphone, joystick, game pad, satellite dish, scanner, printer, wireless device, etc.
Aspects of the subject matter described herein may be described in the general context of computer-executable instructions, such as program modules, being executed by a mobile device. Generally, program modules include routines, programs, objects, components, data structures, and so forth, which perform particular tasks or implement particular abstract data types. Aspects of the subject matter described herein may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
Furthermore, although the term “server” is often used herein, it will be recognized that this term may also encompass a search engine, a set of one or more processes distributed on one or more computers, one or more stand-alone storage devices, a set of one or more other computing or storage devices, a combination of one or more of the above, and the like.
Turning now to
The computing system environment 200 includes a keyword-stack renderer 212, a data store 214, and an end-user computing device 216 with a display screen 217 all in communication with one another via a network 210. The network 210 may include, without limitation, one or more local area networks (LANs) and/or wide area networks (WANs). Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets and the Internet. Accordingly, the network 210 is not further described herein.
In some embodiments, one or more of the illustrated components/modules may be implemented as stand-alone applications. In other embodiments, one or more of the illustrated components/modules may be integrated directly into the operating system of the keyword-stack renderer 212. The components/modules illustrated in
It should be understood that this and other arrangements described herein are set forth only as examples. Other arrangements and elements (e.g., machines, interfaces, functions, orders, and groupings of functions, etc.) can be used in addition to or instead of those shown, and some elements may be omitted altogether. Further, many of the elements described herein are functional entities that may be implemented as discrete or distributed components or in conjunction with other components/modules, and in any suitable combination and location. Various functions described herein as being performed by one or more entities may be carried out by hardware, firmware, and/or software. For instance, various functions may be carried out by a processor executing instructions stored in memory.
The data store 214 is configured to store information associated with internet advertising. In various embodiments, such information may include, without limitation, information concerning internet advertisers and their internet advertisement campaigns, internet advertising metrics associated with the advertisement campaigns, information on advertisement industry benchmarks, internet search engines, and/or the like. In embodiments, the data store 214 is configured to be searchable for one or more of the items stored in association therewith. The information stored in association with the data store 214 may be configurable and may include any information relevant to advertisers, advertisement campaigns, internet advertising metrics, internet search engines, and/or the like. The content and volume of such information are not intended to limit the scope of embodiments of the present invention in any way. Further, though illustrated as a single, independent component, the data store 214 may, in fact, be a plurality of storage devices, for instance, a database cluster, portions of which may reside on the keyword-stack renderer 212, end-user computing device 216, and/or any combination thereof.
As shown, the end-user computing device 216 includes a display screen 217. The display screen 217 is configured to display information to the user of the end-user computing device 216, for instance, information relevant to communications initiated by and/or received by the end-user computing device 216, information concerning internet advertising metrics, graphical displays of internet advertising metrics, and/or the like. Embodiments are not intended to be limited to visual display but rather may also include audio presentation, combined audio/visual presentation, and the like. The end-user computing device 216 may be any type of display device suitable for presenting a GUI. Such computing devices may include, without limitation, a computer, such as, for example, computing device 100 described above with reference to
The keyword-stack renderer 212 shown in
Components of the keyword-stack renderer 212 may include, without limitation, a processing unit, internal system memory, and a suitable system bus for coupling various system components, including one or more data stores for storing information (e.g., files and metadata associated therewith). The keyword-stack renderer 212 typically includes, or has access to, a variety of computer-readable media. By way of example, and not limitation, computer-readable media may include computer-storage media and communication media. The computing system environment 200 is merely exemplary. While the keyword-stack renderer 212 is illustrated as a single unit, one skilled in the art will appreciate that the keyword-stack renderer 212 is scalable. For example, the keyword-stack renderer 212 may in actuality include a plurality of computing devices in communication with one another. Moreover, the data store 214, or portions thereof, may be included within, for instance, the keyword-stack renderer 212, a search engine, or a third-party service as a computer-storage medium. The single unit depictions are meant for clarity, not to limit the scope of embodiments in any form.
As shown in
The receiving component 218 is configured to receive (via the network 210) requests from a user (typically an advertiser) for a graphical representation(s) of internet advertising metrics associated with, for example, a particular advertising campaign or an advertising account associated with the advertiser. In embodiments, such a request from a user device may be specifically initiated by a user. For instance, a user may specify to view one or more metrics associated with an advertising campaign or an advertising account (e.g., an advertiser may have multiple advertising campaigns within his or her advertising account). In other embodiments, such a request from a user device may be provided based on a user selecting to generally view data associated with an advertisement campaign or an advertisement account. By way of example only, upon logging into a user's advertisement account, the user may select a tab, icon, or other indicator to view data pertaining to a campaign, advertisements, keywords, advertisement groups, or the like.
The receiving component 218 may also receive other user requests regarding the graphical representations. For example, the user may request to view a keyword stack associated with a particular metric or metrics. In this regard, the user may select to view one or more metrics. In one embodiment, a menu (e.g., drop down menu) may be used for each keyword-stack to allow the user to configure which metric the user would like to be displayed on the keyword stack. Such metric options may include, for example, average position, clicks (e.g., number of clicks), cost per action (CPA), cost per click (CPC), click through rate (CTR), conversions (e.g., number of conversions), conversion rate, impressions (e.g., number of impressions), and spend (e.g., amount of money spent or cost). In embodiments, such metric options can be selected at any time. For example, several metrics might be selected during account initialization, or thereafter, and saved such that the advertiser views keyword stacks associated with the selected metrics each instance the advertiser views the account, or a portion thereof. In another example, the metrics might be selected each instance the user wishes to view the keyword stack associated with the particular metric.
Further, a user may request that certain filters be applied to the internet advertising metrics. In this way, for a particular keyword-stack, a user can select to narrow the focus of a set of one or more specific keyword representations. Such a filter selection can be applied in any manner. In one embodiment, a menu (e.g., drop down menu) or set of links may be used for each keyword-stack to allow the user to select or filter which keyword or set of keywords the user would like to be displayed or visually distinguished (e.g., high-light, low-light, color variance, etc.) within the keyword stack. Such filter options may include, for example, all performing keywords, most expensive keywords (e.g., top 25% CPC), best performing keywords (e.g., top 25% clicks, bottom 25% CPC), keywords with zero clicks, low-impact keywords (e.g., top 10% CPC, bottom 10% clicks, bottom 10% CTR), etc. As can be appreciated, any number or substance of predetermined filters may be provided to advertisers as an option and/or selected by users. Further, in some cases, a user may generate filter options based on the advertiser's own preference such that the advertiser can simply select a desired filter for a particular keyword stack. In some cases, a filter option can be applied to multiple keyword stacks. For instance, assume that a user selects a “best performing keywords” filter option. In such a case, both a “click” keyword stack and a “CPC” keyword stack might be filtered.
In addition to or in the alternative of being able to select predetermined filters, a user can dynamically apply filters to apply to the internet advertising metrics. For instance, a user may select one or more keyword representations within a keyword stack associated with a particular metric. For instance, in a dot implementation that has a dot (or other symbol or icon) representing each keyword, a specific dot or set of dots can be selected by the user within a keyword stack. In a bar implementation that has a bar or line representing a set of keywords, a specific bar can be selected by the user within a keyword stack (e.g., by selecting a particular bar or using a slider to select one or more bars). As described more fully below, in a multi-stack presentation, when a user selects to filter a first keyword stack by selecting one or more keyword representations, one or more other keyword stacks may automatically filter the keyword representations to display the keyword representations that correspond with the keywords selected by the user in the first keyword stack.
Such filter options can be selected at any time. For example, several filters might be selected during account initialization, or thereafter, and saved such that the advertiser views keyword stacks displaying or visually distinguishing keywords associated with the selected filter each instance the advertiser views the account, or a portion thereof. In another example, the filters might be selected each instance the user wishes to view or filter the keyword stack associated with the particular metric.
The receiving component 218 may also receive requests from users that the internet advertising metrics be sampled over a specified range of time. For example, the user may request that the advertising metrics be sampled only for today, yesterday, the last 7 days, the last 14 days, the last 30 days, month to date, last month, last 3 months, or the last 6 months. Continuing, the receiving component 218 may also receive requests from users that graphical representations of additional internet advertising metrics be displayed. Any and all such variations, and any combination thereof, are contemplated to be within the scope of embodiments of the present invention.
The retrieval component 220 is configured to retrieve data associated with requested internet advertising metrics. The retrieval component may, for example, retrieve the internet advertising metrics, or data associated therewith, from the data store 214. Internet advertising metrics include a variety of well-known metrics that measure the effectiveness of an internet advertisement campaign. For example, internet advertising metrics may include impressions, clicks, spend, conversions, average position, average cost per click, click through rate, cost per action, cost per click, conversion rate, percentage of change, and the like. There are many examples of metrics used to measure the effectiveness of internet advertising and these are all included within the scope of the invention. Further, as the metrics may be displayed in association with a particular period of time, the retrieval component 220 can be configured to retrieve metric data associated with a particular time period (e.g., today, yesterday, the last 7 days, the last 14 days, the last 30 days, month to date, last month, last 3 months, or the last 6 months).
The generating component 222 is configured to generate or modify one or more keyword stacks. The one or more keyword stacks to generate or modify can be based on, for example, a default selection of metrics to be associated with keyword stacks (e.g., based on an application default, based on an advertiser's default preference, etc.) or a selection of a metric(s) while viewing an advertising campaign. Keyword stacks are generated in accordance with a particular metric or metrics, for example, as specified by a user or as set by a default setting or preference (e.g., system defined or user defined). As described more fully below, keyword stacks can be generated in any number of forms, such as a dot representation, a bar representation, various forms thereof, and the like. Any and all such variations, and any combination thereof, are contemplated to be within the scope of embodiments of the present invention.
Generally, a keyword stack associated with a particular metric is used to enable a user to visualize the keyword distribution in association with the specific metric. The keyword stack can show all the keyword representations for a particular advertisement campaign or advertisement account. The vertical component or axis of the keyword stack represents a metric measurement associated with keywords. Such a metric measurement may be any quantity or quality that can represent or indicate data pertaining to the keyword. For instance, a metric measurement may be a number, percent, ratio, etc. By way of example only, for a click keyword stack, the vertical scale can be a keyword's number of clicks for a specified time period. As such, the higher the position of a keyword, the larger the number of associated clicks.
In a dot implementation of a keyword stack, each dot represents a keyword. Each of the dots together provide a visual of the keyword distribution for clicks. Accordingly, top and/or bottom performers can visually stand out to the user without performing detailed analysis. Although the dot representation is generally described herein using dots, any shape, symbol, icon, or other representation can be utilized.
In a bar implementation of a keyword stack, each bar represents a number of keywords falling within a particular metric measurement, or range thereof. The longer or wider the bar, the more keywords that fall into that metric measurement or range. Utilizing bars can enhance scalability so that the visual bar can represent thousands of keywords. Further, the horizontal bars can be center-aligned, left-aligned or right-aligned. Center-aligned horizontal bars in a keyword stack collectively outline a symmetrical shape, such as a pyramid, a diamond, etc. that help the user visualize the overall distribution of the keywords.
The generating component 222 can further utilize any filters to generate and/or modify a keyword stack(s). That is, upon identifying a filter to apply to a particular keyword stack(s), the generating component 222 can generate a new keyword stack or modify a stack to display or visually distinguish any keyword representations associated with the applicable filter. For example, upon a user selecting a particular filter option for a keyword stack or set of keyword stacks (e.g., all performing keywords, most expensive keywords, best performing keywords, keywords with zero clicks, low-impact keywords), the keyword stack can be generated or modified accordingly. In another example, upon a user selecting one or more keyword representations within a keyword stack (e.g., a dot(s) or a bar(s)), the keyword stack can be generated or modified accordingly.
Further, the generating component 222 can also identify additional keyword stacks to generate or modify based on a filter applied to a particular keyword stack. For instance, assume that a user selects three keyword representations within a keyword stack (e.g., as each keyword appears to be performing exceptionally high or low relative to the other keywords). In such a case, the generating component 222 can identify other keyword stacks to modify (e.g., each additional presented keyword stack) and modify such stacks to display or visually distinguish the three corresponding keyword representations.
The rendering component 224 is configured to render a GUI that displays graphical representations of internet advertising metrics, for instance, in the same viewable area. In one aspect, the rendering component 224 utilizes information from the receiving component 218, the retrieval component 220, and/or the generating component 222 to generate a GUI uniquely tailored to the needs of a user. In another aspect, the rendering component 224 determines the amount of screen real estate available on a display device and resizes the graphical representations so that they effectively occupy the available screen space and are all visible within the same viewable area. In other words, it may not be necessary to use a browser scroll bar to view all of the graphical representations.
In yet another aspect, the rendering component 224 may determine that the screen width of a display device has changed. For example, a user may have switched from viewing the display screen of a personal computer to viewing the display screen of a smart phone. Upon making such a determination, the rendering component 224 may proportionally change the size of the graphical representations so that all of the representations continue to be in the same viewable area.
Turning now to
Initially, with reference to
As illustrated in
The stack displaying area 304 is displayed above a keyword grid display area 306. The keyword grid display area 306 includes a listing of the keywords within the advertising campaign or advertising account along with performance data associated with the keyword. For example, each keyword, or identifier thereof, is presented in column 308 with a corresponding bid 310, CPC 312, clicks 314, CTR 316, conversions 318, spend 320, impressions 322, and status 324. Accordingly, specific metric values associated with each keyword can be presented in the keyword grid display area 306. Although
In embodiments, a drop-down menu can be accessed for each keyword stack to allow the user to configure which metrics to view in association with the keywords. Although illustrated with eight metric options, any number of metrics can be provided. In some cases, if a user selects a new metric for which to display a keyword stack when one or more filters are already set for the chart, the filters may be reset. To maintain filters set by the user for other keyword stacks, such settings for those stacks may not be reset.
In embodiments, there is no horizontal scale such that the length of each bar does not represent a specific number of keywords. For example,
As previously described, keyword stacks can be filtered in a number of manners.
In embodiments, each keyword stack includes two sliders to allow a user to filter the keyword data according to the user interests. The sliders can be moved up or down. In some cases, the other keyword stacks displayed can be automatically adjusted to reflect the new filter without the need for the user to click on an “apply” button.
Further, in some implementations, a user may select the area 612 between the first slider 602 and the second slider 604 along the sliding axis 606 to move the sliders while maintaining the distance between sliders. That is, the user can click within the area 612 in between the sliders and drag that section anywhere along the sliding axis 606 to modify the selected bars while preserving the distance between the sliders.
In yet a third embodiment for filtering keywords within a keyword stack,
As can be appreciated, in some embodiments, filter options may be applicable to a single keyword stack. In other embodiments, filter options may be applicable to multiple keyword stacks. A user may have an option to save selected filter(s) such that the saved filter(s) can be applied at a later time.
As illustrated in
In filtering or interacting with keyword representations, various functions may occur in response to such filtering or user interaction. For example, as previously discussed and as illustrated in
In addition to or in the alternative of filtering additional keyword stacks when a filter is applied to a particular keyword stack, as data is filtered within a keyword stack(s), the keyword grid can be automatically and dynamically adjusted to reflect the filtered keywords (e.g., filtered by filtered option selection, user selection of a bar, etc). Accordingly, changes made to a keyword stack can be reflected on the keyword grid by filtering the keywords, for instance, with the high CPC and low conversions. Accordingly, a user is able to quickly identify and/or analyze the low-impact keywords reflected on the grid. In some cases, the filtered-out keywords and corresponding data can be removed from the chart, moved to the bottom of the chart, or otherwise visually distinguished (e.g., faded, high-lighted, low-lighted, etc.). For example, as illustrated in
While
As with the bar keyword stacks illustrated above, the dot keyword stacks can be interacted with or filtered to narrow the focus to particular keyword representations. As illustrated in
By way of another example and with reference to
Further, trending graphs representing the metric trends can be provided, generated, or modified in accordance with the remaining keywords. For instance, an impressions trending graph 1916, a clicks trending graph 1918, a CPC trending graph 1920, and a conversions trending graph 1922 can be displayed with each such graph illustrating trends pertaining to the three selected keywords. As illustrated, keywords stacks can be positioned adjacent to or near the corresponding trending graphs.
Dot keyword stacks can be any width. The width of the keyword stacks illustrated in
To recapitulate, embodiments of the invention include systems, machines, media, methods, techniques, processes and options for providing and filtering keyword stacks. Turning to
Initially, as indicated at block 2502, an indication to display a set of keyword stacks is received. In embodiments, each keyword stack is associated with a different internet advertising metric, such as, for example, a click, an impression, a spend, a conversion, an average position, an average cost per click, a click through rate, a cost per action, a cost per click, a conversion rate, or a percentage of change. Such an indication can be received automatically (e.g., upon a user viewing an advertising campaign or keyword analysis) or upon a user selection to display a particular type of keyword stack. At block 2504, keyword data associated with one or more internet advertising metrics is referenced. Such keyword data can, in embodiments, correspond with a designated, default, or selected time period. At block 2506, the keyword data is used to generate the set of keyword stacks. In some embodiments, each keyword stack is a bar keyword stack such that the stack includes a group of horizontal bars vertically stacked, with each horizontal bar representing a number of keywords falling within a particular metric measurement, or range thereof, corresponding with a vertical axis. In other embodiments, each keyword stack is a dot keyword stack such that a plurality of dots represent the keywords.
With reference now to
Although descriptions and illustrations provided herein generally pertain to the keyword stacks, embodiments of the present invention are not intended to be limited to keyword vertical stacks. Rather, stacks or vertical stacks can be generated in relation to various other concepts within the advertising campaign environment. For instance, vertical stacks can be generated in reference to, among others, search queries, advertisement units, placements, publishes, advertisements, advertisement groups, campaign groups, accounts, etc. Further, metric stack visualization can be applied and useful beyond the advertising industry. For example, in the financial industry, multi-metric stacks can assist users in visualizing individual stocks in a portfolio on the metrics of price changes, P/E ratio, volumes, etc. In another example for sales analysis for a book store, multi-metric stacks can assist in visualizing individual books on the metrics of price, sales volume, profit margin, and readership.
The present invention has been described in relation to particular embodiments, which are intended in all respects to be illustrative rather than restrictive. Alternative embodiments will become apparent to those of ordinary skill in the art to which the present invention pertains without departing from its scope.
