Optimization of location search and mobile search

Abstract

A method for analyzing, reporting, and optimizing digital content (272) for mobile device searches (114), comprising: obtaining digital content (272) containing one or more pages intended for display on mobile devices (114); analyzing the digital content (272) by a processor (240) to determine one or more first properties of the digital content (272) relating to the placement of a reference to the digital content (272) in the mobile device search results (114); analyzing the digital content (272) by a processor (240) to determine one or more second properties of the digital content (272) relating to the configuration of the digital content (272) to redirect a server to one or more of the pages of the digital content (272) configured for a mobile device (114) that has requested the digital content (272);Analyzing the first properties of the digital content (272) to determine one or more first optimizations applicable to the digital content (272) to modify at least one of the first properties to improve the placement of a reference to the digital content (272) in mobile search results; Analyzing the second properties of the digital content (272) to determine one or more second optimizations applicable to the digital content (272) to modify at least one of the second properties to change the digital content so that a server switches to one or more of the pages of the digital content configured for the mobile device (114) that requested the digital content; Generating one or more recommendations to adapt the digital content (272) based on the first and second optimizations;and sending one or more recommendations for adapting digital content (272) to another system configured to implement the recommendations for optimizing digital content (272) for mobile devices (114).

Description

BackgroundSearch engine optimization generally describes the use of computer systems to perform data processing procedures that collect, store, and analyze search engine data to provide recommendations for improving the visibility of a web entry or web page in search engines. Search engine results may be achieved through various search strategies such as natural, non-paid, organic, or algorithm search results, as well as paid search algorithms for paid listings within targeted search engine marketing. In general, the higher it is placed in the list of web entries and the more frequently it appears in the search result list, the more frequently a web entry can get visits from the search engine users. In the search engine optimization, a unit can target different kinds of search results in addition to actual results for web occurrences. For example, universal results such as images, location, videos, news, and other industry-specific search results may be optimized for search engines. Search engine optimization can improve Internet users' availability and access to web occurrences or other digital content.As mobile technology grows, more and more Internet users access the Internet via mobile devices, such as smartphones, tablets, and other mobile devices. Search engines and other providers of Internet content accommodate various increases in searches performed on mobile devices to improve the user experience for Internet users who perform searches on mobile devices. Moreover, a recent increase in search activity during which end users travel with their mobile devices from location to location has been associated with a marked change in that search engines increasingly display search results filtered and organized by the end user's location, resulting in different organization and display of search results depending on device type (stationary devices as opposed to mobile devices) and device location.The explosive increase in combinations of device types along with the increasing level of development of search engines that output search results for display on particular device classes, as well as selectively providing content at any number of particular locations (cities, towns, and other regions and areas such as such entities may be defined in various ways), makes it increasingly difficult for digital marketers to identify, track, observe, and compare differences in search performance depending on device and location, thereby making highly scalable, increasingly integrated, and highly automated solutions highly valuable.The subject matter claimed herein is not limited to embodiments that overcome a drawback or that operate only in such environments as described above. Rather, the background is provided to show, by way of example only, a technological field in which some of the embodiments described herein may be utilized. For example, US 2010 / 0 268 700 A1 describes systems and methods for searching and search optimization using a pattern in a location identifier. Another example is US 2008 / 0 243 821 A1, which describes a system and method for utilizing local intents to provide geographically relevant information in response to a search query. As another example, US 2009 / 0 157 666 A1 describes a method for improving the efficiency of a search engine in accessing, searching, and retrieving information in the form of documents stored in document or content memories. As another example, KR 10 2010 0 079 340 A describes a mobile communication terminal requesting the search for information depending on a location. As another example, the article OEHLMAN, Damon; BLANC, Sebastien, "Pro Android Web Apps, Develop for Android using HTML5, CSS3 & JavaScript", Apress, Berkeley, 2011, describes that web application developers have the ability to develop mobile applications running on a variety of different devices through the combination of HTML5 with CSS3 and Javascript. Another example is the article FAWAD, Nazir, "Optimization and Modeling of Content Delivery Algorithms for Density Mobile Social Networks", The School of Electrical Engineering and Telecommunications, The University of New South Forest, May 2010, which describes information exchange between devices using ad hoc networks built between these devices. A further example is US 2007 / 0 061 302 A1, which describes information about the location of mobile communication devices and other possibilities for improving the presentation and relevance of mobile contents for suitable or desired mobile communication devices.SummaryThis Summary is intended to introduce a selection of concepts in a simplified form that are further described below in the Detailed Summary. This Summary is not intended to identify key characteristics or essential features of the claimed subject matter, nor is it intended to aid in determining the scope of the claimed subject matter.A method for analyzing, reporting, and optimizing digital content for searching on mobile devices is described. The method comprises:obtaining digital content including one or more pages intended for display on mobile devices;analyzing the digital content by a processor to determine one or more first characteristics of the digital content that relate to the placement of a reference to the digital content in the search results for mobile devices;analyzing the digital content by a processor to determine one or more second characteristics of the digital content related to configuring the digital content to switch a server to one or more of the pages of the digital content configured for a mobile device that requested the digital content;analyzing the first characteristics of the digital content to determine one or more first optimizations applicable to the digital content to alter at least one of the first characteristics to improve the placement of a reference to the digital content in the search results for mobile devices;analyzing the second characteristics of the digital content to determine one or more second optimizations applicable to the digital content to alter at least one of the second characteristics to alter the digital content such that a server switches to one or more of the pages of the digital content configured for the mobile device that requested the digital content;generating one or more recommendations to adjust the digital content based on the first and second optimizations; andsending the one or more recommendations to adapt the digital content to another system configured to implement the recommendations to optimize the digital content for mobile devices.Exemplary embodiments of the invention will become more fully apparent from the following description and dependent claims.Brief Description of the FiguresThe foregoing and following information, as well as other functions of this disclosure, will be more fully understood from the following description and appended claims, taken in conjunction with the accompanying drawings. Provided that these drawings show only some embodiments according to the disclosure and are therefore not to be considered as limiting the scope thereof, the disclosure will be described with additional specificity and details through the use of the appended drawings, wherein FIG. 1 illustrates an example of a digital content auditing system; FIG. 2 is a block diagram of an example audio content auditor; FIG. 3 is a flow diagram of an example method for optimizing digital content for searches performed on mobile devices; FIG. 4 illustrates an example keyword management; FIG. 5 is a flow diagram of an example method for search engine optimization based on location; FIG. 6 is a block diagram of an example location data management; and FIG. 7 is a flow diagram of an example method for optimizing web occurrence through the management of location data.DESCRIPTION OF EMBODIMENTSIn the following detailed description, reference is made to the accompanying drawings, which form a part hereof. In the drawings, like symbols typically designate like components, unless context suggests otherwise. The illustrative embodiments described in the detailed description, drawings and claims are not to be considered limiting. Other embodiments may be utilized and other changes may be made without departing from the spirit or scope of the subject matter presented herein. It will be readily appreciated that the aspects of the present disclosure, as generally described herein and illustrated in the figures, may be arranged, replaced, combined, separated, and configured in a wide variety of different configurations, all of which are expressly contemplated herein.As mobile technology grows, more and more users use mobile technology to interact with networks such as the World Wide Web ("Web") through one or more portals such as the Internet. The mobile technologies include mobile phones such as smart phones, game consoles, global positioning system utilizing devices, tablet computers, portable music devices, and other types of mobile devices.In particular, searches are performed on mobile devices rather than fixed devices such as private computers (PCs). Current mobile devices may offer increasingly sophisticated browsers, run on high speed networks, offer convincing graphics performance, simpler / more intuitive user interfaces, and / or almost uninterrupted connectivity to global networks such as, but not limited to, the Internet, and allow end users to do things with their mobile devices that were previously a domain of fixed devices, and that are still more timely and / or frequent as end users travel from location to location. New data from some web entries indicate that visits to web entries originated by mobile devices account for significantly more than 30% of the web traffic of the web entry. This alters the search experience for end users. With current mobile devices, a user may search for a restaurant, hotel, or store while moving throughout the day without ever accessing a stationary device. While mobile devices perform basic search functions similar to those performed by fixed devices, the search experience for users using mobile devices is different and search engines respond to these changes. For example, in some embodiments, search engines (e.g., Google, Bing, Yandex, Badu) may modify search results they provide to end users, taking into account the types of mobile devices with which the end users are searching, the type and quality of digital content suitable for display on such mobile devices, the location of the end user in the search, physical locations associated with the digital content being searched, and other services end users receive from mobile devices. In this and other embodiments, the search engines may modify search results based on the above-mentioned factors to present results of digital content including information about a physical store relevant to the search and specific location of the end user, such as a physical address, phone number, directions, hours of opening, etc., of the physical store. Alternatively or additionally, the search results may be arranged in such a manner as to be suitable for display on different types of devices (including mobile devices), or in specially designed location or mobile "packets" appearing in the search result. An example of this may be a search result that includes the physical location of a retail or service company store (e.g., household convenience store, warehouse, coffee shop, quick restaurant, etc.).The number of web content developers for these networks is increasing. Accordingly, search engines, advertisers, marketers, and others adapt to mobile devices. However, one difficulty in increasing mobile technology is that it is difficult for digital marketers of goods and services to tailor their goods and services to the mobile search environment. Devices seek to make their digital contents take an advantageous rank / function well when searching with mobile devices because it can make up a substantial part of their business success and impact as end users think of their products, services and brands. However, taking an advantageous rank / functioning well in mobile-based searches is difficult because the spread of different mobiles and search engines introduces a change in how they respond to searches from different types of mobiles. As such, entities wishing to optimize their digital content for mobile searches may take into account how their digital content can be processed by search engines when performing searches on mobile devices. Various aspects of digital content may affect how search engines process the digital content. Some aspects of digital content that may affect how search engines process the digital content may include page sizes within the digital content, a compression ratio of pages within the digital content, a cache control setting for the server on which the digital content resides, a keyword type, location information provided by the digital content such as, by way of example and not limitation, street address, phone number, association with a map or directions, all or some of which may be specifically configured for different mobile device types, a flag for mobile devices within the digital content, a sub-map for mobile devices within the digital content, or mobile device specific content within the digital content. In addition, search engines increasingly customize how location-specific search results are presented on mobile devices. This can have a direct influence on how efficiently marketers can organize their contents to maximize their search results for searches performed on a location-dependent basis.The location information provided in digital content and presented to search engines may also be captured and adjusted so that the proper type of location information or information about the physical location (e.g., the phone number, address, slot hours of a store) is provided to a search engine and the information is correct. The information may be captured and adjusted within a search engine optimization system, a redaction system, or any other system such as a database or data storage system.A search engine may also use locations to further refine search results for fixed devices as well as mobile devices. Search results may vary widely depending on the location at which the search is performed. For example, search results for a keyword at a location may yield search results with different digital content from specific categories, such as images, videos, messages, purchases, real-time, blogs, books, locations, discussions, recipes, patents, calculators, stocks, timelines, or other digital content that is closely associated with and targeted to a particular type of digital content so as to be in a category of digital content. For example, in response to a search for burgeres at a first location, the search results may include images of burgeres and locations of various local burger restaurant. In another search for burgeries at a second location, the search results may not include images of burgeries and more or less locations for various burger restaurantes. In another example, references to the same burger restaurant may have different positions in the search results depending on the location at which the search is performed. Alternatively or additionally, adding or omitting a location in the keywords used for the search may change the search results even if the location at which the search is performed is taken into account by the search engine.In general, embodiments disclosed herein relate to computer systems and methods for optimizing digital content for mobile searches. Optimizing digital content for mobile searches includes understanding user behavior in searching mobile devices, as well as understanding how to provide network content providers, such as application developers and search engines, for mobile device search results, and how to adjust digital content based on the behavior of the users, search engines, and network content providers to enhance the ability of entities to improve the visibility of their web occurrences, web pages, or other digital content in searching performed on mobile devices. In some embodiments, optimizations that may be applied to digital content may be prioritized based on one or more factors, such as, but not limited to, an estimated change in position in search results when an optimization is performed, an increase in conversions or traffic when an optimization is performed, or an increase in translation generated by digital content when an optimization is performed. In addition, additional factors for prioritizing optimizations may be determined from the digital content by a web analysis system. It is understood that a device is a company, an operation, a partnership, a company, an organization, a pen, an individual, a trehand company, a family, or other device having digital content on the Internet.Referring now to the figures, similar structures are denoted by similar reference numerals. It is understood that the figures are diagrammatic and schematic representations of some embodiments of the invention, and are not intended to be limiting of the present invention. They are also not necessarily drawn to scale.FIG. 1 illustrates an embodiment of a digital content auditing system 100, in accordance with some embodiments described herein. The system 100 may include a network 102. In some embodiments, the network 102 may be used to connect the various parts of the system 100 together, such as between a correlator 104, a web server 106, a low-index engine 108, a search engine 110, a mobile search module 112, a mobile device 114, a location module 116, and a location data manager 118. It should be understood that although a single component is shown, the components may be combined as desired. Further, although one of each component is illustrated, system 100 may optionally include any number of each of the illustrated componentsNetwork 102 may include the Internet, including a global Internet network formed of logical and physical connections between multiple wide area networks and / or local area networks, and may optionally include the World Wide Web ("Web"), including a system of interconnected hypertext documents accessed via the Internet. Alternatively or additionally, the network 102 includes one or more cellular RF networks and / or one or more cable and / or wireless networks, such as, but not limited to, 802.xx networks, Bluetooth access points, wireless access points, IP-based networks, or the like. The network 102 may also include servers that allow one type of network to interface with another type of network.The web server 106 may include any system capable of storing and transmitting digital content, such as web pages and other digital content. The web server 106 may allow access to web pages of a web entry or other digital content on the web that may be analyzed to improve mobile or local searches. For example, the web server may include a computer program that is responsible for accepting requests from clients (such as web browsers) and providing them with HTTP responses and associated optional data content, which may include HTML documents and associated objects for display to the user. Additionally or alternatively, the web server 106 may include the ability to log some detailed information about requests from clients and server responses into log directories.Digital content, as used herein and unless otherwise specified, refers to any online publication including domains, subdomains, uniform resource identifiers ("URIs"), uniform resource locators ("URLs"), images, videos, or other content, and non-permanent publications such as email and chat.Search engine 110 may be an internal or private search engine used for the function of producing search results. The search results produced by the search engine 110 may vary depending on the requesting device or the type of the requesting device. For example, search engine 110 may provide a first search result set when a search for a keyword is requested by a standard PC / fixed device and a second search result set when the search for the keyword is requested by a mobile device such as mobile device 114. As used herein, the word "keyword" refers to one or more words or characters that can be input to the search engine to produce search results. Accordingly, a keyword may be a single word such as "shoe", or a word string such as "inexpensive red nike basketball shoes". As another example, the search engine 110 may provide a first search result set when the search for a keyword is requested at a first location and a second result set when the search for the keyword is requested from a second location.In some embodiments, search engine 110 may not distinguish between devices of the same type. For example, a search engine 110 may provide first results to a laptop and a desktop for the same search query, but provide second results to different types of mobile devices. In some embodiments, search engine 110 may distinguish between different types of mobile devices or fixed devices. For example, the tablet search engine 110 may generate results that are different from results generated for smartphones. In some embodiments, the difference between the search results generated for different requesting devices may be the representation of the referenced digital content, where the referenced digital content may be the same. Alternatively or additionally, the digital content referenced in the search results may be different. In some embodiments, search engine 110 may also change search results depending on the location of a device and whether the device is a mobile device or a stationary device.The search engine 110 may generate different search results for different devices when the search engine 110 is able to determine a difference between requests received at the search engine 110. For example, a search query may indicate that the query is from a mobile device or from a fixed device such as a personal computer, and the search engine may generate search results suitable for each device. In some embodiments, a search request may not identify a requesting device. In these and other embodiments, search engine 110 may send similar results to different device types.In some embodiments, search engine 110 may generate different requests for different devices depending on whether the devices are different, but also different information received from each device. For example, a mobile device such as mobile device 114 may have a global positioning system (GPS) utilizing device or other device that tracks the location of the mobile device at a low level of granularity. The mobile device 114 may send its location to the search engine 110 in the search query, and the search engine 110 may generate search results based on the mobile device 114. By including the location of the mobile device 114 as a factor in generating the search results, the search engine 110 may generate search results that deviate from search results that do not include the location that does not include the granularity of the location information or that includes the location information in a different form in fixed devices.The search engine 110 may be a public search engine or a commercial search engine such as Bing, Google, Yahoo, Yandex, Badu, or the like.In some embodiments, the low index engine 108 may be configured to generate the search requests using different keywords and send the search requests to the search engine 110. The low-index engine 108 may also receive search results from the search engine 110 and search the search results as crawlers to determine information about the search results. For example, the low-index engine 108 may be configured to search search results as crawlers and analyze data associated with the crawler, including on-page information and back-link data (e.g., back-link URL, anchor text, etc.), for each digital content referenced in the search results.In some embodiments, the low index engine 108 may be configured to emulate various devices to cause the search engine 110 to generate results for a specific device. For example, the low-index engine may emulate a mobile device and a fixed device and search search results output by the search engine 110 as crawlers for both devices. For example, the low-index engine 108 may emulate a mobile device, and in some embodiments, the low-index engine 108 may be configured to emulate devices in different locations. In these and other embodiments, the low-index engine may be capable of detecting differences between search results appearing at different locations.The low-index engine 108 may be further configured to determine the placement of digital content into search results generated by a search engine. It is assumed that when digital content is referred to as being generated by a search engine, the digital content itself may be included in the search results. For example, an image may be included in the search result. Alternatively, digital content that appears in search results may be understood to include a reference to the digital content and / or a portion of the digital content in the search results. For example, the search results may include a reference to a web entry and a portion of that web entry as a preview of the search results, but may not include all of the web entry in the search events.The placement of the digital content in search results may be referred to as a ranking of the digital content in the search results, a page location of the digital content in the search result, or a pixel location of the digital content in the search results. The placement of the digital content may make up a location at which a particular search result is displayed within the search results for a search term or combination of search terms. The relative position of the digital content within the search result may affect how the search term or combination of search terms affects actions of a search engine on search results. For example, digital content such as a web page may be displayed in different locations on a search result page depending on whether the search is requested by a non-mobile device or a mobile device. Alternatively or additionally, digital content, such as a web page, may be displayed in different locations on a search result page depending on whether the requested search includes information regarding the location at which the device requesting the search resides.The placement of digital content in search results may depend on many characteristics of the digital content. Some characteristics of the digital content that affect the placement of the digital content in search results may include a size of one or more of the pages of the digital content, a compression ratio of one or more of the pages of the digital content, a cache control setting for the server hosting the digital content, a keyword type, availability of location information, a mobile device flag, a mobile device subdomain, mobile device specific content, and others.Correlator 104 may be configured to determine how visitors are directed to digital content and how these visitors behave when they have arrived at the digital content. For example, correlator 104 may be configured to determine click-through rates based on the number of visitors who arrive at the digital content from a search result page generated by searching for a keyword and the number of searches that occur using a keyword based on information received from a search engine that generates the search result page. Correlator 104 may be further configured to determine a number of conversions made by visitors to the digital content based on their behavior. In some embodiments, a conversion may be an action of the visitor, such as, but not limited to, downloading a white paper, item, application, file, or other digital item; viewing a page; shopping using the digital content; associating the digital content with a social network, accepting the digital content in a social network, linking the digital content in a social network, mentioning the digital content in some social media. Alternatively or additionally, correlator 104 may be configured to determine a value associated with an increase in the number of visitors to the digital content or an increase in the number of conversions to the digital content.The mobile search module 112 may be configured to examine digital content to determine optimizations that may be performed on the digital content to improve placement of the digital content in the search results generated for a mobile device. In particular, the mobile search module 112 may be configured to receive digital content and analyze the digital content to determine one or more characteristics of the digital content that are related to the placement of a reference to the digital content in the mobile search results. After determining the characteristics of the digital content, the mobile search module 112 may be configured to analyze the characteristics of the digital content to determine one or more optimizations to apply to one or more of the characteristics of the digital content to improve the placement of the reference to the digital content in the results of the mobile search. The mobile search module may be further configured to generate a report that includes the optimizations. In some embodiments, the review may be performed by the mobile search module 112 and may be referred to as "Mobile Site Audit (Review)" of the digital content.In some embodiments, the mobile search module 112 may be further configured to offer optimization for device-specific characteristics, such as stores for mobile applications or "mobile app stores.". As will be appreciated by those skilled in the art, mobile app stores include lists of applications specifically tailored to mobile devices. Typically, these mobile app stores include search functions that function in a similar manner as a search engine, although searches are limited to mobile applications. To optimize its performance in a mobile app store, an enterprise may need to change its marketing strategies. For example, specific descriptions or labels may be more useful or efficient for sales or download of a mobile device app. For example, the mobile search module 112 may determine that a particular enterprise mobile device app that includes a gaming game has lower sales figures than other gaming mobile device apps that offer a free or demoversion of the game. Alternatively, the mobile search module 112 may determine that games with shorter labels are more successful than the company's game. In other examples, the mobile search module 112 may determine that mobile device apps with a larger number of user policies have larger sales figures. Thus, the mobile search module 112 may recommend a marketing program to the enterprise, offering an incentive to the end consumers, such as any form of free content, when evaluating the game. For example, the company may offer additional content for the chafing game, such as specially designed pieces or game boards, to users who evaluated the game.Other information that can be collected and analyzed by the mobile search module 112 in the mobile device app setting includes the number of users of a particular mobile device app, the type or number of links from the app to web occurrences, or applications outside the app or app store, the description of the product of how the app is listed in the app store compared to the search engine ranking list of a non-mobile device.The location module 116 may be configured to determine placement differences in the search results for digital content when the searches are performed based on different location parameters. The location module 116 may communicate with the search engine to perform searches based on various location parameters. In some embodiments, the space parameters may be sent to the search engine from the device requesting the search. In other embodiments, the search engine may have previously retrieved the location parameters from the digital content when it has searched the digital content. Alternatively or additionally, the search engine may retrieve the location information from another database. The search engine may place a reference to the digital content or the digital content in a search result based on the location information. Based on placement differences for the same digital content in search results with different spatial parameters, the spatial module 116 may be configured to offer recommendations for optimizing the digital content to improve the placement of the digital content in the search results.The location data manager 118 may be configured to manage location data for digital content. The place data may include information about at least one physical business lease related to the digital content. For example, a restaurant web entry may include location data that includes information about the restaurant's physical views. The location data may include various fields and may be managed by a redaction system that generates the web entry or by a third party web entry. The location data manager 118 may be configured to check the location data for accuracy, correct formatting, and correct data fields, access the location data, and update the location data.FIG. 2 is a block diagram of an example digital content auditor 200 in accordance with some of the embodiments described herein. The digital content auditor 200 may be communicatively coupled directly or indirectly via a network or via one or more other devices to first and second databases 270, 280. The digital content auditor 200 may include, but is not limited to, a properties module 210, an optimization module 220, a reporting module 230, a processor, a memory 240, and an interface module 250. The digital content auditor 200 may be configured such that the properties module 210, the optimization module 220, the reporting module 230, the processor 240, the memory 250, and the interface module communicate with each other and share information. The first database 270 may include digital content 272 and the second database 280 may include keywords 282.The digital content 272 may be any digital content available over a network, such as the Internet. In some embodiments, digital content 272 may be a multi-page web entry and subdomains. In some embodiments, digital content 272 may be a blog, video, image, or other type of digital content stored on a network or accessible via secured channels or public channels of the Internet.In some embodiments, the first database 270 may be part of a system that includes the digital content auditor 200. In these and other embodiments, digital content 272 may be sent to digital content auditor 200 over a network or directly to digital content auditor 200. In some embodiments, the first database 270 may be remote from the digital content auditor 200. In these and other embodiments, the digital content may be sent to the digital content auditor 200 during backed-up or non-backed-up file transfer. For example, the digital content 272 may be a web page, and the digital content auditor 200 may receive both the public and non-public portions of the digital content 272 via file transfer. In some embodiments, the digital content auditor 200 can access the digital content in the first database 270 by driving the digital content 272 via the Internet and accessing the publicly accessible portions of the digital content 272. For example, the digital content may be a web page, and the digital content auditor 200 may receive the digital content in the same manner as each user of the Internet can access the digital content 272.The properties module 210 may be configured to receive the digital content 272 from the first database 270. The properties module 210 may be further configured to analyze the digital content 272 to determine properties of the digital content related to the placement of a reference to the digital content 272 in search results generated for a mobile device. Various characteristics that may relate to the placement of a reference to digital content 272 in search results generated for a mobile device may include one or more of the following: a size of one or more pages of the digital content, a compression ratio of one or more pages of the digital content, a cache control setting for the server hosting the digital content, a keyword type within the digital content, availability of location information, a mobile device flag, a mobile device subdomain, and a mobile device specific content. The various properties may be determined by analyzing the digital content. For example, the html code or other code and other aspects of a web entry may be analyzed to determine the properties of the web entry.The size of one or more pages of the digital content 272, the compression ratio of one or more pages of the digital content 272, and the cache control setting for the server hosting the digital content 272 may depend on the load times for the digital content 272. The time taken for a device to load the digital content 272 may depend on how a search engine places the digital content 272 or a reference to the digital content on a search result page. For example, mobile devices and their communication speeds are typically longer than non-mobile device communication speeds, and thus, web-enters or applications that are difficult to load onto mobile devices may develop more weakly.The keyword type property may include information about the keywords included in the digital content 272 that may be used by a search engine to associate the digital content with a search performed by the search engine. For example, a search may be performed for the keyword "shoes". If the digital content includes a reference to "shoes" and the search engine recognizes that the digital content 272 includes the reference to "shoes", the search engine may display the digital content 272 or a reference to the digital content 272 in a search result it generates. Other factors besides the digital content 272 that lists the keyword can be accounted for by the search engine when it determines whether to include the digital content 272 or a reference thereto in the search results that the search engine generates.The keyword type property may include various keyword properties. The properties module 210 may analyze the digital content 272 to determine whether the keywords in the digital content include the keyword type properties. In some embodiments, digital content 272 that includes a keyword type property may be digital content 272 that has a particular keyword within digital content 272. For example, the keyword properties may include the length of keywords and keywords associated with a self-completion function used by a mobile device. In these and other embodiments, digital content 272 may have these keyword characteristics by having keywords of reasonable length and using keywords associated with a self-completion function from a mobile device. In some embodiments, the digital content 272 that includes a keyword type property may be the keywords in the digital content 272 that are associated with other aspects of the digital content 272, such as location information in the digital content 272.The length of a keyword can be meaningful because mobile users using the keyboards provided by most mobile devices may be less prone to entering long or very detailed keywords because the keyboards are more difficult to manipulate than keyboards typically attached to most non-mobile devices. Thus, the length of keywords in the digital content may need to correspond to the length of keywords input on a mobile device in order to display the digital content in a search result of a mobile device.Keywords associated with a self-completion function used by a mobile device may also be meaningful because mobile devices may prompt users to complete phrases due to the increased difficulty in entering words into mobile devices. A self-completion function may also include a predictive word search function and a predictive sentence search function. For example, although a user would typically input an entire keyword search "paragraph shoes for women" using a non-mobile device, the same user may see the sentence "paragraph shoes for women" as a predictive search for the input "women", and may select that the predictive search is performed instead of making the trouble to input the second term.The properties module 210 may analyze the digital content 272 to determine whether word patterns resulting from the use of self-completion / predictive search / predictive sentence suggestions typically installed and operating on mobile devices are in the digital content 272.The properties module 210 may determine whether the digital content 272 includes the availability property of the location information. The digital content 272 may have the capability to provide locations associated with the digital content 272 to a search engine. When a search engine searches the digital content 272 or otherwise determines information about the digital content 272, the digital content may provide location data to the search engine so that the search engine associates the digital content 272 with that location. Thus, a search engine may generate search results that include the digital content 272 when a search is performed that includes a space parameter. For example, digital content 272 may be a web entry for a burger restaurant in Oakland, California. In a search for "Burger Oakland", the web entry may not be identified by the search engine if the search engine's digital content has not indicated that the digital content is associated with Oakland.The properties module 210 may determine whether the digital content 272 includes the mobile device flag property. A mobile device flag may be included in the digital content to indicate when the digital content is requested by a mobile device. For example, the mobile device flag may be a method that analyzes a request for digital content from a device to determine whether the request is from a mobile device. If the mobile device flag determines that the request is from a mobile device, the mobile device flag may indicate certain portions of the digital content to the mobile device or direct the request to certain portions of the digital content. For example, if the digital content is a web incident, the web occurrence may be a subdomain with web pages designed for mobile devices (e.g., m.dot), or specific content designed for mobile devices, which is applied using cascading style sheets (step-like design templates). If the web entry detects a mobile device's request for the web entry, the web entry may direct the mobile device to the mobile subdomain or apply mobile device cascade style sheets to the content sent to the mobile device.The properties module 210 may indicate to the optimization module 220 which properties the digital content 272 contains. The optimization module may be configured to determine optimizations that may be applied to the digital content 272 based on the characteristics of the digital content 272. In some embodiments, the optimization module 220 may determine the optimizations that may be applied to the digital content 272 based on the characteristics that are absent from the digital content 272.For example, the digital content 272 may lack a mobile device flag. The optimization module 220 may determine that an optimization for the digital content 272 may be to add a mobile device flag.In some embodiments, the optimization module 220 may review the keyword types present in the digital content 272. In these and other embodiments, the optimization module 220 may retrieve database keywords 282 from the second database 280 and compare the keywords in the digital content to the database keywords 282. If the optimization module 220 determines that the digital content 272 lacks a keyword from the database keywords 282, then optimization of the digital content 272 may be to include the missing keyword. The database keywords 282 used by the optimization module 220 may vary depending on the type of digital content being optimized. For example, keywords may be different depending on locations associated with the digital content.In some embodiments, the optimization module 220 may be further configured to optimize portions of the digital content 272 depending on the characteristics detected by the characteristics module 210. For example, the optimization module 220 may determine that the database keywords 282 are added to the portions of the digital content 272 that are configured to be sent to mobile devices rather than other portions of the digital content 272. The database keywords 282 may be managed by a keyword manager. A keyword manager is described with reference to FIG. 4.The reporting module 230 may be configured to receive optimizations for the digital content 272 from the optimizing module 220 and to represent the optimizations in a report. The report may be sent to a device that controls the content of the digital content 272 to allow the enterprise to correct the content of the digital content 272. In some embodiments, the reporting module 230 may be configured to generate recommendations based on the optimizations from the optimizing module 220 and include the optimizations in the report. Alternatively or additionally, the recommendations may be displayed to a company outside the report representing the optimizations. In some embodiments, optimizations and / or recommendations may be prioritized based on web analytics collected with respect to digital content 272, as explained below.Processor 240 may be configured to execute computer instructions that cause properties module 210, optimization module 220, and reporting module 230 to perform the functions and operations described herein. The computer instructions may be loaded into the memory 250 for execution by the processor 240, and / or data generated, received, or utilized during execution of the functions and operations described herein may be stored at least temporarily in the memory 250.The interface module 260 may be configured to receive data from other systems, users, and / or other processes via any type of communication network and / or send data from other systems, users, and / or other processes. In some embodiments, the interface module 260 may be configured to receive the digital content 272 and store the digital content in the database 270 and / or the memory 250.The properties module 210, the optimization module 220, and the reporting module 230 may each be implemented in any suitable manner, such as a program, software, library, application, script, function, software as a service, analog or digital circuitry, or any combinations thereof. Changes, additions, or omissions may be made to the digital content auditor 200 without departing from the scope of the present disclosure. For example, the auditor 200 may be configured with any number of different modules that aid in checking the digital content.FIG. 3 is a flow diagram of an example method 300 for optimizing digital content for searches performed on mobile devices in accordance with some embodiments described herein. The method 300 may be implemented by a digital content auditor, such as the digital content auditor 200 of FIG. 2, in some embodiments. although shown as standalone, different blocks may be divided into additional blocks, merged into fewer blocks, or removed depending on the desired implementation.The method 300 may begin at block 302, where digital content including one or more pages may be received. In some embodiments, the digital content may be a web entry and the one or more pages may be web pages of the web entry.At block 304, the digital content may be analyzed to determine one or more characteristics of the digital content related to the placement of a reference to the digital content in search results of a mobile device. In some embodiments, the placement in the search results of the mobile device may include, among other things, a ranking of the digital content in the search results of the mobile device, a page location of the digital content in the search results of the mobile device, a pixel location of the digital content in the search results of the mobile device.At block 306, the characteristics of the digital content may be analyzed to determine one or more optimizations to apply to the digital content to improve the placement of the reference to the digital content in the search results of the mobile device. In some embodiments, the one or more characteristics of the digital content may include, but are not limited to, a size of one or more of the one or more pages, a compression ratio of one or more of the one or more pages, a cache control setting for the server hosting the digital content, a keyword type, availability of location information, a mobile device flag, a mobile device subdomain, and mobile device specific content.In some embodiments, the keyword type property may include, among other things, the length of keywords, keywords associated with a self-completion function used by a mobile device, and keywords associated with a word in the digital content. In some embodiments, the self-completion function used by the mobile device may include a predictive word search function and a predictive sentence search function.In some embodiments, the mobile device flag property may include the digital content configured to redirect a server to one or more of the pages of the digital content configured for a device that requested the digital content. For example, the device that requested the digital content may be a mobile device, and the one or more of the pages of the digital content configured for the mobile device may include the mobile device subdomain and the mobile device specific content. In these and other embodiments, the mobile device may be, but is not limited to, a tablet, a smartphone, a feature phone, a storage device, a music device, and a gaming device. At block 308, a report containing the optimizations may be generated.Those skilled in the art will appreciate that for this and other methods and methods described herein, the functions performed in the methods and methods may be implemented in a different order. Further, the steps and operations provided are merely exemplary, and some of the steps and operations may be optional, may be merged into fewer steps and operations, or may be expanded into additional steps and operations without departing from the spirit of the disclosed embodiments.For example, if the property of the digital content includes a keyword type, method 300 may further include generating a map with the keyword locations that evaluates the performance of searching keywords depending on the search locations, wherein one of the optimizations to apply to the digital content includes capturing a keyword from the keyword location. In these and other embodiments, the performance of searching the keywords may be based on the search set of keywords.In some embodiments, the method 300 may further include, if the property of the digital content includes the availability of location information, and if upon analyzing the availability of the location information, the digital content turns out to include location information, determining whether the location information includes one or more of the following fields: an address field, a business time field, a map field, a telephone number field, among others.In some embodiments, the method 300 may further include, when the property of the digital content includes availability of the location information, and when analyzing availability of the location information, the digital content turns out to include location information, searching for second digital content that is separate from the digital content for the location information, the second digital content being executed by a third party. For example, the second digital content may be a database and may be obtained from Yelp, Four Square, City search, Google Place, Google+ local, or another third party that collects and stores data and physical business seats with digital content. In these and other embodiments, the method 300 may further include analyzing the location information on the second digital content for format and accuracy. In some embodiments, one of the one or more optimizations to apply to the digital content may include updating the location information.In some embodiments, the recommendations may be automatically implemented in the digital content. In some embodiments, the method 300 may be implemented by a system that changes the digital content or may change the digital content. In some embodiments, the method 300 may be implemented by a system that is separate from the system that changes the digital content. In these embodiments, the recommendations may be sent automatically to the system, which may implement the changes to the digital content. In these and other embodiments, the systems may communicate through a programming interface (API).An example of optimizing digital content for searches performed on a mobile device is presented below. A company, such as a company that manufactures shoes, may have a company web entry on the Internet. The company may also have images of shoes and other digital content representing the shoes, such as specific pairs of shoes and the corresponding price, available over the Internet, which may be searched by search engines. A web entry may be received and analyzed to determine the characteristics of the web entry. It may be determined that the web entry has a list of keywords, a mobile device flag that mobile device users direct to a mobile device domain with content optimized for mobile devices, and a page size and compression ratio of the pages. The properties are then analyzed. For example, if it is determined that the amount of pages or the size of the pages is so great that the time taken for a mobile user to download or display the pages is very long compared to the business competition web occurrences, then an optimization may be to reformat pages to be more compatible for mobile devices. In other examples, the analysis may indicate that location-specific keywords, shorter keywords, or keywords matched to predictive keyword searches generated on mobile devices that are not part of the web entry are to be included in the web entry.FIG. 4 exemplarily illustrates a keyword manager 400 arranged according to some of the embodiments described herein. The keyword manager 400 may include the network 102 operatively coupling a management module 412, a search result computing system 430, a location selector 440, a search engine 442, and a keyword database 450. Although these elements are separately illustrated, it is understood that the elements may be combined as desired. Further, although one of each element is illustrated, the keyword manager 400 may optionally include any number of each of the illustrated elements.The management module 412 may be configured to manage keywords for use in optimizing digital content for searches performed with mobile devices and / or other functions. The management module 412 may include sub-modules for implementing certain functionalities. The management module 412 may include and be generic to an analysis module 422, a determination module 424, and a reporting module 426.The search result computing system 430 may include a search result database 432, which may store one or more search results 434, which may include search results of the search engine 442, as well as digital content included in or referenced by the search results. Alternatively or additionally, the search result database 432 may also store data collected from the one or more search results.The search result computation system 430 may be configured to obtain the search results 434 by initiating a search to be performed by the search engine 442 that uses one or more keywords found in the search term database 450. In some embodiments, the search result computation system 430 may be configured to search using search keywords, the keywords resulting from a self-completion function, a predictive word search function, and / or a predictive sentence search function of a mobile device. In some embodiments, the keywords may be keywords unrelated to the self-completion function, a predictive word search function, and / or a predictive sentence search function of a mobile device.The search result computing system 430 may be configured to obtain the search results 434 by initiating a search to be performed by the search engine 442 using one or more locations found in the search term database 450 for each of the one or more keywords in the database. The location selector 440 may select a location for which the search may be performed. For example, the location selector 440 may select a geographic area, such as a country, state, region, city, neighborhood, or zip code, for which the search may be performed by the search engine 442. In some embodiments, the search selector 440 may correct one or more settings of the search engine that allow a location where the search is to be performed to be set to select the location for which the search may be performed. In other embodiments, the search selector 440 may select servers located at the selected location to perform the search to select the location for which the search may be performed. Alternatively or additionally, search selector 440 may send signals to search engine 442 such that search engine 442 relates a location to the search. These signals may include information such as, but not limited to, an IP address, GPS coordinates, cell towers in a wireless communication system, and names of cities along with keywords.The following is an example of a location-based search: a user executing a search in San Francisco may select a setting in a search engine to indicate that the search is being executed in San Francisco. Thus, the search engine has the ability to tailor searches to the user. For example, a search for the search term "pizza restaurant" may generate results for pizza jam events at arbitrary locations when no location is specified in a search engine. On the contrary, if a location is set in a search engine, either by a user or automatically by the search engine based on an IP address of the user or other information such as a term in the search string, the search results provided by the search engine may include pizza restaurant in the vicinity of the location where the search is performed.In some embodiments, the search results obtained by the search engine may vary according to previous searches performed by the user. For example, in some embodiments, a search engine may take a profile of a user into account when generating the search results. In some embodiments, a user's profile may be based on a previous search history that appears at the same IP address or Mac address. For example, a user's profile may be based on a user's previous search history determined by cookie or other digital information stored on an electronic device on which the user performs a search. In some embodiments, a user's profile may be based on a previous search history stored on a server. For example, a user may be stored with a search engine, and the search engine may store a history of the user's searches. In some embodiments, a user's profile may be based on the user's previous search history generated during a current search session. For example, if a user has performed a first search and then performed a second search that relates to the first search, based on the results from the first search, the results generated by the search engine for the second searcher may be based on the first search performed by the user.In some embodiments, the search result computation system 430 may be configured to obtain the search results 434 by requesting a search to be performed by the search engine 442, wherein the search result computation system 430 serves as one of a plurality of types of devices. For example, the search result computing system 430 may send the request to the search engine 442, which serves as a mobile device or a non-mobile device. Alternatively or additionally, the search result computing system 430 may send the request to the search engine 442, which serves as a particular type of mobile device, such as a smartphone or feature phone.In some embodiments, the search result computation system 430 may obtain multiple search results 434 based on numerous search configurations that may be sent to the search engine 442. For example, for each device or device group, searches with different locations and different keywords may be performed to obtain the search results 434.Information about the search results 434 may be collected by searching the search results 434. In some embodiments, the search results 434 may be searched using a low index engine, such as low index engine 108 of FIG. 1. In some embodiments, the information about the search results 434 may be collected in a different manner.Referring back to the management module 420, the analysis module 422 may be configured to analyze the information for each of the search results 434. The analysis module 422 may include one or more algorithms for analyzing the information from the search results 434. For example, the analysis module 422 may analyze information from each of the search results 434 to identify whether the search results 434 include references to digital content. Additionally or alternatively, the analysis module 422 may correlate the search results 434.The determination module 424 may include one or more algorithms for processing data originating from the analysis module 422. For example, the determination module 424 may be configured using the data originating from the analysis module 422 to determine a position for digital content or a reference to digital content in each of the search results 434 or in a subset of the search results 434. Additionally or alternatively, the determination module 424 may be configured to determine a number of searches performed on a search engine for one or more keywords from a first location. Additionally or alternatively, the determination module 424 may be configured to determine a number of searches performed on the search engine for one or more keywords from a first location, wherein one or more of the search terms is a second location. For example, the determination module 424 may be adapted to determine a number of searches performed for the keyword "Hotels in New York" from Chicago, or any other location. The determination module 424 may be adapted to determine a number of searches performed based on information received from the search engine 442. For example, the search engine 442 may publish information related to the frequency of searches performed using the keyword "hotels in New York" along with other information related to the searches performed at specific locations, such that the determination module 424 may determine the number of searches performed.The reporting module 426 may compile information from the analysis module 422, the determination module 424, or both to generate a report and generate recommendations regarding, among other things, keyword performance based on location, keyword type, device types. The keyword capability may be based on a position of digital content relating to a business in a search result. Thus, a keyword that generates a search result with digital content in the search result in a position better than another keyword can be regarded as a keyword with better keyword performance.For example, the reporting module 426 may be configured to generate reports that compare the performance of keywords derived from self-completion functions, predictive word search functions, and / or predictive sentence search functions with keywords not corresponding to this keyword type in searches performed by mobile devices. Based on this information, the management module 412 may be configured to provide keywords to the digital content to improve the digital content for searching by mobile devices as described with reference to FIG. 3.In some embodiments, the reporting module 426 may be configured to generate reports that compare the performance of keywords at locations to different granularity levels. For example, the reporting module 426 may be suitable for reporting keyword capability over various cities, city areas, zip codes, or other areas. Based on the report, the management module 412 may propose different keywords associated with different locations to optimize the digital content for searching by mobile devices as described with reference to FIG. 3.In some embodiments, the reporting module 426 may be configured to generate reports that compare the performance of keywords across different device types. For example, the reporting module 426 may report the capability of various keywords in non-mobile devices and mobile devices.In some embodiments, the reporting module 426 may also be configured to generate reports indicating search sets of keywords based on the geographic location where the search is performed. In these and other embodiments, the reports may emphasize locations where many searches are performed for a particular keyword. In these and other embodiments, the management module 412 may suggest to relate the use of the often used keywords to a content location that is related to the location to increase the ability of digital content to appear in a search result. For example, a web entry may be associated with a restaurant in New York. A local newspaper report may have advanced the restaurant to the foreground in a top-ten list. The top-ten list may be a keyword that receives multiple searches in New York. The management module 412 may indicate that the web entry for the restaurant includes the keyword of the top-ten list to increase the probability of the web entry such that the restaurant is part of the search result.In other embodiments, the management module 412 may perform click-through rate (CTR) tracking that compares and distinguishes CTRs on mobile devices from non-mobile devices. Such a system could use this information combined with other information to provide performance reporting for broader web management.FIG. 5 is a flow diagram of an example method 500 of location-based search engine optimization, in accordance with some embodiments described herein. The method 500 may be implemented by a management module, such as the management module 412 of FIG. 4, in some embodiments. although illustrated as discrete blocks, different blocks may be divided into additional blocks, combined into fewer blocks, or removed depending on the desired implementation.The method 500 may be at block 502, where a first search may be performed on a network with a search engine using a first keyword to obtain first search results, the first search based on a first location. The first search based on the first location may indicate that the first location is a parameter used by the search engine when executing the first search. At block 504, a first location for a reference to digital content within the first search results may be determined.At block 506, a second search may be performed on the network with the search engine using a second keyword to obtain second search results, the second search based on a second location. In some embodiments, the first and second locations may be the same type of locations. For example, both of the first and second locations may be one of the following: countries, cities, metropolitan regions, residential areas, zip codes, federal countries, providens, countries, or regions. Alternatively, one of the first and second locations may be one of the above listed types of locations and another of the first and second locations may be another of the above listed types of locations. For example, the first location may be a zip code and the second location may be a city.In some embodiments, the first search and the second search may be performed using a mobile device or a non-mobile device. In some embodiments, the first location may be in a first country and the second location may be in a second country different from the first country. For example, the first location may be in the United States and the second location may be in France.In some embodiments, the first keyword may be the same as the second keyword, and the first and second keywords need not include the first location and the second location. In these and other embodiments, the search requesting device may indicate its location to the search engine, such that the search engine may include the location of the device within the search parameters when executing the search. Alternatively or additionally, the first keyword may include the first location and the second keyword may not include the location. In these and other embodiments, the device may provide its location in requesting the second search, rather than the first search.In some embodiments, one or both of the first keyword and the second keyword include a group of keywords. In these and other embodiments, a search may be performed and a location for the reference to the digital content found for each of the keywords in the group.In block 508, a second location for the reference to the digital content may be determined within the second search results. In some embodiments, the first position and the second position may be a rank of the reference to the digital content within the first and second search results. In some embodiments, the second position and the first position may be the same. Alternatively or additionally, the second position and the first position may be different.At block 510, a recommendation based on the first position and the second position may be generated to adjust the digital content to improve the position of the reference to the digital content within one or both of the first and second search results. Adjusting the digital content may include adjusting one or more aspects of the digital content by changing, adding, and / or deleting one or more of: content, links, HTML header, data within the HTML header, among other things, content. Alternatively or additionally, adjusting the digital content may include adjusting location data for the digital content. For example, the location data for the digital content may be accessed and analyzed to determine various characteristics of the location data, and corrections may be made to the location data. More information on accessing, analyzing, and correcting location data is discussed in reference to Figures 6 and 7. In some embodiments, a report may be generated at block 510 to indicate the first position and the second position for the keywords.One skilled in the art will appreciate that for these and other processes and methods disclosed herein, the functions performed in the processes and methods may be implemented in a different order. Further, the illustrated steps and operations are provided merely as examples, and some of the steps and operations may be optional, combined into fewer steps and operations, or extended into additional steps and operations without departing from the spirit of the disclosed embodiments.For example, the method 500 may further include performing multiple searches on the network, wherein each of the multiple searches is performed using the keyword to obtain a plurality of search results. Each of the plurality of searches may be based on a different location and / or keyword. In some embodiments, the locations may be randomly assigned. In some embodiments, the locations may be preselected based on user input. The number of multiple searches may be large, for example, the number of multiple searches may be greater than 1,000, 10,000, 100,000, or more. The method 500 may further include identifying a location for the reference to the digital content within each of the plurality of search results and generating the recommendation based on the first location, the second location, and the location for each of the plurality of search results. In some embodiments, the method 500 may not include generating the recommendation. In some embodiments, the method 500 may include generating a report representing the positions for each of the keywords at each of the different positions. Providing a report representing the positions for each of the keywords may allow analysis to be performed to search digital content and how search engines search and bypass the digital content.In some embodiments, the recommendations may be automatically inserted into the digital content. In some embodiments, the method 500 may be implemented by a system that changes the digital content or may change the digital content. In some embodiments, the method 500 may be implemented by a system separate from the system that changes digital content. In these embodiments, the recommendations may be automatically sent to the system, which may implement the changes to the digital content. In these and other embodiments, the systems may communicate through an API.In some embodiments, the method 500 may further include generating a second recommendation based on the first location and the second location to set an aspect of the reference to the digital content to improve the location of the reference to the digital content within one or both of the first and second search results. In some embodiments, the recommendation and the second recommendation may be prioritized based on web analytics collected regarding the reference to the digital content. In these and other embodiments, the web analytics may be collected by a low-index engine and / or correlator, such as low-index engine 108 and correlator 104 of FIG. 1. In these and other embodiments, the web analytics may include, among other metrics, a number of visits to the reference to the digital content, a number of conversions per visit. Based on these metrics, the recommendation that may result in the greatest increase in traffic, conversions, revenue, or any other metric may be given priority over other recommendations.In some embodiments, the method 500 may further include determining a third location for a reference to other digital content within the first search results. The other digital content may be controlled and operated by a company different from the company that controls and operates the digital content. In some embodiments, the enterprise that controls and serves the other digital content may be a competitor of the enterprise that controls and serves the digital content.In these and other embodiments, the method 500 may further include determining a fourth location for reference to the other digital content within the second search results and comparing the third and fourth locations to the first and second locations, respectively. If one or both of the third and fourth positions are respectively higher than the first and second positions, or, in other circumstances, for example, if the third and fourth positions are both lower than the first and second positions, the method 500 may include generating a recommendation to adjust the digital content to include location data related to the reference to the other digital content.The method 500 follows an example: A store, such as a restaurant, may have digital content, such as a web entry, that provides information about the restaurant to users of the web entry and location information about various physical locations of the restaurant. The restaurant may have physical locations worldwide. Using method 500, the restaurant may gain insight into what performance the restaurant's web occurrence yields in organic searches performed at different locations. For example, the web entry may take a fourth rank when a search for "best steak restaurant" is performed in Miami, and a twelfth rank when a search for "best steak restaurant" is performed in Chicago. By understanding the differences in rankings, the web occurrence can be adjusted to improve ranking in Chicago. In some cases, the search result ranking of the restaurant's web entry at different locations may be compared to the search result ranking of a competitor's restaurant's web entry at the same locations. The restaurant's web entry may be adjusted to include aspects of the competitor's restaurant's web entry when the competitor's restaurant is higher in rank in search results than the restaurant's web entry. For example, the location data of the restaurant's web entry can be matched to the location data of the competitor's restaurant's web entry.FIG. 6 is a block diagram of an example of a location data manager 600 in accordance with some embodiments described herein. The location data manager 600 may be communicatively coupled to a database 670 directly or indirectly through a network or through one or more other devices. The location data manager 600 may include, but is not limited to, a properties module 610, an optimization module 620, a recommendation module 630, a processor 640, a memory 640, and an interface module 650. The location data manager may be configured such that the properties module 610, the optimization module 620, the recommendation module 630, the processor 640, the memory 650, and the interface module 660 may communicate with each other and share information. Database 670 may include location data 672.The location data 672 may be data associated with a physical location of a business, society, or any other business. In some embodiments, location data 672 may be located on the digital content of the business, society, or any other business. In some embodiments, location data 672 may be included in various digital content, such as a web entry that includes location data for various companies, for example, but not limited to, Google+local, Yelp, CityEar. The location data 672 may include various fields. For example, location data 672 may include a phone number field for a phone number of the physical location. Alternatively or additionally, the location data 672 may include, but is not limited to, an address field for the physical address, a map field for a map containing the physical address, a business time field for the operating times at the physical location. For example, a web entry for a retail store may have location data, such as the address of one or more of the retail stores on the web entry and the operating times for that retail store.In some embodiments, database 670 may be part of a content management system (content management system) that generates the digital content that may include the location data. In these and other embodiments, the location data 672 may be a data store or file that provides the information for the digital content to the editor system. Setting the data store or file may result in the digital content being set. In these and other embodiments, the location data manager 600 may be part of the redaction system or may be capable of associating with the redaction system.In some embodiments, database 670 may be part of a system that is separate from the system that manages or provides the digital content associated with location data 672. In these or other embodiments, database 670 may be controlled and served by a third party. For example, database 670 may be part of a web entry that provides location data 672 on the Internet for physical stores such as Yelp, Google+ Loc, CityEar, or any other enterprise. In these and other embodiments, location data manager 600 may be configured to interface with database 670 to allow location data manager 600 to receive location data from database 670 and send location data thereto.In some embodiments, the properties module 610 may be configured to receive the location data from the database 670. For example, the properties module 610 may be part of a redaction system that includes the location data 672. In these and other embodiments, the properties module 610 may access the files with the location data 672. In some embodiments, the properties module 610 may access the location data 672 by searching third party digital content. For example, the properties module 610 may search Yelp or any other web entry that provides the location data 672 to access the location data 672.The properties module 610 may also be configured to analyze the location data 672 to determine the properties of the location data 672 related to the placement of a reference to the digital content in location-specific search results. Location-specific search results may be search results based at least in part on a location parameter considered in generating the search results. For example, a mobile device may request a search for hamburgers and send an indication of its current location. The search engine may perform a search for hamburgers that contain the parameter of the current location of the mobile device and generate results based on the parameter, for example hamburger locations near the physical location of the mobile device. If digital content does not contain appropriate location information, the search engine does not need to display the digital content in the search results.The various characteristics may be determined by analyzing the digital content. For example, the HTML code or other code and other aspects of a web entry may be analyzed to determine the properties of the web entry.The various characteristics of the location data 672 that may be determined by the characteristics module 610 include, but are not limited to, accuracy of the location data 672, data field types, and data field formatting. The data field types may include, but are not limited to, those discussed above, such as a telephone number field, an address field, a card field, and a business hour field. The data fields available in the location data 672 may affect how a search engine may handle digital content associated with the location data 672. For example, a search engine may preferentially handle digital content associated with location data 672 including a map field and an address field. If digital content does not include either of these fields, the digital content may not be placed in search results or at a worse location in the search results.The accuracy of the location data property may be related to the accuracy of the location data 672. One or more of the fields of location data 672 may change for one or more physical locations of a business. The accuracy of the location data property may depend on how accurate the location data 672 is.The data field formatting may be related to how the location data 672 is formatted. For example, for the phone number field, the phone number may include a location prefix, a country prefix, a guide digit, a dash between number groupings, among other formatting questions for a phone number. Formatting the data fields may affect how a search engine may handle the data fields. For example, a data field that is incorrectly formatted does not need to be considered by the search engine, resulting in the digital content associated with the data field not being displayed in search results generated by the search engine.The properties module 610 may indicate to the optimization module 620 which properties include the location data 672. The optimization module 620 may be configured to determine optimizations that may be applied to the location data 672 based on the characteristics of the location data 62. In some embodiments, the optimization module 620 may determine the optimizations that may be applied to the location data 672 based on the characteristics that the location data 672 is missing.For example, the optimization module 620 may determine an optimization for adjusting the format of one or more of the location data fields. In some embodiments, optimization module 620 may receive indications of optimizations to be performed from interface module 660. These indications may be based on comparisons between location data of the digital content and location data of other digital content. The other digital content may be digital content controlled by a competitor or other digital content of the enterprise. In some embodiments, the other digital content may be placed higher in search results than the digital content. In these and other embodiments, the optimization module 620 may receive an indication of the location data for the other digital content. Based on the characteristics of the digital content, the optimization module 620 may determine optimizations for the location data 672 of the digital content such that the location data is more analog to or more closely matched to the location data of the other digital content. For example, the location data of the other digital content may include business hours and the location data 672 of the digital content may not include business hours. An optimization may be to include the business times in the location data 672.In some embodiments, the optimization module 620 may directly perform the optimizations on the location data 672. For example, the optimization module 620 may send new location data 672 to the database 670. For example, the optimization module 620 may rewrite a file in a redaction system to perform the optimizations on the location data 672. Alternatively or additionally, the optimization module 620 may interface with the database 670 when the database 670 is controlled by a third party and present the new location data 672 to the database 670.The recommendation module 630 may be configured to receive optimizations for the location data 672 from the optimization module 620 and present the optimizations in a report or generate recommendations regarding optimization of the location data. The report may be sent to a company that controls the content of the digital content 672 to allow the company to adjust the content of the digital content 672.The processor 640 may be configured to apply computer instructions that cause the properties module 610, the optimization module 620, and the recommendation module 630 to perform the functions and operations described herein. The computer instructions may be loaded into the memory 650 for application by the processor 640 and / or data that was generated, received, or processed during performance of the functions and operations described herein may be stored at least temporarily in the memory 650.The interface module 660 may be configured to receive data from and / or send data to other systems, users, and / or other processes via any type of communication network. In some embodiments, the interface module 660 may be configured to receive the location data 672 and store the location data 672 in the database 670 and / or the memory 650.The properties module 610, the optimization module 620, and the recommendation module 630 may each be implemented in any suitable manner, such as a program, software, library, application, script, function, software as service ("software as service"), analog or digital circuitry, or any combination thereof. Changes, additions or omissions may be made to the location data manager 600 without departing from the scope of the present disclosure. For example, location data manager 600 may be configured to include any number of different modules.FIG. 7 is a flow diagram of an example method 700 for optimizing web occurrence by managing location data, in accordance with some embodiments described herein. The method 700 may be implemented by a location data manager, such as location data manager 600 of FIG. 6, in some embodiments. Although illustrated as discrete blocks, different blocks may be divided into additional blocks, combined into fewer blocks, or removed depending on the desired conversion.The method 700 may begin at block 702, where location data in a location database may be accessed. The location data may be associated with and available on a web entry of a business, and the location data may include information about at least one physical location of the business. In some embodiments, the location database may be part of a redaction system that generates the web entry. Alternatively or additionally, the location database can be part of a database external to the web entry and controlled by a third party. For example, the location database may be controlled by Yelp, Google+ Loc, or any other digital content provider.At block 704, the location data may be analyzed to determine one or more characteristics of the location data that relates to placement of a reference to the web occurrence in location-specific search results. In some embodiments, the one or more characteristics of the location data may include, but are not limited to, accuracy of the location data, data field types, data field formatting. In some embodiments, the data field types may include, but are not limited to, an address field, a map field, a phone number field, a business time field.At block 706, the characteristics of the location data may be analyzed to determine one or more optimizations for application to the location data to improve the placement of the reference to the web entry in the location-specific search results. At block 708, one or more recommendations for adjusting the location data may be generated based on the optimizations.In some embodiments, the recommendations may be automatically introduced into the digital content. In some embodiments, the method 700 may be implemented by a system that changes the digital content or may change the digital content. In some embodiments, the method 700 may be implemented by a system separate from the system that changes digital content. In these embodiments, the recommendations may be automatically sent to the system, which may introduce the changes to the digital content. In these and other embodiments, the systems may communicate through an API.One skilled in the art will appreciate that for these and other processes and methods disclosed herein, the functions performed in the processes and methods may be implemented in a different order. Further, the illustrated steps and operations are provided merely as examples, and some of the steps and operations may be optional, combined into fewer steps and operations, or extended into additional steps and operations without departing from the spirit of the disclosed embodiments.Some embodiments described herein include a computer program product having computer executable instructions for causing a computing system including the computer program product to perform a computing method of the computer executable instructions to increase search engine optimization (SEO) performance of the digital content. The computing method may be any method described herein performed by a computing system. The computer program product may be located on a computer storage device, which may be removable or integral with the computing system.Some embodiments described herein include a computing system capable of performing the methods described herein. As such, the computing system may include a storage device having the computer-executable instructions for performing the method.In some embodiments, a computing device, such as a computer or storage device of a computer, may include a determination module and a reporting module. The determination module and reporting module may be configured to perform any of the methods described herein. Additionally, the determination module and the reporting module may be combined into a single module or on a single platform. In some embodiments, a computer program product may include one or more algorithms for performing any methods of any of the claims.One skilled in the art will appreciate that for these and other processes and methods disclosed herein, the functions performed in the processes and methods may be implemented in a different order. Further, the illustrated steps and operations are provided merely as examples, and some of the steps and operations may be optional, combined into fewer steps and operations, or extended into additional steps and operations without departing from the spirit of the disclosed embodiments. It should also be appreciated that any module or component described herein(s) could implement the functionalities associated with the name of the module or component.One skilled in the art will appreciate that for these and other processes and methods disclosed herein, the functions performed in the processes and methods may be implemented in a different order. Further, the illustrated steps and operations are provided merely as examples, and some of the steps and operations may be optional, combined into fewer steps and operations, or extended into additional steps and operations without departing from the spirit of the disclosed embodiments. It should also be appreciated that any module or component described herein(s) may implement the functionalities associated with the name of the module or component.The present disclosure is not intended to be limited to the particular embodiments described in this application, which are intended as illustrations of various aspects. Many modifications and variations may be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Functionally equivalent methods and apparatus within the scope of the disclosure will be apparent to those skilled in the art in addition to those enumerated herein from the foregoing descriptions. Such modifications and variations are intended to fall within the scope of the appended claims. The present disclosure is intended to be limited by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled. It is to be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting.In an illustrative embodiment, any of the operations, processes, etc. described herein may be implemented as computer readable instructions stored on a computer readable medium. The computer readable instructions may be executed by a processor of a mobile unit, a network element, and / or any other computing device.There remains little difference between hardware and software implementations of aspects of systems; the use of hardware or software is generally (but not always so that in certain contexts the choice between hardware and software may be critical) a design dependent choice that is a compromise of cost versus efficiency. There are various vehicles by which processes and / or systems and / or other technologies described herein may be touched (e.g., hardware, software, and / or firmware), where the preferred vehicle will vary contextually with respect to the processes and / or systems and / or other technologies employed. For example, if an implementor determines that speed and accuracy are predominant, the implementor may predominantly decide on a hardware and / or firmware vehicle; if flexibility is predominant, the implementor may decide on a principal software implementation; or, as another alternative, the implementor may decide on any combination of hardware, software and / or firmware.The foregoing detailed description has set forth various embodiments of the processes using block diagrams, flowcharts, and / or examples. Inasmuch as such block diagrams, flowcharts, and / or examples include one or more functions and / or operations, it will be understood by those skilled in the art that each function and / or operation within such block diagram, flowchart, or example is individually and / or collectively implementable over a wide range of hardware, software, firmware, or virtually any combination thereof. In some embodiments, multiple portions of the subject matter described herein may be implemented using application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), digital signal processors (DSPs), or other integrated formats. However, those skilled in the art will appreciate that some aspects of the embodiments disclosed herein may be implemented in integrated circuits in a totally or partially equivalent manner, as one or more computer programs executing on one or more computers (e.g., as one or more programs executing on one or more computer systems), as one or more programs executing on one or more processors (e.g., as one or more programs executing on one or more microprocessors), as firmware, or as virtually any combination thereof, and that the design of the circuits and / or the writing of code for the software and / or firmware will be readily realizable by those skilled in the art in light of the present disclosure. In addition, those skilled in the art will appreciate that the mechanisms of the subject matter described herein may be distributed as a program product in a variety of forms and that an illustrative embodiment of the subject matter described herein applies regardless of the particular type of signal bearing medium used to actually perform the distribution. Examples of a signal bearing medium include, but are not limited to: a recordable medium such as a floppy disk, a hard disk drive, a CD, a DVD, a digital tape, a computer memory, etc.; and a transmission medium such as a digital and / or analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communication link, a wireless communication link, etc.).Those skilled in the art will appreciate that it is common in the art to describe devices and / or processes as set forth herein and thereafter apply engineering practices to integrate such described devices and / or processes into data processing systems. That is, at least a portion of the devices and / or processes described herein may be incorporated into a data processing system using a reasonable experimentation effort. Those skilled in the art will appreciate that a typical data processing system generally includes one or / or more of a system unit housing, a video display device, memory such as volatile and non-volatile memory, processors such as microprocessors and digital signal processors, computing units such as operating systems, drivers, graphical user interfaces and application programs, one or more interaction devices such as a touchpad or screen, and / or control systems including feedback loops and control motors (e.g., feedback for sensing position and / or velocity; control motors for moving and / or adjusting components and / or amounts). A typical data processing system may be implemented using suitable commercially available components, such as those commonly found in data accounting / communication and / or network accounting / communication systems.The subject matter described herein sometimes illustrates other components included or associated therewith. It is understood that such illustrated architectures are to be considered exemplary only and that indeed, numerous other architectures may be implemented that achieve the same functionality. In a conceptual sense, any arrangement of components for achieving the same functionality is effectively "related" such that the desired functionality is achieved. Thus, any two components herein that are combined to achieve a particular functionality may be considered "related to each other," such that the desired functionality is achieved regardless of the architecture or intermediate components. Accordingly, any two components so associated may also be considered "operatively connected" or "operatively coupled" to each other to achieve the desired functionality, and any two components that may be associated may also be considered "operatively coupled" to each other to achieve the desired functionality. Specific examples of operative connectivity include, but are not limited to, physically mateable and / or physically interactive components and / or wirelessly interactable and / or wirelessly interactive components and / or logically interactive and / or logically interactable components.The embodiments described herein may involve the use of a special purpose or general purpose computer, including various computer hardware or software modules.Embodiments within the scope of the present invention also include computer readable media having or carrying computer executable instructions or data structures stored thereon. Such computer readable media may be any available medium that can be accessed by a general purpose or special purpose computer. By way of example, and not limitation, such computer readable media may comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code means in the form of computer executable instructions or data structures and which can be accessed by a general purpose or special purpose computer. When information is transmitted or provided to a computer over a network or other communication link (either hardwired, wireless, or a combination of hardwired and wireless), the computer suitably views the link as a computer readable medium. Thus, each such connection is conveniently referred to as a computer readable medium. Combinations of the above are also included within the scope of computer readable media.Computer-executable instructions include, for example, instructions and data that cause a general purpose computer, special purpose computer, or special purpose processing device to perform a particular function or group of functions. Although the subject matter has been described by specific terms for structural features and / or methodological steps, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or steps described above. Rather, the specific features and steps described above are disclosed as example forms of implementing the claims.The term "module" or "component" as used herein may refer to software objects or routines executing on the computing system. The various components, modules, engines, and services described herein may be implemented as objects or processes executing on the computing system (e.g., as separate threads). While the system and methods described herein are preferably implemented in software, implementations in hardware or in a combination of software and hardware are also possible and contemplated. In this specification, a "computing unit" may be any computing system as defined hereinabove or any module or combination of modules running on a computing system.With respect to the use of substantially any plural and / or singular term herein, as appropriate, those skilled in the art may derive the singular form from the plural form and / or derive the plural form from the singular form depending on the context and / or application. The various singular / plural possibilities may be expressly listed herein for clarity.Those within the scope of the invention will generally understand that terms used herein, and particularly in the appended claims (e.g., in the bodies of the appended claims), are generally to be understood as "open" terms (e.g., the term "comprising" is to be interpreted as "comprising, but not limited to", the term "comprising" is to be interpreted as "at least comprising", the term "including" is to be interpreted as "including, but not limited to"). Furthermore, those skilled in the art will recognize that if a particular number is intended in an introductory claim enumeration, then this is expressly recited in the claim, if such enumeration is missing, then such intent is not present. For convenience, the following appended claims may include the introductory phrases "at least one" and "one or more" to initiate claim enumerations. The use of such phrases, however, does not mean that the introduction of a claim enumeration by the indefinite articles "a / e" limits any claim containing such an introductory claim enumeration to embodiments containing only such enumeration, even though the same claim contains the introductory phrases "one or more" or "at least one" and indefinite articles such as "a / e" (e.g., "a / e" should be interpreted to mean "at least one / e" or "a / e or more"); the same applies to the use of certain articles to initiate claim enumerations. Additionally, even if a particular number of an introductory claim enumeration is explicitly recited, those skilled in the art will recognize that such enumeration should be interpreted as meaning at least the recited number (e.g., the mere listing of "two enumerations" without further modifiers means at least two enumerations, two or more enumerations). Furthermore, in those cases where a term analogous to "at least one of A, B, and C, etc." is used, the construction is generally understood in the sense that one skilled in the art would understand the indication (e.g., "a system having at least one of A, B, and C" would include, but not be limited to, systems including A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, etc.). In those instances where an indication analogous to "at least one of A, B, or C, etc." is used, such a construction is generally understood in the sense that one skilled in the art would understand (e.g., "a system having at least one of A, B, or C" would include, but not be limited to, systems having A alone, B alone, C alone, A and B together, A and C together, B and C together, and / or A, B, and C together, etc.). Furthermore, it will be understood by those skilled in the art that virtually any OR-linked word or word sequence containing two or more alternative terms, whether in the specification, claims or drawings, is to be understood as including the possibilities of one of the terms, any of the terms, or both terms being meant. The phrase "A or B" is to be understood, for example, to include the possibilities "A" or "B" or "A and B".One skilled in the art will understand that for any and all purposes, for example, to provide a written description, all of the ranges disclosed herein also include any and all possible sub-ranges and combinations of sub-ranges thereof. Each indicated range is easily recognizable as describing the same range sufficiently and enabling it to be divided into at least equal halves, thirds, quarters, fifths, tenths, etc. As a non-limiting example, each region discussed herein may be easily divided into a lower third, middle third, and upper third, etc. In addition, one skilled in the art will understand that phrases such as "up to", "at least", and the like include the number indicated and refer to ranges that can be subsequently divided into sub-ranges as described above. Finally, one skilled in the art will also understand that a range includes each individual element. For example, a group of 1-3 cells includes groups of 1, 2 or 3 cells. Similarly, a group of 1-5 cells includes groups of 1, 2, 3, 4 or 5 cells, etc.From the foregoing, it is to be understood that various embodiments of the present disclosure have been described for the purpose of illustration and that various modifications may be made without departing from the scope and spirit of the present disclosure. Accordingly, the various embodiments disclosed herein are not to be considered as limiting, and the true scope and spirit is set forth in the following claims.

Claims

A method of analyzing, reporting, and optimizing digital content (272) for searching on mobile devices (114), the method comprising: obtaining digital content (272) including one or more pages intended for display on mobile devices (114); analyzing, by a processor (240), the digital content (272) to determine one or more first characteristics of the digital content (272) that relate to the placement of a reference to the digital content (272) in the search results for mobile devices (114); analyzing, by a processor (240), the digital content (272) to determine one or more second characteristics of the digital content (272) related to configuring the digital content (272) to switch a server to one or more of the pages of the digital content (272) configured for a mobile device (114) that requested the digital content (272); analyzing the first characteristics of the digital content (272) to determine one or more first optimizations applicable to the digital content (272) to alter at least one of the first characteristics to enhance placement of a reference to the digital content (272) in the search results for mobile devices; Analyzing the second characteristics of the digital content (272) to determine one or more second optimizations applicable to the digital content (272) to alter at least one of the second characteristics to alter the digital content such that a server switches to one or more of the pages of the digital content configured for the mobile device (114) that requested the digital content; generating one or more recommendations to adjust the digital content (272) based on the first and second optimizations; and sending the one or more recommendations to adjust the digital content (272) to another system configured to translate the recommendations to optimize the digital content (272) for mobile devices (114).The method of claim 1, wherein the digital content (272) is a web entry and the one or more pages are web pages of the web entry.The method of claim 1, wherein the one or more first characteristics of the digital content (272) include a keyword type or availability of location information.The method of claim 3, wherein the keyword type includes lengths of keywords in the digital content, keywords associated with an auto-complete function used by a mobile device (114), or keywords associated with a location in the digital content (272).The method of claim 4, wherein the auto-complete function used by the mobile device (114) includes a predictive word search function and a predictive expression search function.The method of claim 1, wherein the first property of the digital content (272) includes a keyword type, the method further comprising: generating a keyword location map that evaluates the search quality of keywords (282) based on search locations, wherein one of the first optimizations to be applied to the digital content (272) includes the inclusion of a keyword (282) from the keyword location map.The method of claim 6, wherein the search quality of the keywords (282) is based on the search scope of the keywords (282).The method of claim 1, wherein the first property of the digital content (272) includes location information, wherein analyzing location information when the digital content (272) includes location information further includes determining when the location information includes one or more of the following fields: an address field, a business time field, a map or directions field, a telephone number field, and customer scores.The method of claim 1, wherein the first property of the digital content (272) includes availability of location information, and analyzing the location information when the digital content includes location information further includes: searching a second digital content separate from the digital content (272) for the location information, the second digital content being operated by a third party; and analyzing the location information in the second digital content for format and accuracy.The method of claim 9, wherein one of the one or more first optimizations to be applied to the digital content (272) includes updating location information.

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