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WO2013177230A1 - Optimisation d'engagement sur les médias sociaux - Google Patents

Optimisation d'engagement sur les médias sociaux Download PDF

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Publication number
WO2013177230A1
WO2013177230A1 PCT/US2013/042117 US2013042117W WO2013177230A1 WO 2013177230 A1 WO2013177230 A1 WO 2013177230A1 US 2013042117 W US2013042117 W US 2013042117W WO 2013177230 A1 WO2013177230 A1 WO 2013177230A1
Authority
WO
WIPO (PCT)
Prior art keywords
social media
webpages
correspondence
keyword
keywords
Prior art date
Application number
PCT/US2013/042117
Other languages
English (en)
Inventor
Lemuel S. Park
Jimmy Yu
Sammy Yu
Emeka AJOKU
Thomas J. Ziola
Original Assignee
Brightedge Technologies, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US13/476,893 external-priority patent/US8972275B2/en
Application filed by Brightedge Technologies, Inc. filed Critical Brightedge Technologies, Inc.
Priority to DE112013002594.9T priority Critical patent/DE112013002594T5/de
Publication of WO2013177230A1 publication Critical patent/WO2013177230A1/fr

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Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0201—Market modelling; Market analysis; Collecting market data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/01—Social networking

Definitions

  • Social media websites are becoming increasingly popular popular by having the abilities of connecting users and communities in a collaborative way.
  • Social media services explore the opportunities for advanced communication and also serve as an advanced content sharing mechanism. Examples include not only social networking services (SNSs), such as MYSPACE and FACEBOOK, but also telecom operator's services such as messaging, photo -sharing, person-to-person as well as conference calls and even microblogging services such as TWITTER.
  • SNSs social networking services
  • telecom operator's services such as messaging, photo -sharing, person-to-person as well as conference calls and even microblogging services such as TWITTER.
  • TWITTER has over 100 million active users generating over 250 million tweets per day (20 percent of which contain links).
  • social media websites such as TWITTER, offer an attractive channel for online marketing and sales.
  • Such methods may include identifying search engine optimization keywords utilized for at least one webpage, analyzing at least one social media website to generate analytic data related to the search engine optimization keywords contained in correspondence displayed on the at least one social media website and determining at least one type of paid advertising available from the at least one social media website based on the analytic data.
  • such methods may include collecting content from a plurality of webpages by crawling at least one network, searching the content collected from the plurality of webpages to identify references to at least one keyword, analyzing the content to determine a frequency of the references to the at least one keyword associated with at least one of the plurality of webpages, the relevant references generated by users of at least one social media website and generating a recommendation for at least one type of social media correspondence including a link to the at least one web page.
  • Such a system may include, for example, a deep index engine configured to crawl a plurality of webpages and to identify social media correspondence located on the plurality of webpages; an analyzing module configured to analyze the social media correspondence to identify references to at least one keyword in the social media correspondence and determine at least one type of social media correspondence available for purchase from at least one social media website based on the frequency of the references to the at least one keyword; and a reporting module for generating at least one report for display to a user, the report comprising a link to a portal configured to enable the purchase of the at least one type of social media correspondence.
  • analytic data may be provided that includes trending keywords or phrases, the activity of the keywords or phrases and performance of the keywords or phrases within one or more web page. Such information enables identification of keywords or phrases of importance in advertising and/or social media campaigns.
  • FIG. 1A illustrates an embodiment of a social media engagement system in accordance with the technologies described herein;
  • Figure IB illustrates another embodiment of a social media engagement system in accordance with the technologies described herein;
  • Figure 2 is a flow type diagram illustrating an embodiment of a method of increasing social media engagement in accordance with the technologies described herein;
  • Figure 3 illustrates an embodiment of a computing system that can implement some embodiments described herein.
  • embodiments disclosed herein generally relate to computing systems and computing processes used in methods of optimizing social media engagement by tracking and engaging in social media correspondence.
  • an entity can achieve greater brand visibility.
  • engaging in social media correspondence can lead to increased traffic of an entity's main webpage and better page rank for the entity's webpage.
  • Figure 1A illustrates an embodiment of a social media optimization system 100a, which can include a network 102.
  • the network 102 can be used to connect the various parts of the system 100a to one another, such as between a web server 106, a deep index engine 108, a correlator 104, and a social media optimization module 112. It will be appreciated that while these components are shown as separate, the components may be combined as desired. Further, while one of each component is illustrated, the system 100a may optionally include any number of each of the illustrated components.
  • the network 102 may include the Internet, including a global internetwork formed by logical and physical connections between multiple wide area networks and/or local area networks and can optionally include the World Wide Web ("Web"), including a system of interlinked hypertext documents accessed via the Internet.
  • the network 102 includes one or more cellular RF networks and/or one or more wired 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 can also include servers that enable one type of network to interface with another type of network.
  • the web server 106 can include any system capable of storing and transmitting a webpage to a user.
  • the web server 106 can provide access to the webpages of a website to be analyzed for improving social media optimization.
  • the web server 106 can include a computer program that is responsible for accepting requests from clients (user agents such as web browsers), and serving them HTTP responses along with optional data contents, which can include HTML documents and linked objects for display to the user.
  • the web server 106 can include the capability of logging some detailed information, about client requests and server response, to log files.
  • the website can include any number of webpages.
  • the aggregation of references to the various webpages can be referred to as traffic.
  • webpage refers to any online posting, including domains, subdomains, web posts, Uniform Resource Identifiers ("URIs”), Uniform Resource Locators ("URLs”), images, videos, or other piece of content and non-permanent postings such as e-mail and chat, unless otherwise specified.
  • URIs Uniform Resource Identifiers
  • URLs Uniform Resource Locators
  • the deep index engine 108 may be configured to crawl the webpages accessed by the webserver 106 to retrieve external data.
  • crawl and “crawling” may refer to collecting content of multiple files or sites (e.g., webpages) on the network 102 so that the content may be searched.
  • the deep index engine 108 may be configured to crawl the webpages and analyze data associated with the crawl, including on-page information and back link data (e.g., back link URL, anchor text, etc.) for each webpage.
  • the deep index engine 108 may be configured to crawl webpages via the Internet and/or via a wireless network.
  • Social media is often accessed using a mobile device (e.g., a mobile phone, a personal digital assistant (PDA), a tablet computer, etc.) through the wireless network.
  • the deep index engine 108 may utilize an algorithm or software mechanism (e.g., a crawler) to crawl the files or sites on the network 102 for the content.
  • the webpages crawled by the deep index engine 108 through the wireless network may provide user-specific and/or location-specific information.
  • a deep index engine 108 according to some embodiments is described in more detail in copending U.S. Patent Application Serial No. 12/436,704 entitled COLLECTING AND SCORING ONLINE REFERENCES, filed May 6, 2009, which application is hereby incorporated by reference in its entirety.
  • the functionalities described herein can be applied to optimizing webpages for a website.
  • a correlator 104 according to some embodiments is described in more detail in co-pending U.S. Patent Application Serial No. 12/574,069, filed October 6, 2009 entitled CORRELATING WEB PAGE VISITS AND CONVERSIONS WITH EXTERNAL REFERENCES, which application is hereby incorporated by reference in its entirety.
  • the functionalities described herein can be applied to optimizing webpages for a website.
  • the correlator 104 or other component may be configured to collect web analytics data from the webpages.
  • the web analytics data may be used in estimating the cost, value, or both, associated with one or more search engine optimization (SEO) or social media optimization opportunities. Examples of web analytics data that may be collected include number of visitors, page views, conversions (e.g., purchases), and the like or any combination thereof.
  • SEO search engine optimization
  • the social media optimization module 112 is configured for tracking, identifying, and analyzing social media correspondence as well as orchestrating and performing the webpage analysis of a website as described herein so that recommendations can be made to improve social media interactions and increase the exposure of the entity to thereby improve the SEO of the website.
  • the social media optimization module 112 may access the social media correspondence generated with a user device (e.g., a computer or a mobile phone) in communication with the network 102.
  • a user device e.g., a computer or a mobile phone
  • Figure IB illustrates another embodiment of a social media optimization system 100b.
  • the network 102 operably couples the social media optimization module 112 with a website computing system 128.
  • the social media optimization module 112 includes a computing system 120 configured to perform social media optimization analysis and produce recommendations as described herein.
  • Such recommendations may include, for example, a list of high performing keywords, web pages or landing pages on which the keywords perform well as well as web pages, topics, keywords and/or phrases that are showing up on one or more social media website.
  • the web pages, topics, keywords and/or phrases identified on the social media websites provide invaluable information for advertising and social media campaigns.
  • the computing system 120 may be configured to suggest at least one paid, promoted or sponsored activity within the social media based on the social media optimization analysis.
  • the suggestion may be provided by way of a platform or interactive analytics tool accessible to the customer or entity, for example, through the network 102.
  • the paid, promoted or sponsored activity may be a post, micropost (e.g., a TWEET), or any other item for display on a social media website.
  • the computing system 120 can include submodules for implementing particular functionalities.
  • the computing system 120 can be generic to and include an analytic module 122, determination module 124, and a reporting module
  • the website computing system 128 can include a website database 129 that includes SEO data from entity webpages 132 from an entity website 130.
  • the entity website 130 can be the website of an entity for which social media optimization is to be performed.
  • the website database 129 can further include social media webpages 142 of a social media website 140.
  • the social media website 140 can be any type of social media.
  • social media can include collaborative projects (e.g. WIKIPEDIA), blogs and microblogs (e.g. TWITTER), content communities (e.g. YOUTUBE), social networking sites (e.g. Facebook, virtual game worlds (e.g. WORLD OF WARCRAFT), and virtual social worlds (e.g. SECOND LIFE), among other types of social media and can take many different forms including Internet forums, weblogs, microblogging, social blogs, wikis, podcasts, photographs or pictures, video, rating, social bookmarking, and others.
  • the social media webpages 142 can include any type of digital content that contains social media from the social media website 140.
  • the social media webpage 142 may include a single micropost, a home page of a user with a microblog account with a collection of the user's microposts, or any other digital content that contains microposts.
  • a micropost may include a message or post made public on a website or distributed to a specific group of subscribers, who can observe them over the network 102 via, for example, a computer or a mobile device.
  • Such microposts may be, for example, a status update, a comment, a post (e.g., a website address) or a so-called "check in” at a particular location via social media.
  • Such a micropost on TWITTER social networking service is often referred to as a "TWEET.”
  • Users may copy and repost the tweet of another, which is often referred to as a "re -TWEET.”
  • the micropost may include one or more so-called "hashtags,” in which the "#" symbol is used to mark words or topics in a TWEET.
  • the micropost may also be a reply, such as another TWEET, in response to an original TWEET, which is often denoted with the "@" symbol and a username.
  • TWEETs may be used to drive referral traffic and conversions from TWITTER.
  • this may be challenging for customers because it may require customers to identify high-value opportunities and respond very rapidly with relevant, compelling tweets and content.
  • the social media webpage 142 can be a networking page of a user, a post of a user, a comment, or any other digital content related to the social networking site.
  • the website computing system 128 can contain a second website database so that the entity webpages 132 and the social media webpages 142 reside in separate databases. It should be understood that the data from the entity webpages 132 and the social media webpages 142 may be stored in any configuration without departing from the embodiments described herein.
  • the website computing system 128 can obtain data from the entity webpages 132 and the social media webpages 142 by accessing the entity website 130 and the social media website 140 through a web server, such as the web server 106 of Figure 1A. Furthermore, the data from the entity webpages 132 and the social media webpages 142 can be collected by crawling the webpages 132, 142. In some embodiments, the webpages 132, 142 can be crawled using the deep index engine 108 of Figure 1A, for instance. In some embodiments, the webpages 132, 142 can be crawled using a different mechanism.
  • the data may be obtained from the webpages 132, 142 during a predetermined aggregation period.
  • the predetermined aggregation period may be a time period, such as, one or more hours, days or weeks.
  • the data may be obtained during a single day or a single week.
  • the website computing system 128 may conduct a keyword volume count in which each occurrence of the keyword is counted to determine keyword volume.
  • the keywords may be identified using an exact match or a phrase match. For example, different spellings, misspellings, abbreviations, concatenations and/or URL short code of the keywords may all be searched and evaluated.
  • the keyword volume may include a count or number of an exact and/or phrase match occurrence of the keyword in a social media correspondence, such as a TWEET. The occurrence of the keyword may be classified by according to a type of social media correspondence in which they appear.
  • each occurrence of the keyword may be classified as a reposting of correspondence posted by another (e.g., a retweet), a reply to correspondence (e.g., a TWEET) posted by another or an original correspondence (e.g., a TWEET).
  • the keyword occurrences marked as a specific user-defined topic e.g., by the "#" symbol
  • marked by a username e.g., by the "@” symbol
  • One or more keyword trends may be determined based on the keyword volume.
  • Keyword trend strength may be calculated is calculated from a percent difference between the keyword volume and an average volume for the keyword over a predetermined time period (e.g., the aggregation period).
  • the aggregation period may be one day and they keyword trend strength may include a percent deviation from an average determined over another predetermined time period (e.g., 7 days).
  • the aggregation period may be one week and they keyword trend strength may include a percent deviation from an average determined over another predetermined time period (e.g., 4 weeks).
  • the website computing module 128 may additionally filter data from the entity webpages 132 and the social media webpages 142.
  • the data may be filtered based on any relevant criteria, such as, a number of webpages or a period of time.
  • a sample size may be selected including a predetermined number of webpages and the website computing module 128 may be configured to obtain information from a sample of entity webpages 132 and/or the social media webpages 142 according to the relevant sample size.
  • the data may be filtered to include a particular number or percentage of webpages, or to include one or more websites of interest.
  • the sample may from the entity webpages 132 and the social media webpages 142 may be used to determine a frequency of SEO keyword.
  • the frequency at which the SEO keyword occurs in webpages e.g., the entity webpages 132 and the social media webpages 142
  • the frequency at which the SEO keyword occurs in webpages may be estimated. For example, if the sample size is fifty (50) percent of the webpages, the number of references to the SEO keyword appearing in the webpages obtained from the sample may be doubled to provide an estimate of the actual number of references to the SEO keyword. If the data obtained from the sample indicates a low number of references to the keyword, or no references to the keyword, a larger sample size may be selected or the filter may be removed to ensure accuracy of the estimate.
  • the data may be filtered based on predetermined period of time.
  • a period of time may be selected and the number of references to the SEO keyword that appear on the webpages during the period of time may be determined.
  • the frequency of references to the SEO keyword during the predetermined period of time may be determined.
  • the filtering criteria may be dynamically changed based on the information collected. For example, the group of webpages crawled the period of time, or the SEO keywords may be modified as additional information is gathered an analyzed.
  • filtering data may be used to estimate the frequency of references to the SEO keywords appearing on webpages, to determine the frequency of references to SEO keywords appearing on the webpages in a predetermined period of time, and/or to determine a frequency of references to the SEO keywords appearing on a predetermined group of webpages. Because businesses may be charged a fee per each of the SEO keywords they select, filtering the data is useful in providing such businesses with an estimate of potential costs associated with such services.
  • the computer module 120 may include web pages or content presented to an end user by a content management system (CMS) or other dynamically generated content optimized for an individual user or type of user.
  • CMS content management system
  • the computer module 120 may be configured to provide the end user with access to collected information and to enable the end user to modify, edit and/or publish such information.
  • the analytic module 122 within the computing module 120 can be configured to analyze the webpages 132, 142 to obtain data from the webpage 132, 142.
  • the analytic module 122 can include one or more algorithms for analyzing the webpages 132, 142.
  • the analytic module 122 can analyze on -page data, source code, or any other data of the entity webpages 132 to identify SEO keywords, which may include any branded names of the entity or other words or string of words that are associated with the entity, product names produced by the entity, product categories, relevant search terms, general topics, and other words or strings of words used in SEO.
  • the analytic module 122 can analyze on-page data, source code, or any other data of the social media webpages 142 to identify social media correspondence.
  • Social media correspondence can be any data placed on the social media webpages 142 by a user of the social media website 140 that can be read by other users of the social media website 140.
  • social media correspondence can include posts, comments, or both on a social networking website.
  • social media correspondence can include posts, comments, or both on a blog or microblog. It should be understood that the aforementioned are only some examples of different types of social correspondence and that the scope of social media correspondence as used herein should not be limited in anyway by these examples.
  • the analytic module 122 can further analyze the social media correspondence for one or more words, phrases, or other data using one or more algorithms. For example, in some embodiments, the analytic module 122 can analyze the social media correspondence to identify the SEO keywords identified by the analytic module 122 in the entity webpages 132.
  • the analytic module 122 can analyze the on -page data, source data, or both of the social media webpages 142 and/or the social media website 140 to identify information about specific users of the social media website 140.
  • the identified information can include the social media participation of a user as well as content provided or discussed by the user.
  • the social media participation of the user can include how often the user participates in the social media, such as the number of social media correspondences produced by the user. Additionally or alternately, the social media participation of the user can include how many other users of the social media follow, view, comment on, reference, contribute to, or otherwise acknowledge the social media correspondence produced by the user.
  • the analysis may enable preparation of recommendations to improve visibility by using high-performing keywords (e.g., keywords with a higher than average number of references and/or providing a higher than average return on investment).
  • the recommendations may include, but are not limited to high performing keywords, web pages on which the keyword performs well and topics, web pages, keywords, phrases that are relevant to particular entities because they have an increased presence at a given time.
  • the analysis of keyword trends may be utilized to provide information about valuable keywords trending on social media, and to show how individual webpages rank and convert on the high-performing keywords, to provide alerts on opportunities to drive engagement on social media using existing content, and to prioritize which social media opportunities will be most effective if pursued.
  • the recommendations may further include one or more webpages determined to be relevant for targeting consumers identified as interested in the specific keywords. For example, consumers interested in the selected keywords may be identified and a determination may be made as to which webpages will be the best to use for targeting those consumers based on the selected keywords. Such webpages may be identified based on an analysis of rankings obtained from one or more search engines, an amount or type of traffic, conversions, bounce rate, conversion rate and revenues.
  • the recommendation may include webpages determined to be well-ranked and/or to have a higher than average number of visits or conversions.
  • the recommendations may include one or more webpages (e.g., landing pages) that are performing the best with respect to the keywords ("high performing webpage(s)").
  • the high performing webpages may then be used in one or more advertising or social media campaigns.
  • a report may be provided that includes a link to or URL for the high performing webpage(s) and the report may suggest including the high performing webpage(s) in a social media correspondence, such as a TWEET.
  • the social media correspondence may be provided to the user and may include the link to or URL for the high performing webpage(s).
  • the social media correspondence including the link to or URL for the high performing webpage(s) may provided to the user in a report, an electronic report, in a platform that enables the social media correspondence to be promoted, marketed and delivered, and/or through a portal that automatically connects to a social media service and generates the correspondence.
  • the recommendations improve customer visibility by providing a customer with social media correspondence, such as a TWEET, that includes topics, keywords and/or webpages.
  • Some embodiments further relate to analytics and/or the generation of analytics related to the identification of social media correspondence and SEO keywords.
  • the analytics may be derived from the information received from or collected from the webpages 132, 142, which may be combined or augmented with the SEO data obtained from the website database 129. Such information may also be used for targeted marketing across platforms. The information can also be used to generate revenue. The information may be used to target specific advertisements to specific consumers. In addition, demographics such as demographics of consumers (when provided), types of devices, types of content, and the like may be collected and used to generate analytics.
  • the information may be used to provide a tool for customers to execute or engage in paid advertising campaigns.
  • a social media service may provide paid, sponsored or promoted activity for purchase by an entity.
  • the activity may include, for example, posts or microposts that may be purchased by the entity.
  • TWITTER provides promoted or sponsored TWEETs available for purchase.
  • the information obtained from the analytics described herein may be used to determine paid, sponsored or promoted activity, such as TWEETs, for a particular entity and that activity may be suggested to the entity.
  • the information may also be used to determine a value of the SEO keywords or the webpages 132, 142 and/or to rank the SEO keywords or the webpages 132, 142.
  • information indicating that the SEO keywords are references in social media correspondence more frequently than other SEO keywords is information that may be used by to rank the relevance of the SEO keywords and/or the webpages 132, 142. More frequently referenced SEO keywords may be ranked higher than other less referenced SEO keywords.
  • the webpages 132, 142 referencing a particular SEO keyword of interest more frequently than other webpages may be ranked higher than the other webpages. This information may also be used, for example, to predict or determine price points for social media engagement.
  • the analytics may be used to predict which SEO keywords are more likely to be referenced in social media and/or which webpages are most likely to include the references to the SEO keywords.
  • the analytics may also be used to determine the SEO keywords that provide the highest return on investment (ROI).
  • ROI return on investment
  • return on investment may refer to revenue generated from the SEO keywords or popularity of the keywords in comparison to the costs associated with use of the SEO keywords.
  • one or more webpages having the highest number of references to the SEO keyword may also be determined.
  • the webpages may be sorted in the order of the frequency of keywords associated with the social media.
  • the webpages including the highest number of references to the SEO keyword may be determined and those webpages may be targeted and optimized.
  • the social media optimization system 100b described herein enables tailoring of marketing strategies to optimize SEO keyword usage.
  • the determination module 124 may also be configured to determine one or more webpages that are being shared in social media regardless of the SEO keywords. Information related to such webpages may be analyzed to determine the SEO keywords associated therewith and to optimize social media correspondence.
  • the determination module 124 can obtain data from the analytic module 122 and use the data to determine which identified social media correspondences contain the SEO keywords identified in the entity's webpages 132.
  • the determination module 124 can include one or more algorithms for processing the data obtained from the analytic module 122. Additionally or alternately, the determination module 124 can determine the frequency that the SEO keywords from the entity's website 132 appear in the identified social media correspondences and rank the SEO keywords accordingly. Additionally or alternately, the determination module 124 can determine if there is an increase in use of one or more of the identified SEO keywords over a period.
  • the determination module 124 can determine a rank of the social media participation of a user of the social media website 140 with respect to other users of the social media website 140. For example, for a microblog, such as TWITTER, the number of followers, retweets, and views of a user's TWEET can be used to rank a user as compared to all other users of TWITTER. Additionally or alternately, the determination module 124 can also determine the rank of the social media participation of a user employing other factors, such as by using influence and participation rankings produced by other websites or entities. Additionally or alternately, the determination module 124 can determine which users of the social media website 140 are discussing, providing, viewing, or otherwise associating with social media correspondence that relates to the identified SEO keywords.
  • the reporting module 126 can compile information from the analytic module 122, determination module 124, or both to generate various types of reports and make recommendations to improve social media optimization.
  • the reporting module 126 can include one or more algorithms that can generate one or more reports and provide one or more recommendations for improved social media optimization.
  • the reporting module 126 may include a platform that enables a customer to obtain a promoted or sponsored social media post, such as a promoted or sponsored TWEET on TWITTER, which is selected based on the SEO data as modulated or combined with any of the web analytics data.
  • the platform may suggest the promoted or sponsored social media post and may assist the customer in purchasing the promoted or sponsored social media posts from one or more social media services.
  • the platform may directly linked to the social media service enabling the customer to actively purchase the promoted or sponsored social media post, or may connect with another platform that enables purchase of the promoted or sponsored social media post thereby assisting the customer in the purchase.
  • a particular TWEET may be suggested to the customer through the platform on the reporting module 126 and the customer select and purchase the TWEET by selecting a particular button configured to link the customer to a portal through which the customer may obtain the TWEET.
  • the determination module 124 may access data from one or more mobile devices via a wireless network to gather information and can generate marketing information based on location. For example, location tagging on social media correspondence or login/check-in information provided in social media correspondence may be analyzed to determine references to keywords based on location.
  • the determination module 124 may analyze trends associated with the SEO keywords, such as growth in social media correspondence and demographics (e.g., gender, race, age, interests, education, employment status, and location), consumption and creation of content.
  • the information obtained from such analysis may be provided, for example, in a report, an electronic report and/or an electronic notification, and may be used to tailor marketing strategies.
  • the electronic report may be, for example, displayed on the screen of a computer, downloaded into one or more electronic file formats or printed onto paper.
  • Such reports generated based on the collected information may include, for example, activity reports, stimulus reports, dynamic maps, etc.
  • the reports may include information related to the webpages, the SEO keywords, the social media, or users of the social media.
  • a report may include a dynamic map of activity associated with the SEO keywords or with webpages including at least one reference to the SEO keyword.
  • such a report may include an analysis of the webpages according to the references to the SEO keyword (e.g., webpages with the highest number of occurrences).
  • such a report may include demographic information about the users associated with the references to the SEO keyword.
  • the report may include at least one promoted or sponsored social media post that is determined based on the SEO data and web analytic data.
  • the report may provide information for accessing the promoted or sponsored social media post or, if the report is in an electronic form, may include a link or button for purchasing the promoted or sponsored social media post. Accordingly, the social media optimization system 100b generates data useful for developing paid advertising campaigns.
  • an all keywords report may be generated that enables users to quickly observe what keywords and webpages may most effectively drive revenue.
  • Such keywords may be those with the highest number of references in social media or may be those with the greatest increase in references within a predetermined time period.
  • the all keywords report may additionally provide information about which keywords within a group of multiple keyword groups (e.g. multiple product categories) are increasing in social media correspondence.
  • Such webpages may be those that include the highest number of references to one or more selected keywords or may be those in which the frequency of references to the selected keywords is increasing most rapidly.
  • the report may provide information related to the keywords and webpages to include in social media correspondences, such as a TWEET made by a user of TWITTER, to drive revenue.
  • the report may provide information about the strongest trending keywords and the high-value pages and opportunities related to those keywords.
  • the all keywords report may include, for example, a stack bar-chart showing total keyword volume by keyword trend strength.
  • the reports may be customized according to customer specifications.
  • the reports may be customized to include keywords with 0 percent or less deviation from average, keywords trending above 0 percent but less that 50 percent above average, keywords trending above 50 percent but less that 100 percent from average, and/or keywords trending 100 percent or more above average.
  • the reports may include data from any number of aggregation periods.
  • the report may be an electronic report including web-based graphical user interfaces, or screens, in which the data may be viewed.
  • the electronic report may include one or more buttons that links to a map of each trend strength category.
  • the keyword data may be filtered. For example, wherein the data may be filtered or sorted to show only the keywords that fall in the specific trend category described by the button.
  • the reports may include any number of fields, each of which may be related to the keyword or to the social media.
  • the fields may include the keywords having the highest volume (e.g., keyword rank), the webpages having the highest number of references to the keyword (e.g., top ranked webpages), organic search revenue for the keyword during a predetermined time period, and/or a percent change in the keyword volume.
  • a trending report may be generated that includes the top ranked webpage for each keyword and one or more other webpages including the keyword.
  • the reports may include a function that enables display of information for a particular date and/or time. For example, a particular date in the past may be selected and data from that date may correspond to that date.
  • the report may also include an option to export the data in to another format, such as, a text file, a comma-separated values (CSV) file, or any other type of file.
  • the exported data may include all or a portion of the data shown in the electronic report.
  • the exported data may additional include, for example, a number of visits, a number of webpage views, conversations and/or orders within a predetermined time period.
  • the reports may also be configured into one or more at-a-glance views or so-called "dashboards.”
  • the keyword link between social media correspondence and webpages may be used to generate specific recommendations to leverage those webpages and drive engagement and revenue on the social media. Such recommendations will be tied to the keyword and the webpage.
  • Figure 2 illustrates an embodiment of a method 200 for increasing social media engagement.
  • the method 200 can be implemented in the social media optimization system 100a or 100b of Figure 1A or IB, for instance.
  • the method 200 may include identifying one or more SEO keywords from a webpage of an entity at block 210.
  • identifying one or more SEO keywords from the webpage of the entity can include crawling the website of the entity, obtaining SEO data from the website, and identifying the SEO keywords.
  • the SEO keywords can include any branded names of the entity or other words or string of words that are associated with the entity, product names produced by the entity, product categories, relevant search terms, general topics, and other words or strings of words used in SEO.
  • the method 200 can further include identifying social media correspondence from social media webpages that reference the SEO keywords at block 220.
  • identifying social media correspondence from the social media webpage can include crawling the social media webpage, obtaining SEO data from the webpage, and analyzing social correspondence located on the social media webpage for references to the previously identified SEO keywords.
  • the SEO keywords referenced more often in the social media correspondences may by noted. Additionally or alternately, the frequency that SEO keywords are referenced in social media correspondence may be determined and tracked to create a moving average of the number of references. If the number of social media correspondences that reference a particular SEO keyword is above or below the moving average of number of references for that SEO keyword or string of keywords, the SEO keyword or string of keywords may be noted.
  • the method 200 may further include identifying social media participants with higher than average social media participation.
  • Social media participants with higher than average social media participation may be considered influential participates. These social media participants may be identified based on one or more factors. Factors may include the number of social media participant followers, the number of social media correspondences produced, and other factors.
  • the method 200 may further include identifying specific social media participants that have provided input to the social media with respect to the social media correspondence referencing the SEO keywords.
  • the method 200 can further include recommending material, related to webpages that contain the SEO keywords referenced in social media correspondence, for engagement in the social media at block 230.
  • Engagement in the social media can include contributing to the social media by producing social media correspondence, distributing social media correspondence, or some other contribution.
  • the material related to all SEO keywords referenced in the social media correspondence can be used to engage in the social media. Additionally or alternately, only material related to SEO keywords that are above the moving average for the number of social media correspondences that reference the SEO keywords can be used to engage in the social media. Additionally or alternately, only material related to SEO keywords that are below the moving average for the number of social media correspondences that reference the SEO keywords are used to engage in the social media.
  • the material related to the SEO keywords is the material from a webpage from which the SEO keywords are derived.
  • the occurrence of the SEO keywords determined to rank the highest for a particular entity may be monitored on the social media, such as TWITTER or FACEBOOK. As changes in the occurrence of the SEO keywords on the social media are identified, information related to the changes may be reported. For example, if the occurrence of the SEO keyword increases, a reporting may be generated illustrating increases in the occurrence of the keywords over time. Other relevant information may be monitored, such as groups of users or demographic information associated with social media users associated with the occurrence of the SEO keywords on the social media.
  • the users associated with the occurrence of the SEO keywords within the social media may include, for example, those posting the keywords (or variations thereof), information related to the keywords and/or those responding to or reposting correspondence including the SEO keywords.
  • the recommendations may provide at least one of instructions for creating social media correspondence, text for posting the social media correspondence, keywords or phrases to insert into a social media correspondence or a link to post pre -written social media correspondence including at least one of a web page or the keywords or phrases.
  • the recommendations may be in the form of an electronic report and may provide information such as keywords, phrases or a web page for posting in a TWEET or may include a link to a social media website or a portal that interacts with the social media website to generate a TWEET that includes the information.
  • such recommendations may be based on web pages that perform well with respect to the keywords. For example, matching keywords to trending phrases on webpages provides data for improving visibility in the marketplace. Specific web pages may be targeted by determining which web pages performing best with respect to the keywords. By analyzing target web pages and trending topics or keywords within social media, a web page or landing page may be identified that will have particular importance in advertising and social media campaigns.
  • the recommendations may include information about how to compose social media correspondence based on the identified web page or landing page, thus, providing specific actions for advertising and social media campaigns.
  • the recommendations may include a list of items or services that may be purchased from an advertising or marketing agency, such as a phrase, keywords, etc. The information in the recommendations may, thus, be used to promote the entity in the campaign.
  • the recommendations may include a list or a screen provided or displayed that provides a platform or a portal for purchasing a promoted social media correspondence.
  • the platform or portal may be configured to accept input from the customer, such as a request for a type of social media correspondence and an desired amount to be spent on the paid campaign, and the paid campaign may be generated and executed.
  • the customer may be provided with a link to a social media service or an advertising/marketing company through the portal which enables them to create, request and/or implement the paid campaign.
  • the method 200 can include recommending that social media participants that have provided social media correspondence referencing the SEO keywords be engaged with material related to the SEO keywords.
  • Social media participants can be engaged by sending the social media participants new social media correspondence, replying to social media correspondence produced by the social media participants, or otherwise engaging with the social media participants through the social media.
  • the method 200 can include recommending that social media participants with higher than average social media participation be engaged with material related to the SEO keywords that the social media participants have previously included in their social media correspondence.
  • the method 200 can include recommending the suggestion of new or additional content for a webpage of a user related to SEO keywords that have been identified in social media correspondence.
  • the method may further include providing an entity with data concerning the number of SEO keywords referenced in the social media correspondence over a period.
  • the data can come in the form of a report with one or more images, charts, graphs, or other display. Additionally or alternately, the entity can be provided with data concerning the social media correspondences that reference a certain SEO keyword, any SEO keywords, or a combination of SEO keywords over a period.
  • An example of the method 200 is as follows.
  • An entity such as a shoe store may have a website with webpages that display and offer shoes for sale.
  • the webpage may be crawled and SEO keywords, such as the brand of the shoes and other words such as, shoe, performance, running, and others may be identified.
  • the webpages of the social media may also be crawled.
  • all of the webpages of the website TWITTER may be crawled, and social media correspondence, such as, a TWEET, may be identified and analyzed to identify SEO keywords within the social media correspondence.
  • a recommendation may be made to the shoe store to engage in the social media by generating and posting TWEETS including information about the shoes, such as a sale, benefits of the shoes, or other material, based on the SEO keywords that were identified in the social media correspondence.
  • the data collected from the social media correspondence may be correlated with the SEO keywords data to determine topics or web pages of relevance for a social media or marketing campaign, such topics or web pages having a high ROI or trending in social media.
  • the recommendation may include the topics or web pages which may be included in social media correspondence to improve visibility.
  • a report may be generated that includes a recommendation for at least one type of social media correspondence with a link to the web page(s) determined to be of relevance.
  • the recommendation may include a link to a platform that provides text or the actual social media correspondence including the link to the web page(s) and/or a portal that provides access to social media website(s) from which the social media correspondence including the link to the web page(s) may be directly obtained.
  • the recommended social media correspondence may be a TWEET that includes the link to the web page(s) and the customer may be provided with a platform that enables them to link to the TWITTER website to post the TWEET or a portal that enables them to automatically obtain or purchase the TWEET.
  • the customer may, thus, use the recommendation to implement a social media or marketing campaign.
  • the method 200 improves visibility, better targeting and actionability within social media.
  • the data may also be used to create, formulate, reshape, edit and/or optimize content on website to reflect trends in social media.
  • the trending keywords and web pages reflected in the data may be used not only as a tag in social media correspondence, but also as a signal to display on a web site.
  • the topic or keyword may be identified. This facilitates alteration of content on a website to improve performance and rankings.
  • a report may be generated that describes content for addition to a website.
  • content may be created and provided to a customer based on the data, or the customer may be provided with access to a CMS system to create the recommended content, for example, by clicking a button in the report.
  • the data may be useful in performing a gap analysis comparing competitors. For example, keywords that a customer ranks well on may be correlated with and compared with keywords and web pages that one or more competitors rank well on to determine performance relative to the competitor. Such information may be assessed and recommendations may be provided based on the correlation, the recommendations enabling improvement of ranking with respect to the competitors. Correlating the keywords and web pages may include assessing whether a customer is more aligned with what is trending in social media than the competitors. After filtering and comparing competitors keywords and web pages to determine how the competitors are performing, a report may be generated showing what percentage of the trending keywords and web pages are being utilized by the customer and the competitors. This may enable alteration of content on the customer website to reflect trending keywords and to improve performance in comparison to the competitors. The report may provide recommendations for altering content on the website, or may link the customer to a platform (such as the CMS) that enables the customer to alter content on the website to improve performance.
  • a platform such as the CMS
  • Some embodiments disclosed herein include a computer program product having computer-executable instructions for causing a computing system having the computer program product to perform a computing method of the computer-executable instructions for improving SEO of social media webpages of an entity.
  • the computing method can be any method described herein as performed by a computing system.
  • the computer program product can be located on a computer memory device, which may be removable or integrated with the computing system.
  • Some embodiments include a computing system capable of performing the methods described herein. As such, the computing system can include a memory device that has the computer-executable instructions for performing the method.
  • a computing device such as a computer or memory device of a computer, can include an analytic module, determination module, and reporting module.
  • the analytic module, determination module, and reporting module can be configured to perform any of the methods described herein. Also, the analytic module, determination module, and reporting module can be combined into a single module or on a single platform.
  • the computer program product can include one or more algorithms for performing any of the methods of any of the claims.
  • the computer program product can include one or more algorithms for performing any of the methods of any of the claims.
  • any of the operations, processes, etc. described herein can be implemented as computer-readable instructions stored on a computer- readable medium.
  • the computer-readable instructions can be executed by a processor of a mobile unit, a network element, and/or any other computing device.
  • the implementer may opt for a mainly hardware and/or firmware vehicle; if flexibility is paramount, the implementer may opt for a mainly software implementation; or, yet again alternatively, the implementer may opt for some combination of hardware, software, and/or firmware.
  • a signal bearing medium examples include, but are not limited to, the following: a recordable type medium such as a floppy disk, a hard disk drive, a CD, a DVD, a digital tape, a computer memory, etc.; and a transmission type medium such as a digital and/or an analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).
  • a typical data processing system generally includes one or more of a system unit housing, a video display device, a memory such as volatile and non-volatile memory, processors such as microprocessors and digital signal processors, computational entities such as operating systems, drivers, graphical user interfaces, and applications programs, one or more interaction devices, such as a touch pad 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 quantities).
  • a typical data processing system may be implemented utilizing any suitable commercially available components, such as those generally found in data computing/communication and/or network computing/communication systems.
  • any two components so associated can also be viewed as being “operably connected”, or “operably coupled”, to each other to achieve the desired functionality, and any two components capable of being so associated can also be viewed as being “operably couplable”, to each other to achieve the desired functionality.
  • operably couplable include but are not limited to physically mateable and/or physically interacting components and/or wirelessly interactable and/or wirelessly interacting components and/or logically interacting and/or logically interactable components.
  • FIG. 3 shows an example computing device 300 that is arranged to perform any of the computing methods described herein.
  • computing device 300 generally includes one or more processors 304 and a system memory 306.
  • a memory bus 308 may be used for communicating between processor 304 and system memory 306.
  • processor 304 may be of any type including but not limited to a microprocessor ( ⁇ ), a microcontroller ( ⁇ ), a digital signal processor (DSP), or any combination thereof.
  • Processor 304 may include one more levels of caching, such as a level one cache 310 and a level two cache 312, a processor core 314, and registers 316.
  • An example processor core 314 may include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP Core), or any combination thereof.
  • An example memory controller 318 may also be used with processor 304, or in some implementations memory controller 318 may be an internal part of processor 304.
  • system memory 306 may be of any type including but not limited to volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.) or any combination thereof.
  • System memory 306 may include an operating system 320, one or more applications 322, and program data 324.
  • Application 322 may include a determination application 326 that is arranged to perform the functions as described herein including those described with respect to methods described herein.
  • the determination application 326 may correspond to the determination module 124 of Figure IB, for example.
  • Program Data 324 may include determination information 328 that may be useful for analyzing social media correspondences located on the social media webpage.
  • application 322 may be arranged to operate with program data 324 on operating system 320.
  • Computing device 300 may have additional features or functionality, and additional interfaces to facilitate communications between basic configuration 302 and any required devices and interfaces.
  • a bus/interface controller 330 may be used to facilitate communications between basic configuration 302 and one or more data storage devices 332 via a storage interface bus 334.
  • Data storage devices 332 may be removable storage devices 336, non-removable storage devices 338, or a combination thereof. Examples of removable storage and non-removable storage devices include magnetic disk devices such as flexible disk drives and hard-disk drives (HDD), optical disk drives such as compact disk (CD) drives or digital versatile disk (DVD) drives, solid state drives (SSD), and tape drives to name a few.
  • Example computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data.
  • Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to store the desired information and which may be accessed by computing device 300. Any such computer storage media may be part of computing device 300.
  • Computing device 300 may also include an interface bus 340 for facilitating communication from various interface devices (e.g., output devices 342, peripheral interfaces 344, and communication devices 346) to basic configuration 302 via bus/interface controller 330.
  • Example output devices 342 include a graphics processing unit 348 and an audio processing unit 350, which may be configured to communicate to various external devices such as a display or speakers via one or more A/V ports 352.
  • Example peripheral interfaces 344 include a serial interface controller 354 or a parallel interface controller 356, which may be configured to communicate with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device, etc.) or other peripheral devices (e.g., printer, scanner, etc.) via one or more I/O ports 358.
  • An example communication device 346 includes a network controller 360, which may be arranged to facilitate communications with one or more other computing devices 362 over a network communication link via one or more communication ports 364.
  • the network communication link may be one example of a communication media.
  • Communication media may generally be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and may include any information delivery media.
  • a "modulated data signal" may be a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal.
  • communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), microwave, infrared (IR) and other wireless media.
  • RF radio frequency
  • IR infrared
  • the term computer readable media as used herein may include both storage media and communication media.
  • Computing device 300 may be implemented as a portion of a small-form factor portable (or mobile) electronic device such as a cell phone, a personal data assistant (PDA), a personal media player device, a wireless web-watch device, a personal headset device, an application specific device, or a hybrid device that include any of the above functions.
  • Computing device 300 may also be implemented as a personal computer including both laptop computer and non-laptop computer configurations.
  • the computing device 300 can also be any type of network computing device.
  • the computing device 300 can also be an automated system as described herein.
  • the embodiments described herein may include 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 for carrying or having computer-executable instructions or data structures stored thereon.
  • Such computer-readable media can be any available media that can be accessed by a general purpose or special purpose computer.
  • Such computer-readable media can 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.
  • Computer-executable instructions comprise, for example, instructions and data that cause a general-purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions.
  • module can refer to software objects or routines that execute on the computing system.
  • the different components, modules, engines, and services described herein may be implemented as objects or processes that execute 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 a combination of software and hardware are also possible and contemplated.
  • a "computing entity” may be any computing system as previously defined herein, or any module or combination of modulates running on a computing system.
  • a range includes each individual member.
  • a group having 1-3 cells refers to groups having 1, 2, or 3 cells.
  • a group having 1-5 cells refers to groups having 1, 2, 3, 4, or 5 cells, and so forth.

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Abstract

L'invention porte sur des procédés pour optimiser un média social. Ces procédés peuvent consister à identifier au moins un mot-clé utilisé pour au moins une page Web, à identifier une correspondance de média social référençant le ou les mots-clés, à analyser du contenu rassemblé auprès du média social afin de déterminer une fréquence de références au ou aux mots-clés et à générer au moins un rapport comprenant des informations fondées sur l'analyse. Le rapport peut comprendre des recommandations d'optimisation de média social, par exemple par achat d'articles ou de liens payants sur un site Web de média social. Des systèmes pour mettre en œuvre les procédés sont également décrits.
PCT/US2013/042117 2012-05-21 2013-05-21 Optimisation d'engagement sur les médias sociaux WO2013177230A1 (fr)

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