• Share
  • Email
  • Embed
  • Like
  • Save
  • Private Content
The Effect of Microdata on Search Engine Optimization
 

The Effect of Microdata on Search Engine Optimization

on

  • 791 views

Microdata is a new development that is likely to have a significant impact on the search engine optimization (SEO) industry. The objective of this study was to determine the effect of microdata on ...

Microdata is a new development that is likely to have a significant impact on the search engine optimization (SEO) industry. The objective of this study was to determine the effect of microdata on search engine optimization. The attitudes and experiences of search engine optimization professionals were explored to determine if, and how, microdata fits into their overall search engine optimization strategy both now and in the future. The study also explored the level of effort required and the payoff that was expected as a result of incorporating microdata into web pages. The results of the study will provide search engine optimization professionals with a better understanding of the importance of microdata to other industry professionals and will help them determine the possible importance of microdata to their own overall search engine optimization strategy.

Statistics

Views

Total Views
791
Views on SlideShare
734
Embed Views
57

Actions

Likes
0
Downloads
11
Comments
0

1 Embed 57

http://www.bengriffiths.me 57

Accessibility

Categories

Upload Details

Uploaded via as Microsoft Word

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

    The Effect of Microdata on Search Engine Optimization The Effect of Microdata on Search Engine Optimization Document Transcript

    • Running head: THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATIONTHE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATIONA ThesisPresented byBen GriffithsSubmitted to the Graduate College of Stevens-Henager College in partial fulfillment of therequirements for the degree ofMASTER OF BUSINESS ADMINISTRATIONJune 2012Committee:Darren Adamson, Ph.D.Cheryl McDowell, Ph.D.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 1© 2012Ben GriffithsAll Rights Reserved
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 2AbstractMicrodata is a new development that is likely to have a significant impact on the search engineoptimization (SEO) industry. The objective of this study was to determine the effect ofmicrodata on search engine optimization. The attitudes and experiences of search engineoptimization professionals were explored to determine if, and how, microdata fits into theiroverall search engine optimization strategy both now and in the future. The study also exploredthe level of effort required and the payoff that was expected as a result of incorporatingmicrodata into web pages. The results of the study will provide search engine optimizationprofessionals with a better understanding of the importance of microdata to other industryprofessionals and will help them determine the possible importance of microdata to their ownoverall search engine optimization strategy.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 3TABLE OF CONTENTS1. INTRODUCTION …………………………………………………………………… 5Background ……………………………………………………………………. 5Statement of the Problem ……………………………………………………… 6Purpose Statement ……………………………………………………………... 7Objectives of the Study ………………………………………………………... 7Hypothesis ……………………………………………………………………... 7Assumptions …………………………………………………………………… 8Limitations ……………………………………………………………………... 8Definition of Terms ……………………………………………………………. 92. LITERATURE REVIEW ……………………………………………………………. 11Introduction ……………………………………………………………………. 11Review …………………………………………………………………………. 11Conclusion ……………………………………………………………………... 203. METHODOLOGY …………………………………………………………………... 21Introduction ……………………………………………………………………. 21Participants ……………………………………………………………………... 21Materials ……………………………………………………………………….. 22Design ………………………………………………………………………….. 23Procedure ………………………………………………………………………. 254. RESULTS ……………………………………………………………………………. 26Introduction ……………………………………………………………………. 26Findings of the Study …………………………………………………………... 27
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 4Summary ……………………………………………………………………….. 415. CONCLUSION AND RECOMMENDATIONS ……………………………………. 42Introduction ……………………………………………………………………. 42Conclusion ……………………………………………………………………... 43Recommendations ……………………………………………………………… 44Considerations for Future Research ……………………………………………. 44Summary ……………………………………………………………………….. 456. REFERENCES ………………………………………………………………………. 46
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 5Chapter IIntroductionBackgroundSearch engines have transformed the way we gather information about the world aroundus. Research that used to take months or years to complete can now be conducted in hours orminutes. With a few keystrokes we can access literally billions of pages of information aboutnearly any topic in a fraction of a second through several web-based search engines.While many smaller search engines serve niche groups of users, the three major searchengines that serve the greatest user base today are Google, Bing, and Yahoo!. Google, arguablythe most influential search engine, was founded in 1998 by Larry Page and Sergey Brin, twostudents at Stanford University. Various search engines have come and gone over the years, buttheir goal has largely remained unchanged: gather information from web pages from across theInternet and help users find the ones that are most relevant to what they are searching for.―Google’s mission is to organize the world’s information and make it universally accessible anduseful,‖ (Google, 2012).Search engines are powered by ―robots‖ or ―spiders‖ that crawl the web accessing webpages and indexing the content that they find. The web pages are then ranked so searchers maybe presented with the most relevant information at the top of the results. Properly ranking thesearch results keeps users happy, ensuring that they return to their search engine of choice fortheir next search—and that keeps search engines happy as they retain users, and continue to gainnew ones.Low quality or irrelevant search results frustrate users, driving them to competing searchengines. To increase the relevance of search results, search engines constantly update their
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 6ranking algorithms—complex mathematical equations used to measure the relevance of a webpage to a specific search query and rank them against each other.Business owners and marketers have recognized the change that the Internet has made tothe way consumers and businesses communicate and interact with each other. Consumers haveturned to the Internet, particularly through search engines, to gather information about companiesand products before making purchases, and even complete many of their purchases directly fromcompany websites. ―Getting found‖ on search engines has become an important and lucrativebusiness objective and has led to an entirely new industry called Search Engine Optimization(SEO).The goal of search engine optimization is to get a company’s or individual’s web pages tooutrank competitors’ for search terms that consumers are using to find relevant products,services, or information. This is done by analyzing the behavior of search engines to determinefactors included in search engines’ ranking algorithms, and optimizing web pages to satisfy theseranking factors.Statement of the ProblemOver the years the major search engines, such as Google, Yahoo!, and Bing haveincorporated different types of information into search results. Instead of showing just a title,brief description, and a hyperlink to searchers, they are now showing photos, videos, productinformation, pricing, addresses, phone numbers, customer reviews, and more in their searchresult pages. This information, known as structured data, provides useful information tosearchers and helps them find what they are looking for more quickly and efficiently.While search engines may be able to identify, interpret, and gather some of thisinformation on their own, various schemas have been created to help communicate this type of
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 7information to the search engines directly. Recently, Google, Yahoo!, and Bing have joinedtogether in an effort to promote a single schema for webmasters to use to communicatestructured data to the search engines—eliminating the need for multiple schemas to satisfymultiple search engines. This single schema is called microdata.Purpose StatementMicrodata represents a considerable change to the way search results are displayed andhow website owners and webmasters can communicate relevant information to search engines.Microdata is now universally supported by the three major search engines: Google, Bing, andYahoo!. The purpose of this thesis is to examine the effect of microdata on search engineoptimization.Objectives of the StudyMicrodata is a new development that is likely to have a significant impact on the searchengine optimization industry. While the implementation of microdata into web pages isrelatively easy, the full effect has yet to be determined. The objective of the study is todetermine the effect of microdata on search engine optimization. The results of the study willprovide search engine optimization professionals with a better understanding of the importanceof microdata to industry professionals. It will also help them determine the possible importanceof microdata to their overall search engine optimization strategy.HypothesisEarly indications are that for a small investment of time, search engine optimizers maysee a large impact in how users interact with search results. While microdata is not expected tobe a direct ranking factor, it will likely be an indirect ranking factor because of changes in theway users interact with search results. Particularly, search result click-through-rates are expected
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 8to increase, sending a signal to search engines that the associated pages are relevant to searchqueries. Having a single schema that applies to all three of the major search engines also makesthe job of a search engine optimizer that much easier.AssumptionsThe following assumptions have been made in relation to this study:1. Search Engine Optimization is possible—that is, webmasters can take actionsthat will directly influence search engine results.2. Search engine optimization professionals have a desire to optimize their webpages to the fullest extent possible.3. Google, Bing, and Yahoo! have accurately represented the nature of microdatain public communications, such as blog posts and announcements on companyweb pages.4. Relevant search results mutually benefit users, search engines, andwebmasters.5. Search engine optimization professionals know what microdata is, and havehad at least limited experience with it.LimitationsDue to limited time and resources this study will not attempt to demonstrate a statisticallysignificant change in rankings, click-through-rates, or web page performance as a result ofincorporating microdata into web pages. Rather, this study will be exploratory in natureandmeasure the attitudes and experiences of search engine optimization professionals as they relateto microdata and its effect on search engine optimization.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 9Definition of TermsThe following definitions will aid the reader in sharing the same meaning as the author:Search Engine: A web-based service for retrieving web pages, documents, andother information from the Internet.Search Engine Optimization (SEO): The practice of optimizing web pages toappear at the top of search results for relevant search queries with the intent ofgenerating traffic to web pages that ultimately results in revenue for an individualor business.Keywords: Words or phrases entered into a search engine by users whensearching for information on the Internet.Search Engine Result Placements (SERPs): The results that are presented by asearch engine following a search.Rankings: The sort order of search engine result placements (SERPs).Ranking algorithms: Complex mathematical equations used to measure therelevance of web pages to specific search queries.Click-through-rate: The rate at which users click on a particular search engineresult placements (SERPs).Structured data: Data such as photos, videos, product information, pricing,addresses, phone numbers, customer reviews, etc. that is easilydistinguishable by humans, but not by machines.Schema: The representation of a plan or theory in the form of a model.Markup: A set of symbols used to annotate a web page that is syntacticallydistinguishable from text.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 10Microdata: A simple schema for embedding semantic markup into HTMLdocuments.Eye-tracking: A system of hardware and software used to measure and track themovement of a subject’s eyes for analysis of user behavior.Analytics: Analytical tools and software used to track and measure user actionson web pages for analysis by an analyst with the intention of determining userbehavior and intent.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 11Chapter IILiterature ReviewIntroductionMicrodata is a relatively new development within the Search Engine Optimization (SEO)industry and thus, few studies have been conducted specific to microdata. Structured markupand rich snippets have been around for years however, which has served as the genesis formicrodata. A brief history of the most popular rich snippet formats will be reviewed which ledup to microdata. The need for microdata will then be explored, along with a thoroughdescription of what it is and how it works.ReviewThe Goal of SchemasHumans and machines interpret data differently. Humans are able to distinguish betweendifferent types of data and draw conclusions about them automatically. Machines, on the otherhand, have a difficult time distinguishing between different types of data. For example, a humancan read a testimonial from another user and understand that it represents a third-party opinionabout a product or service. The tone and word-choice of the review sends signals to humans thatone review is positive, while another is negative. The human reader then draws a conclusionabout the product or service based on the review that has been read and interpreted—which canimpact purchasing behavior.For a machine, however, that same review is difficult to interpret as anything other thanmore text on a web page. It is difficult for the machine to recognize that the text is a review,measure the tone of the message, or draw conclusions based on that interpretation. As an affect,no action may be taken by the machine as a result of that testimonial.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 12Schemas attempt to allow a webmaster to mark up the text on the web page in a way thatcommunicates to a search engine that a certain piece of text represents a particular type of data,which it can then interpret and act on. A particular piece of text, for example, may be marked upby a webmaster to indicate that it is a testimonial, that it pertains to a particular product, and thatit was rated 4 out of 5 stars by the user. The search engine may then recognize the favorablereview, its associated product, and not only display this information in the SERPs, but even rankthe highly-rated product page higher than the lower-rated product page.This benefits the search engine because it can more easily recognize, interpret, and actupon certain types of data. And, it benefits the human user because he or she can more easilylocate a product that has been highly-rated and view testimonials that will validate the product inhis or her mind.Popular SchemasThe three most popular schemas are RDFa, microformats, and microdata. Each schemaallows webmasters to mark up structured data in a way that it is understood by both humans andmachines.Adida and Birbeck (2008) have provided an overview of RDFa and described how to turnexisting ―human-visible‖ text and links into ―machine-readable‖ data without repeating content.RDFa ―provides a set of XHTML attributes to augment visual data with machine-readable hints‖.RDFa is highly extensible and easy for machines to understand, but can be difficult to implementfor humans.Microformats.org (2012) outlines the proper use of microformats, giving a description ofwhat they are and what they are not. Microformats attempt to adapt to current behaviors and
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 13usage patterns and are highly correlated with semantic XHTML. Microformats are humanfriendly because of their simplicity, but are not as extensible as RDFa, making them lessimpactful for machines.Hickson (2012)has outlined the specification that defines the HTML microdatamechanism. Microdata allow webmasters to embed ―machine-readable data‖ into HTMLdocuments in a simple format that may be parsed by machines. A balance of extensibility andsimplicity is reached by the microdata format, making it favorable to both machines as well ashumans.Google (2011)has described the purpose of microdata and provided guidance on the useof non-visible content. That is, Google generally will not display content that is not visible tousers on a web page. Google encourages webmasters to display the same information to searchengines as is shown to visitors, but mark up the data using microdata so that it can be interpretedcorrectly (see Figure 2.1 and Figure 2.2).Figure 2.1. HTML without microdata markup.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 14Figure 2.2. HTML with microdata markup.In 2010, Chattopadhyay et al. officiallyannounced that Google had incorporated supportfor microdata for rich snippets. According to Chattopadhyay, ―Microdata has the nice propertyof balancing richness with simplicity‖ (para. 5). Google recognizes all three schemas, butrecommends the use of microdata.Rich SnippetsAccording to Google (2012), if the search engine can understand the content on a webpage, it can include detailed snippets of information in its search results to help users withspecific queries. These detailed snippets of information are called rich snippets (see Figure 2.3).Rich snippets are shown in search results to ―give users a sense for what’s on the page and whyit’s relevant to their query‖ (Google, 2012, para. 1).―For example, the snippet for a restaurant might show the average review and pricerange; the snippet for a recipe page might show the total preparation time, a photo, and
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 15the recipe’s review rating; and the snippet for a music album could list songs along with alink to play each song‖ (Google, 2012, para. 2).Figure 2.3. Examples of Rich Snippets.Google supports rich snippets for these content types:ReviewsPeopleProductsBusinesses and organizationsRecipesEventsMusicVideo content
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 16Structured markup also helps Google present relevant information in its local searchresults. When this structured markup is included in web pages, it allows webmasters tocommunicate specific types of information, such as a business name, address, or a phone numberto Google, which is in turn presented to searchers in local results (Google, 2011).The Case for MicrodataWith three different schemas fighting for adoption, each of the search engines had todecide which of the schemas to support, and webmasters were left needing to satisfy multiplesearch engines by incorporating multiple schemas. The alternative was to choose only oneschema to support and only satisfy some of the search engines.In 2012, Google announced the launch of Schema.org, which is an effort co-supported byGoogle, Bing, and Yahoo!. Schema.org (2011) provides a collection of shared vocabularieswebmasters can use to mark up their pages in ways that can be understood by the major searchengines: Google, Microsoft, and Yahoo! The vocabularies found at Schema.org may be encodedusing the microdata format to add information to the HTML content of a web page.Google chose to support Microdata as ―a single format [to] improve consistency acrosssearch engines‖, and states that ―microdata strikes a balance between the extensibility of RDFaand the simplicity of microformats,‖ (Google, 2012, n.p.). Google also states that this data is notcurrently used as a ranking factor, but that it ―can make your web pages appear moreprominently in search results, so you may see an increase in traffic,‖ (Google, 2012, n.p.).Google’sprovides an online testing tool that allows webmasters to check that Google cancorrectly parse the structured data markup on their web pages and display it in search results(2010). The tool is available at http://www.google.com/webmasters/tools/richsnippets.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 17The Effect of Microdata on SEOIn a study by González-Caro and Marcos (2010) researchers examined user behavior todetermine whether the intention behind search queries affects the way people browse the resultspage. Eye tracking techniques were used to record eye fixations in title, snippet, URL andimages. Generally, the results demonstrated that a relationship exists between the users’intention and their behavior when they browse the results page. In other words, the type ofinformation that searchers were looking for dictated the way they viewed and interpreted searchresults.Search engines pay special attention to the way searchers interact with search results. Inan interview with Enge (2011), Duane Forrester, a Sr. Product manager with Bing’s WebmasterProgram, described various ranking factors that Bing looks at, including the interaction ofsearchers with search results. ―We are watching the user’s behavior to understand which resultwe showed them seemed to be the most relevant in their opinion, and their opinion is voiced bytheir actions‖ (n.p.).Enge (2011)shared his experiences and opinions in relation to the impact of microdata onclick-through rates for search engine results. Enge said, ―The presence of the stars in the searchlistings will tend to draw the human eye and increase the click-through rate for those results‖(n.p.).Meyers (2011)confirmed the behavior that Enge described above with the results of aneye-tracking study that demonstrates the effect of rich snippets in local search results. Meyers’summary of the results of the eye-tracking study describes how searchers’ eyes tend to fixate on
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 18rich snippet data in search results, such as user reviews, addresses, photos, and videos even whenthese results rank lower than non-rich snippet results (see Figure 2.4).While the ranking of web pages in search results is not directly impacted by rich snippets,the number of users clicking on the links tends to increase because their eyes are drawn to theresults.Figure 2.4. Rich Snippets Eye-Tracking Study.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 19The inclusion of reviews in rich snippets is of particular interest given the results of astudy by Luca (2010) where he demonstrated that a one-star increase in Yelp rating lead to a 9%increase in revenue for independent restaurants. Luca described how ―online consumer reviewssubstitute for more traditional forms of reputation,‖ (p. 1).Microdata represents an opportunity for webmasters to communicate reviews to searchengines and have those reviews displayed in SERPs, increasing click-through rates andpotentially increasing revenues. The rich snippets can include star ratings; number of votes,price range, the date of the last review, the number of critic reviews vs. regular user reviews, andthe address with a link to a map of the location (see Figure 2.5). Presenting this level of datadirectly in the search results helps users find relevant data more quickly, leading to higher click-through rates and traffic for the site owners.Figure 2.5. Example of a Rich Snippet – Local Restaurant Review.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 20ConclusionWhile much material exists describing what rich snippets are and how they aretheoretically useful to machines (search engines) and humans (searchers), little has been done todemonstrate the true impact of rich snippets on the practice of SEO. Initial eye-tracking studieshave shown that searchers are attracted to rich snippets that are presented in SERPs, leading tohigher click-through-rates. Star ratings and reviews, in particular, have been demonstrated toimpact buyer purchasing habits and directly impact revenues. Despite this, the full effect of richsnippets, and in particular, microdata, has not been explored.To better understand the effect of microdata on search engine optimization, further studyis needed. The attitudes and experiences of search engine optimization professionals need to beexplored. These are the professionals that determine if and how microdata fits into the overallsearch engine optimization strategy. The level of effort required and the payoff expected willdetermine if microdata is just a fad, or if it is here to stay.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 21Chapter IIIMethodologyIntroductionMicrodata is a new development within the Search Engine Optimization (SEO) industry,and thus few studies have been conducted specific to microdata. The purpose of thisstudy was toexamine the effect of microdata on search engine optimization. In particular, the attitudes andexperiences of search engine optimization professionals were explored.This chapter describes the participants of the study and how they were selected,thematerials, measures, equipment and organizational procedures followed, the type of design usedin the study, the variables that were measured, and a detail of the procedures that were followed.ParticipantsThe participants in the studywereSearch Engine Optimization (SEO) professionals whowere selected based on their membership in various online professional networking groups. Theprofessional networking groups included: Inbound Marketers LinkedIn group, InboundMarketing University Alumni LinkedIn group, Market Motive LinkedIn group, TriiibesMembers LinkedIn group, and SEOmoz LinkedIn group. Members of these groups were invitedto participate in an online survey. A total of twelve SEO professionals were included in thestudy.The Inbound Marketers LinkedIn group is an online group for marketing professionals.The group was created on September 21, 2007 and consists of 79,702 members. The groupforms a community of marketers who are interested in online techniques like ―inboundmarketing, search engine optimization (SEO and social media,‖ (Inbound Marketers, n.p., 2012).
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 22The Inbound Marketing University Alumni LinkedIn group is a group of certifiedinbound marketing professionals. The group was created on June 20, 2009 and consists of 2,268members. The group is a place for graduates of the Inbound Marketing University certificationprogram to connect and share ideas (Inbound Marketing University Alumni, 2012).Market Motive is a subscription service that provides weekly workshops, tutorials,courses, and certifications to online marketing professionals. The Market Motive LinkedIngroup is a place for Market Motive subscribers to communicate about conversion optimization,online PR, paid search, social media, web analytics, SEO, and email marketing. The group wascreated on March 31, 2009 and includes 230 members (Market Motive, 2012).The Triiibes Members LinkedIn group is a place for members of Seth Godin’s Triiibesnetwork. Seth Godin’s Triiibes network is a by-invitation-only group of marketingprofessionals. The group was created on August 7, 2008 and consists of 328 members (TriiibesMembers, 2012).The SEOmoz LinkedIn group is a place for search engine optimization professionals(SEOs) to connect, find resources, and network. The group is run by SEOmoz, a provider ofSEO tools and tutorials. The group was created on April 20, 2010 and consists of 8,140members (SEOmoz, 2012).MaterialsA survey of search engine optimization (SEO) industry professionals was conducted toexamine their experiences and opinions regarding microdata. The study was conducted usingSurveyMonkey’s online survey tool. Participants were invited to participate in the study viavarious professional LinkedIn groups where they were encouraged to click on a hyperlink and
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 23answer 14 survey questions using the online survey tool. The survey included nine multiplechoice questions allowing a single answer, four multiple choice questions allowing multipleanswers, and one optional essay question. Access to the Internet was required to complete thesurvey.DesignThe research design was a quantitative, cross-sectional, descriptive survey. The purposeof a quantitative study is to ―quantify data and generalize results from a sample to the populationof interest‖ (Snap Surveys, n.p., 2012). The survey questions examined the opinions andexperiences of SEO professionals as they relate to microdata with the purpose of quantifying thedata and generalizing the results to the SEO industry.Given the requirement of participants to be an SEO professional, a probability samplingproved too difficult. A nonprobability sampling method was instead used, which still allowedfor generalization about the culture of SEO professionals as it relates to microdata (Bernard,2000). The survey was conducted at a single point in time, making it cross-sectional in nature(Creswell, 2002).The survey questions were designed to gather quantitative, descriptive data regarding thefollowing areas of interest:1. Identify the current role of the SEO professional2. Identify the amount of SEO experience the professional has acquired3. Identify the schemas the SEO professional has used in the previous 12 months4. Identify which types of structured data the SEO professional has attempted tocommunicate to the search engines within the previous 12 months
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 245. Identify which types of structured data the SEO professional has successfullyincorporated into search results (i.e. rich snippets)6. Identify which search engines the SEO professional has been successful with atincorporating structured data in search results (i.e. rich snippets)7. Identify how many times the SEO professional has visited Schema.org in the previous 12months8. Learn the SEO professional’s opinion regarding the effectiveness of schemas to increasesearch engine rankings9. Learn the SEO professional’s opinion regarding the effectiveness of rich snippets toincrease click-through-rates of search results10. Learn the SEO professional’s opinion regarding the effectiveness of higher click-through-rates to increase rankings with the search engines11. Learn the SEO professional’s opinion regarding the difficulty of incorporating Microdatainto web pages12. Learn the SEO professional’s opinion regarding the effort required to incorporateMicrodata into web pages13. Identify the likelihood that the SEO professional will include Microdata in his or hersearch engine optimization strategy during the following 12 months14. Collect any other thoughts, opinions, or experiences that the SEO professional would liketo share about Microdata
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 25ProcedureA brief introduction to the survey was posted on search engine optimization (SEO)industry LinkedIn groups requesting participation. Participants from the groups were self-selected by clicking on a hyperlink that was included in the LinkedIn discussion posts. Theparticipants then completed the survey using SurveyMonkey’s online survey software. The datawas then analyzed using SurveyMonkey’s online survey software.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 26Chapter IVResultsIntroductionThis chapter includes a description of the data that was collected during the course of thestudy. Survey responses were collected, compiled, and analyzed using Survey Monkey’s onlinesurvey tool. The charts below were generated by the software and represent all of the surveyresponses as they were entered by the study participants. Counts and percentages arerepresentational of the number of responses received for each survey question, and not all surveyquestions received an answer from all participants of the study. This chapter does not include aninterpretation of the data. The interpretation of the data will appear in Chapter V.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 27Findings of the StudyFigure 4.1. Current Search Engine Optimization (SEO) Role.This question received a total of twelve responses. Three respondents, 25.0%, selectedthat they were currently in a role as an in-house search marketer. One respondent, 8.3%, selectedthat he or she was currently in a role as an agency search marketer. Three respondents, 25.0%,selected that they were currently an independent consultant. Five respondents, 41.7%, selectedthat they did not currently fulfill any of the roles stated above.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 28Figure 4.2. Years of SEO Experience.This question received a total of twelve responses. Four respondents, 33.3%, selectedthat they had less than a year of SEO experience. One respondent, 8.3%, selected that he or shehad 1-2 years of SEO experience. One respondent, 8.3%, selected that he or she had 2-3 years ofSEO experience. Three respondents, 25%, selected that they had 4-5 years of SEO experience.Three respondents, 25%, selected that they had 5-10 years of SEO experience. None of therespondents had more than 10 years of SEO experience. The respondents of the study had awide range of SEO experience.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 29Figure 4.3. Schemas Used by Respondents within the Previous 12 Months.This question received a total of eleven responses. One respondent, 9.1%, selected thathe or she had used RDFa within the previous 12 months. None of the respondents selected thatthey had used Microformats within the previous 12 months. Two respondents, 18.2%, hadselected that they had used Microdata within the previous 12 months. Eight respondents, 72.7%,selected that they had not used RDFa, Microformats, or Microdata within the previous 12months.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 30Figure 4.4. Types of Structured Data that was Attempted within the Previous 12 Months.This question received a total of ten responses. Four respondents had attempted tocommunicate reviews to the search engines within the previous 12 months, three had attemptedto communicate People, five had attempted to communicate Products, five had attempted tocommunicate Businesses and organizations, three had attempted to communicate Recipes, twohad attempted to communicate Events, none had attempted to communicate Music, and four hadattempted to communicate Video content. Three respondents had not attempted to communicateany of the types of structured data that were listed within the previous 12 months.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 31Figure 4.5. Types of Structured Data that was Successfully Incorporated into Search Resultswithin the Previous 12 Months.This question received a total of ten responses. Three respondents had successfullyincorporated reviews into search results (i.e. rich snippets) within the previous 12 months, threehad incorporated People, four had incorporated Products, three had incorporated Businesses andorganizations, two had incorporated Recipes, three had incorporated Events, none hadincorporated Music, and two had incorporated Video content. Four respondents had notsuccessfully incorporated into search results (i.e. rich snippets) any of the types of structured datathat were listed within the previous 12 months.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 32Figure 4.6. Search Engines Where Structured Data was Successfully Incorporated.This question received a total of ten responses. Seven respondents, 70%, hadsuccessfully incorporated structured data into Google’s search results (i.e. rich snippets) withinthe previous 12 months. One respondent, 10%, had successfully incorporated structured datainto Bing’s search results (i.e. rich snippets) within the previous 12 months. Two respondents,20%, had successfully incorporated structured data into Yahoo!’s search results (i.e. richsnippets) within the previous 12 months. Three respondents, 30%, had not successfullyincorporated structured data into Google, Bing, or Yahoo’s search results.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 33Figure 4.7. How Many Times Respondents had Visited Schema.org in the Previous 12 Months.This question received a total of ten responses. Seven respondents, 70%, had nevervisited Schema.org. One respondent, 10%, had visited Schema.org 1-3 times in the previous 12months, and two respondents, 20% had visited Schema.org more than 10 times in the previous 12months.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 34Figure 4.8. Likelihood of RDFa, Microformats, or Microdata to Increase Rankings.This question received a total of ten responses. 60% of respondents were not sure if theuse of RDFa, Microformats, or Microdata would increase rankings with the search engines. 20%believed that it would increase rankings somewhat, and 20% believed that it would not increaserankings.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 35Figure 4.9. Likelihood of Rich Snippets to Increase Click-Through-Rates.This question received a total of ten responses. 50% of respondents believed that richsnippets either somewhat or definitely increase click-through-rates of search results. 40% ofrespondents were unsure if rich snippets increase click-through-rates, and only 10% believed thatrich snippets do not increase click-through-rates of search results.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 36Figure 4.10. Likelihood of Higher Click-Through-Rates to Increase Rankings.This question received a total of ten responses. 40% of respondents believed that higherclick-through-rates would increase rankings with the search engines. 60% of respondents wereunsure if higher click-through-rates would increase rankings. None of the respondents indicatedthat they believed that higher click-through-rates would not increase rankings.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 37Figure 4.11. Difficulty of Incorporating Microdata into Web Pages.This question received a total of ten responses. 60% of respondents believed thatincorporating microdata into web pages was neither easy nor difficult. 10% of respondentsbelieved that incorporating microdata was somewhat easy, and 30% believed that it wassomewhat difficult.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 38Figure 4.12. Worth of Effort to Incorporate Microdata into Web Pages.This question received a total of ten responses. 50% of respondents were unsure if it wasworth the effort to incorporate microdata into web pages. 30% of respondents believed that itwas either somewhat or definitely worth the effort to incorporate microdata into web pages, andonly 20% believed that it was not really worth the effort.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 39Figure 4.13. Likelihood of Including Microdata in the SEO Strategy During the Next 12 Months.This question received a total of nine responses. 55.5% of respondents were eithersomewhat likely or very likely to include microdata in their search engine optimization (SEO)strategy in the next 12 months. 22.2% of respondents were unsure, and 22.2% were eithersomewhat unlikely or very unlikely to include microdata in their search engine optimization(SEO) strategy in the next 12 months.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 40Do you have any other thoughts, opinions, or experiences youd like toshare about Microdata?RDFa Lite has incorporated the design of microdata, and my feeling is that RDFa Lite isjust as easy to integrate in HTML as microdata. see the announcement:http://blog.schema.org/2011/11/using-rdfa-11-lite-with-schemaorg.htmlHavent done much with microdata but plan on it in the futureFigure 4.13. Additional Thoughts, Opinions, or Experiences about Microdata.This optional, open-ended question received a total of two responses. One respondentindicated that he or she believed that RDFa Lite, a new development, was similar to microdataand just as easy to integrate. One respondent indicated that he or she had not done much withmicrodata, but planned on it in the future.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 41SummaryThis chapter included a description of the data that was collected during the course of thestudy. This description included data regarding the current role of the respondents, the numberof years of SEO experience they held, the schemas they had used within the previous 12 months,the types of structured data that they had attempted to communicate to the search engines withinthe previous 12 months, the types of structured data that they weresuccessful at incorporatinginto search results within the previous 12 months, the search engines where they were successfulat incorporating structured data, and how many times they had visited schema.org in the previous12 months.The opinions of respondents regarding the likelihood of RDFa, microformats, ormicrodata to increase rankings in search results were described, along with the likelihood of richsnippets to increase click-through-rates, and the likelihood of higher click-through-rates toincrease rankings.The respondents’ opinions regarding the difficulty of incorporating microdata into webpages, and the worthiness of the effort required to incorporate microdata into web pages wasdescribed. The likelihood that respondents would include microdata in theirSEO strategy duringthe next 12 months was also described with additional thoughts, opinions, and experiences ofrespondents regarding microdata.An analysis of the data was not included, but will appear in thenext chapter.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 42Chapter VConclusion and RecommendationsIntroductionThe purpose of the study was to examine the effect of microdata on search engineoptimization. Rich snippets represent an important change to the way search results aredisplayed to users and Microdata facilitates how website owners and webmasters cancommunicate relevant information to search engines for display in search results.Microdata is a relatively new development that has the potential to have a significantimpact on the search engine optimization industry because it is now universally supported by thethree major search engines: Google, Bing, and Yahoo!.. The results of the study can providesearch engine optimization professionals with a better understanding of the importance that otherSEO professionals are placing on microdata in their overall SEO efforts. This data can then helpSEO professionals to better determine the possible importance of microdata in their own overallsearch engine optimization strategy.Early indications were that for a small investment of time, search engine optimizers maysee a large impact in how users interact with search results. While microdata was not expectedto be a direct ranking factor, it was likely be an indirect ranking factor because of changes in theway users interact with search results. Particularly, search result click-through-rates wereexpected to increase, sending a signal to search engines that the associated pages are relevant tosearch queries. Having a single schema that applies to all three of the major search engines alsowas expected to make the job of a search engine optimizer that much easier.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 43ConclusionWhile the purpose of the study was to examine the effect of microdata on search engineoptimization, the results show that it may still be too early to decide. Rich snippets do in factrepresent an important change to the way search results are displayed to users, and Microdatadoes facilitates the communication of relevant information to the search engines, but microdatahas not yet reached widespread adoption by search engine optimization professionals.Even though microdata is now universally supported by the three major search engines,very few participants in the study had ever attempted to utilize it. The participants of the studyhad attempted to communicate nearly every type of structured data that microdata is equipped tohandle, but had failed to use microdata in those attempts. While some of the participants weresuccessful in their attempts, their lack of experience with microdata likely affected their ability tosucceed in all of those efforts. In fact, 70% of the participants in the study had never visitedSchema.org, the site created by the three major search engines to outline and describe the schemato website owners and webmasters.The hypothesis of the study was that for a small investment of time, search engineoptimizers could see a large impact in how users interact with search results, increasing click-through-rates, and indirectly increasing rankings. Participants of the study were relativelyconfident that rich snippets could increase click-through-rates, and that higher click-through-rates could lead to higher rankings, but were unconvinced that schemas such as microdata couldincrease rankings. It is unclear if participants merely failed to link the use of microdata with thedisplay of rich snippets, and therefore higher click-through-rates and rankings, or if they simplydid not believe that microdata was effective at influencing search engines to display richsnippets.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 44Participants in the study did not perceive the incorporation of microdata as easy, andwere generally unsure if the effort to incorporate microdata into web pages was worth the effort.The participants did expect to include microdata in their search engine optimization strategy inthe next 12 months, however.RecommendationsThe participants’ lack of experience with microdata clearly prevented them from drawingconclusions as to the effect it could have on their SEO efforts. Even though they were not sure ifincorporating microdata would be worth the effort, or that it would have an impact on rankings,they expressed a willingness to test it within the next 12 months. Search engine optimizationprofessionals who are considering the inclusion of microdata in their overall SEO strategy shouldrecognize that their competitors are likely to do so soon and that if microdata does eventuallyprove to be effective SEOs who wait to incorporate it will be at a disadvantage.While the use of microdata may lead to higher click-through-rates, the increase may onlyaffect results that have already achieved first-page rankings. Rankings on lower pages receiveless traffic, causing click-through-rates to become a less important factor. It may be wise,therefore, to focus first on getting to the first page of results, then on the incorporation ofmicrodata with the intention of increasing click-through-rates, and ultimately even higherrankings.Considerations for Future ResearchMicrodata is relatively new to the SEO industry and future research on this topic is stillneeded. This study was limited in scope and only included 12 participants, and participants wereselected using a nonprobability sampling method. The following recommendations wouldimprove future studies:
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 451. A larger sample size is recommended, and a probability sampling method couldprovide results that more closely represent the opinions, views, and experiences ofthe SEO industry as a whole.2. Does the amount of experience that a search engine optimization professionalholds affect the decision to use microdata?3. Do those who have used microdata in the past plan to continue to use it in thefuture?4. Where does microdata rank in terms of importance with other possibleoptimizations that can be performed (such as on page factors, link building, etc.)?5. Does the industry of the business influence the importance of microdata (serviceproviders, restaurants, ecommerce, informational, etc.)?SummaryThe purpose of the study was to examine the effect of microdata on search engineoptimization. Rich snippets represent an important change to the way search results aredisplayed to users, and microdata facilitates the communication of relevant information to thesearch engines. Microdata has not yet reached widespread adoption by search engineoptimization professionals, but is expected to increase over the next 12 months. Future studiesare needed to measure the impact that the adoption of microdata will have on search engineoptimization.
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 46ReferencesAdida, B., Birbeck, M. (October 14, 2008). RDFa Primer: Bridging the Human and Data Webs.W3C. Retrieved on February 26, 2012 from: http://www.w3.org/TR/xhtml-rdfa-primer/Bernard, H. (December 21, 2000). Sampling. Social Research Methods: Qualitative andQuantitative Approaches. Sage Publications, Inc. Retrieved on April 14, 2012 from:http://fycs.ifas.ufl.edu/swisher/OTS/bermard%20on%20sampling.pdfChattopadhyay, S., Goel, K., Guha, R., Gupta, P., Hansson, O. (March 11, 2010). Microdatasupport for Rich Snippets. Webmaster Central Blog. Retrieved on February 26, 2012from: http://googlewebmastercentral.blogspot.com/2010/03/microdata-support-for-rich-snippets.htmlCreswell, J. (July 15, 2002). A Framework For Design. Research Design: Qualitative,Quantitative, and mixed methods approaches. (2nd ed.) Retrieved on April 14, 2012from:http://files.myopera.com/caohockinhtek21/blog/Qualitative,%20Quantitative,%20and%20mixed%20methods.pdfEnge, E. (Interviewer) & Forrester, D. (Interviewee). (September 7, 2011). How Bing Uses CTRin Rankings, and more with Duane Forrester (Interview transcript). Retrieved from StoneTemple Consulting Web site: http://www.stonetemple.com/search-algorithms-and-bing-webmaster-tools-with-duane-forrester/Enge, E. (November 7, 2011). How To Use Rich Snippets, Structured Markup For High PoweredSEO. Search Engine Land. Retrieved on April 14, 2012 from:http://searchengineland.com/how-to-use-rich-snippets-structured-markup-for-high-powered-seo-99081González-Caro, C., Marcos, M. (2010). User behavior in the search engines results page: a studybased on the eye tracking technique. El professional de la información. 2010, Julio-Agosto, v. 19, n. 4, pp. 348-358. Retrieved on February 26, 2012 from:http://grupoweb.upf.es/WRG/dctos/marcos__gonzalez_2010.pdfGoogle. (2010). Rich Snippets Testing Tool. Google Webmaster Tools. Retrieved on February26, 2012 from: http://www.google.com/webmasters/tools/richsnippetsGoogle. (2011). Rich Snippets for Local Search. Google Maps. Retrieved on February 26, 2012from: http://maps.google.com/help/maps/richsnippetslocal/Google. (July 23, 2011). About microdata. Google Webmaster Tools. Retrieved on February 26,2012 from:
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 47http://support.google.com/webmasters/bin/answer.py?hl=en&answer=176035&topic=1088472&ctx=topicGoogle. (2012). Company Overview. About Google. Retrieved on May 19, 2012 from:http://www.google.com/about.company/Google. (January 11, 2012). Schema.org FAQ. Google Webmaster Tools. Retrieved on February26, 2012 from:http://support.google.com/webmasters/bin/answer.py?hl=en&answer=1211158&topic=1088472&ctx=topicGoogle. (February 16, 2012). Rich snippets (microdata, microformats, and RDFa). GoogleWebmaster Tools. Retrieved on February 26, 2012 from:http://support.google.com/webmasters/bin/answer.py?hl=en&answer=99170Hickson, I. (February 6, 2012). HTML Microdata. W3C. Retrieved on February 26, 2012 from:http://dev.w3.org/html5/md/Overview.htmlInbound Marketers. (2012). Inbound Marketers – For Marketing Professionals Group Profile.LinkedIn Groups. Retrieved on May 29, 2012 from:http://www.linkedin.com/groups/Inbound-Marketers-Marketing-Professionals-21005Inbound Marketing University Alumni. (2012). Inbound Marketing University Alumni GroupProfile. LinkedIn Groups. Retrieved on May 29, 2012 from:http://www.linkedin.com/groups/Inbound-Marketing-University-Alumni-2045641Luca, M. (November 2010). Reviews, Reputation, and Revenue: The Case of Yelp.com. JobMarket Paper. Retrieved on February 26, 2012 from:http://www.nber.org/conf_papers/f5990/f5990.pdfMarket Motive. (2012). Market Motive Group Profile. LinkedIn Groups. Retrieved on May 29,2012 from: http://www.linkedin.com/groups/Market-Motive-1877017Meyers, P. (October 5, 2011). Eye-Tracking Google SERPs. SEOmoz.org. Retrieved on February26, 2012 from: http://www.seomoz.org/blog/eyetracking-google-serpsMicroformats.org. (2012). About Microformats. Microformats.org. Retrieved on February 26,2012 from: http://microformats.org/aboutSchema.org. (June 29, 2011). Getting started with schema.org. Schema.org. Retrieved onFebruary 26, 2012 from: http://www.schema.org/docs/gs.htmlSEOmoz. (2012). SEOmoz Group Profile. LinkedIn Groups. Retrieved on May 29, 2012 from:http://www.linkedin.com/groups/SEOmoz-2976409
    • THE EFFECT OF MICRODATA ON SEARCH ENGINE OPTIMIZATION 48Snap Surveys. (2012). Qualitative vs Quantitative Research. Snap Surveys. Retrieved on April14, 2012 from: http://www.snapsurveys.com/techadvqualquant.shtmlTriiibes Members. (2012). Triiibes Members Group Profile. LinkedIn Groups. Retrieved on May29, 2012 from: http://www.linkedin.com/groups/Triiibes-Members-162640