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For advertisers leveraging search engine optimization (SEO), having a data-driven understanding of how investments in SEO will drive online results is a difficult problem. The reactions of the search ...

For advertisers leveraging search engine optimization (SEO), having a data-driven understanding of how investments in SEO will drive online results is a difficult problem. The reactions of the search engines (Google, Baidu, Bing, etc) seem unpredictable, and often are – being driven by changing algorithms from the engines, competitive changes, and the ever-changing context of the world wide web.

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SEO Audit: Search Engine Optimization Audit Score v3.0 SEO Audit: Search Engine Optimization Audit Score v3.0 Document Transcript

  • Covario’s Search Engine Optimization TM Audit Score v3.0 Covario’s Search Engine Optimization Audit Score v3.0 A Technical Paper on How It Is Derived By Craig Macdonald, Chief Marketing Officer, Covario For advertisers leveraging search engine optimization (SEO), having a data-driven understanding of how investments in SEO will drive online results is a difficult problem. The reactions of the search engines (Google, Baidu, Bing, etc) seem unpredictable, and often are – being driven by changing algorithms from the engines, competitive changes, and the ever-changing context of the world wide web. Covario helps advertisers improve the predictability of the ROI of their SEO investments. We do so through development of the Covario Audit Score, embedded in Covario’s Organic Search Insight (OSI) – our SEO page auditing and reporting technology. As part of the SEO audit, we gather statistics on how changes to over 800,000 landing pages impact changes in search engine ranking for keywords associated with those pages. In the past, we updated the score as the changes in the algorithm dictate – there have been 10 adjustments in the score during the past four years. With the launch of our most recent version of the Organic Search Insight™ solution, we have made major changes to one key aspect of the Covario Audit Score – how the system analyzes links and linking strategy. We know this is an important aspect of the search engine ranking algorithms – and we have made significant advances in our ability to measure this impact. The purpose of this document is to outline how the improvements made to the linking analysis have improved the predictability of the Covario Audit Score v3.0 in determining search engine ranking. Specifically, this paper explains how advertisers can use this knowledge to better predict ranking results, and prioritize investments in SEO. Executive Summary Here are some of the key findings from studying the data used to derive Covario Audit Score v3.0. • Covario Audit Score v3.0 includes a new Link Audit Score, which identifies particular Link Hubs that are important in driving higher ranking. • The addition of the new Link Audit Score has improved the predictability of the Covario Audit Score by nearly 3-times (3X) – and it has the closest fit with the Google algorithm. • The analysis of the Covario Audit Score v3.0 shows that the sophistication of search engines in crawling sites for content has improved markedly. Engines find most content now, except in situations where advertisers use a technique called “session ID’s” in their URLs. Session ID’s cause all sorts of distress to search engine crawlers. • On-Page content is of lesser importance in driving ranking. Most advertisers have developed processes that allow them to ensure that content is being generated at scale.Published January 2011. © 2011 Covario, Inc. All rights reserved. 1
  • Covario’s Search Engine Optimization Audit Score v3.0 • Off-Page factors – specifically linking strategy – is the key to driving ranking improvements. Covario Audit Score v3.0 shows clearly that link building is about quality, not quantity. The statistical impact of the raw count of internal and external links is about 1/5th the impact of having links to a small number of well-regarded sites. • Overall, Covario Audit Score v3.0 explains 30-35% of the variability in ranking, and weighs (i) off-page factors like link strategy as 50% of its predictive-ness, (ii) on-page content factors at 40%, and (iii) technical factors at only 10%. Overview of the Covario Audit Score The Covario Audit Score is a statistic, constructed to evaluate SEO health of an advertiser’s webpage in the context of a given set of keywords, derived by the advertiser (or their agency). The score evaluates a series of factors – both on-page and off-page – to determine SEO health. Those factors are weighed based on their statistical relationship to a dependent variable. In this case, the ranking on the search engines. We use ranking, as opposed to “conversions” for example, for a number of reasons. • Rankings are easily obtainable through automated processes and at scale. This is important given the size of the data set necessary to do the analyses for deriving the score. • Rankings are a consistent metric across advertisers, unlike conversions, which vary and are often ill-defined. The Covario Audit Score is normalized to vary between 0 (“bad”) and 100 (“good”). The score, being normalized, is able to be manipulated to provide derivative scores – like the average score for a set of pages, a site, a business unit, or even across other advertisers for competitive analysis. Last, the score is meant to have “meaning” – i.e., as the Covario Audit Score gets better for a given keyword-page pairing, an advertiser should expect, within the statistical significance, that ranking will improve. The Factors Used in the Covario Audit Score The Covario Audit Score is made up of a series of on-page and off-page factors related to SEO. These factors are divided into three groups – two (2) on-page groups and one (1) off-page group. Content Factors For Content Factors, each page is evaluated using a given set of keywords: • Keyword emphasis – percentage of identified keywords that are emphasized. • Tag Optimization – there are various checks done on tags – keyword presence, keyword uniqueness. The analysis also looks at partial matches for phrases. o Title Tag o Body Tag o Header Tags (1,2,and 3) • Keyword usage in URL – identification of keyword in the URL. • Image Tag. Technical Factors Technical Factors evaluate how effectively the search engine “crawlers” penetrate web pages to ascertain their relevancy for search terms. The Covario Audit Score evaluates:Published January 2011. © 2011 Covario, Inc. All rights reserved. 2
  • Covario’s Search Engine Optimization Audit Score v3.0 • Return Errors. Does the page render (300, 400, 500 series error checks). • Page Return Time. Evaluation of the time it takes for the page to render. • URL Analysis. o URL length – the character length of the URL o Distance from root directory – the number of “/”’s the landing page is from the root. o Use of dynamic parameters in URL o Use of session ID’s in URL • Page size. The number of bytes in a page (similar to Page Return Time). • Navigation Assessment. The system evaluates how effectively crawlers can use the navigation to find additional content. o Use of opaque Flash Navigation design o Use of opaque HTML design Off-Page Linking and Context Factors The analysis evaluates the off-page context of each webpage (for a given keyword) by looking at a number of key factors: • Count of external links. • Count of internal links. • Importance of external links (through Link Hub Score) –the importance of links is evaluated using a proprietary methodology that is described below. • Anchor text analysis – percentage of inbound external links containing the keyword (or partial matches) in the text surrounding the hyperlink on the referring page. These factors are measured directly. Due to both the importance, and the nature, of data and structure of external links, the analysis requires a sub-algorithm in order to ascertain the importance of each external link. The next section describes how this algorithm works. Link Importance Analysis Identifying the key links for a particular keyword on a search engine is necessary to evaluate the overall SEO health of a webpage-keyword combination. The Covario Audit Score leverages a process to identify and prioritize links to a webpage using the following methodology. • Link Hub Identification. The goal of the process is to identify Link Hubs – these are domains that the search engines weigh heavily in their ranking algorithms for keywords. o For a given keyword, the top 10 listings on a search engine are ascertained. This is a straightforward process and highly scalable. o For each of the top10 listing URLs, the top 100 inbound external links for each URL are identified. The source of this information is Yahoo Site Explorer (YSE). YSE is global and is considered the best source of link data in the industry. o This process yields 1,000 inbound external links per keyword, per search engine. o A matching process is run to see if any of the links for each ranking URL are shared. Shared links are potential Link Hubs.Published January 2011. © 2011 Covario, Inc. All rights reserved. 3 View slide
  • Covario’s Search Engine Optimization Audit Score v3.0 Figure 1. Link Hub Identification • Link Hub Prioritization. Link Hubs, once identified, require prioritization in order to (a) provide recommendations to advertisers on the order of links to build and (b) germane to the analysis, to identify the relative importance of links as based on how the search engine judge performance to make the Audit Score more predictive. o Link Hub Ranking Comparison. The analysis takes (i) a raw count of the number of top 10 listings that share a link and (ii) which of the specific rank positions share that Link Hub. o Link Hub Ranking Weighings. The ranks of the listing URLs are weighed based on a standard “click through” statistic (see chart below). o Link Hub Score. A normalized score is created which represents the average of the click through rates for the URLs that are shared for each Link Hub identified. Link Hub Score = (∑(CTR Ranking_URL ))/(∑ (count of shared rankings))Published January 2011. © 2011 Covario, Inc. All rights reserved. 4 View slide
  • Covario’s Search Engine Optimization Audit Score v3.0 This is done per identified Link Hub and is used in the analysis. Figure 2. Click Through Rate by Ranking These are the factors that make up the Covario Link Audit Score. With this information, the analytics determine the relative importance of each factor. Statistical Methodology to Evaluate Relative Importance of SEO On-Page and Off-Page Factors in Ranking To evaluate the importance of the various factors that make up the Covario Audit Score, a standard linear regression methodology is employed. The analysis evaluates how important changes in each of the on-page and off-page factors are in determining changes in ranking on the various search engines.Published January 2011. © 2011 Covario, Inc. All rights reserved. 5
  • Covario’s Search Engine Optimization Audit Score v3.0 The figure below shows the analytic framework. Figure 3. Covario Audit Score Analytic Framework The independent variables, the on-page and off-page factors, are used to predict change in rank. With this framework, the objective is to develop a formula like the following: This is simplified for space considerations only. The analysis looks for the ’s (or independent variable coefficients) for ALL of the independent variables as well as the ∆’s (changes in each independent variables and ranking). Data Used in the Analysis To develop the s – the following data set was used: • The analysis was conducted on Google, Bing, and Yahoo in the US. • The data is from November 1, 2010 through December 15, 2010. • There were 937 data points in the analysis – representing web page – keyword pairs. We use this level of specific data to ensure that the measurement of changes to pages corresponds to measurable changes to the keyword rankings on the search engine results pages. • All keywords with ranking beyond position 50 were discarded in order to ensure variability in ranking is measured appropriately. • Also, any data with missing or corrupted data was eliminated from the study. The analysis was conducted at the aggregate and search engine level for each search engine.Published January 2011. © 2011 Covario, Inc. All rights reserved. 6
  • Covario’s Search Engine Optimization Audit Score v3.0 Correlation Analysis Before evaluating the comprehensive regression model, the following table shows the correlation analysis on the data. A couple of key points: • Overall, a correlation less than .05 with this data set is considered insignificant. • Given that “1” is considered a good ranking, and “50” is considered poor – many of the correlations are negative (i.e., as the independent variable improves or gets larger, the ranking gets lower as it is driven toward “1”). • Java script navigation had no variation – i.e., the sample set did not detect any java script navigation errors, so the correlation is NA. The table shows the correlations for each search engine – Bing, Yahoo, Google and in total. Correlation Anlaysis Audit Criteria Bing Google Yahoo Total Technical Audit Checks Return Errors 0.067 0.033 0.069 0.057 Response Time 0.240 0.344 -0.001 0.215 Page Size -0.063 -0.084 0.020 -0.030 URL Character Length* -0.033 0.034 0.083 0.023 Use of Flash Navigation 0.054 0.067 0.051 0.057 Use of Java Script Navigation NA NA NA NA Use of Session IDs in URL 0.054 0.067 0.051 0.057 Use of Dynamic Parameters in URL -0.057 -0.058 -0.041 -0.052 Proximity of Page to Root Directory 0.080 0.188 0.135 0.133 Content Audit Checks Gold Word Density Check -0.102 -0.260 -0.193 -0.180 Gold Word Emphasis Check -0.085 -0.114 -0.050 -0.080 Title Tag Optimization 0.042 -0.062 0.269 0.082 Meta Tag Optimization 0.071 -0.179 0.091 -0.002 Body Tag Content 0.054 0.067 0.051 0.057 H1 Tag Optimization 0.175 0.203 0.140 0.172 H2 Tag Optimization 0.054 0.112 0.163 0.108 H3 Tag Optmization 0.087 -0.006 0.139 0.067 Image Optimization 0.108 -0.017 0.023 0.044 Gold Words in URL -0.200 -0.249 -0.335 -0.257 Link Audit Check External Link Count -0.033 -0.097 -0.055 -0.-61 Internal Link Count -0.028 -0.112 -0.050 -0.047 Gold Word in Anchor Text 0.021 -0.100 0.135 0.021 Link Builder Score -0.223 -0.316 -0.184 -0.238 Figure 4. Correlation Table for Covario Audit Score AnalysisPublished January 2011. © 2011 Covario, Inc. All rights reserved. 7
  • Covario’s Search Engine Optimization Audit Score v3.0 From a qualitative standpoint, a couple of key observations are identifiable: • The Link Hub Score described above is a very powerful variable. It has a strong correlation with ranking – particularly on Google and Bing. • Having Gold Words in the URL is also correlated strongly with ranking – in fact, this is the strongest overall correlation. • Page response time is also a strong correlation variable. This relationship should be positive – i.e., as page load time is faster (i.e., lower value) then ranking is better (i.e., lower). Comprehensive Regression Analysis The regression analysis is conducted using the Line Estimation functionality in Microsoft Excel. The result of the analysis shows a very strong predictive capability. For each of the search engines, and in total, here is the amount of variability in ranking explained by the factors analyzed in the Covario Audit Score. • Google – 31.5% • Bing – 15.2% • Yahoo – 26.8% • Total – 27.4% So overall, the analysis is a good predictor of ranking variability – the key test of its usefulness. With that established, it is important to evaluate how to use the relationship between the independent variables to construct the Covario Audit Score. To make the interpretation of the regression more straightforward, the results are expressed below in a series of bar charts that show the relative importance of each factor in predicting ranking. . First, the On-Page Technical Factors: • Use of session ID’s in the URLs continues to be a major factor in ranking. Usage of these protocols has a major negative impact on ranking. • Overall, the importance of technical factors is relatively low. This is driven by two factors. o The advertisers have improved the crawlability of their website. The issues that dominated site construction 3-4 years ago are eliminated in most cases – with indexing of sites being an issue for only particular types of sites. o The search engine platforms have become far more effective in indexing content through improvements made in identifying site structure through various types of navigation techniques.Published January 2011. © 2011 Covario, Inc. All rights reserved. 8
  • Covario’s Search Engine Optimization Audit Score v3.0 Second, the On-Page Content Factors continue to have major relevancy: • As pointed out in the correlation analysis, usage of keyword in the URL is very important factor in search engine ranking and is weighted accordingly in the Audit Score. • In addition, the usage of keyword in the Title, Meta, and H1 tags has a strong impact on ranking change. • Keyword density continues to be a relatively strong factor; however, overall, this has degraded since the last time the Audit Score was updated due to improvements in the search engine crawlers and their ability to identify content.Published January 2011. © 2011 Covario, Inc. All rights reserved. 9
  • Covario’s Search Engine Optimization Audit Score v3.0 Last, the Off-Page or Link Factors analyzed as part of the Audit Score are taking a prominent role: • The Link Hub Score – which is a proxy for the quality of links has a highly significant impact on search engine ranking results. • Both External and Internal Link Counts have a significant impact on ranking – i.e., those pages with more links do marginally better than those with less. Internal links have very little impact, while external links have some impact but nowhere near as strong as the impact of having quality links (as measured through the Link Hub Score). • Having the keywords in the anchor text of inbound external links is considered a relatively strong factor by SEO practitioners – however the analysis shows this to be of middling importance. The table showing the regression results is shown in the Appendix. Computing the Audit Score With the relative weightings of the independent variables established, the Covario Audit Score uses these weightings to create the normalized score. Here is how this is done: • The Covario Audit Score is based on weightings applied to 3 “sub-scores” – one each for Content, Technical, and Linking Strategies. These scores are 0-100 scores reflecting the impact of the underlying factors making up each sub-score. • The weightings are allocated based on the model – specifically the distribution of the sum of the squared errors from the regression analysis. Covario Audit Score = 0.5(Link Audit Score) + 0.4(Content Audit Score) + 0.1(Technical Audit Score) For each sub-score, the scores are normalized as follows: Content Audit Score = [(w1 * Content Factor1) + (w2 * Content Factor2) + etc)]/[Content Factor1 + Content Factor2 + etc] Technical Audit Score = [(w1 * Technical Factor1) + (w2 * Technical Factor2) + etc)]/[Technical Factor1 + Technical Factor2 + etc]Published January 2011. © 2011 Covario, Inc. All rights reserved. 10
  • Covario’s Search Engine Optimization Audit Score v3.0 The entire equation is not being listed here for reasons of brevity. With the Link Audit Score, we have made major changes. Link Audit Score = 0.75(Link Hub Score) + 0.05 * ln(Internal Link Count)/5 + 0.1 * ln(External Link Count)/5 + 0.1[(Count of External links w Anchor Text/External Link Count)]*100 The Link Hub Score is described above. We are using the natural log (ln) of the count of links to deal with the many orders of magnitude in the data. Interpreting Covario Audit Score v3.0 Now that the construction of the Covario Audit Score v3.0 is described – the application of the score is described. Covario Audit Score v3.0 is developed for each page within Covario’s Organic Search Insight – or through Covario’s Organic Search Optimizer Ad-Hoc Auditing capability. Each page is evaluated bi-monthly and Audit Scores are updatable in real time by an advertiser or their agency. When applied to a page: • The Covario Audit Score v3.0 has an average of 50, and this is the same for the Content, Technical and Link Scores. • Link strategy accounts for 50% of the variability in the score, Content for 40% of the variability, and Technical issues 10%. • The Link Score weights quality of links very highly. The external links for a particular page uses YSE, and compares the links to the page to the defined set of Link Hubs for each keyword associated with the page. • If a match is detected between a Link coming to a page and a Link Hub, the value of the Link Hub is aggregated to create the associated score for that page. These then drive the overall Link Hub score for the page. Figure 5. Identification of Link Hub Score for a PagePublished January 2011. © 2011 Covario, Inc. All rights reserved. 11
  • Covario’s Search Engine Optimization Audit Score v3.0 • Content and Technical Scores are developed in a similar way – if an audit passes, the page gets credit for each passed audit based on the weighting scheme from the analysis. And given the statistical relationship established in the analysis, as the score improves, the likelihood of improved ranking is well documented. This is the key to the goal of the Covario Audit Score v3.0 – making the analysis of ROI for SEO more transparent. Covario Audit Score v3.0 is the best way to do this – its ability to identify issues, and prioritize them based on statistical analysis for how those on-page and off-page factors influence ranking – down to specific external links to build – is unparalleled. About Covario Covario, Inc. is one of the largest independent SEM (search engine marketing) and SEO (search engine optimization) solutions providers, offering software and agency services for paid and organic search management. Covario provides large global organizations with robust solutions for paid search advertising, organic search (SEO), social media and display advertising. Covario enables complex and distributed organizations to control their brand integrity; ensure budget transparency; and deliver quantifiable results across business units, distribution channels and languages. Headquartered in San Diego, the company’s growing customer base includes some of the world’s best known brands in technology, retail, ecommerce, financial services, consumer electronics, media, entertainment, publishing and consumer packaged goods. More information about Covario is available by calling 858.397.1500 or online at http://www.covario.com.Published January 2011. © 2011 Covario, Inc. All rights reserved. 12
  • Covario’s Search Engine Optimization Audit Score v3.0 Appendix Appendix 1 – Table of Regression Results for Covario Audit Score v3.0 Regression Analysis Audit Criteria Bing Google Yahoo Total Technical Audit Checks Return Errors NA NA NA NA Response Time NA NA NA NA Page Size 4.300 11.473 -4.222 3.968 URL Character Length* 0.440 1.211 0.396 0.654 Use of Flash Navigation 0.808 -1.087 -0.543 -0.114 Use of Java Script Navigation NA NA NA NA Use of Session IDs in URL -1.427 -1.083 -2.643 -1.610 Use of Dynamic Parameters in URL NA NA NA NA Proximity of Page to Root Directory -0.072 -0.176 0.021 -0.071 Content Audit Checks Gold Word Density Check 0.000 -0.001 0.000 0.000 Gold Word Emphasis Check NA NA NA NA Title Tag Optimization 0.000 0.001 0.000 0.000 Meta Tag Optimization NA NA NA NA Body Tag Content 0.000 0.000 0.000 0.000 H1 Tag Optimization -10.779 -10.388 -15.875 -11.852 H2 Tag Optimization NA NA NA NA H3 Tag Optimization NA NA NA NA Image Optimization 0.000 0.000 0.000 0.000 Gold Words in URL 3.676 1.469 7.582 4.445 Link Audit Check External Link Count -0.648 -0.663 2.198 0.220 Internal Link Count -15.375 -90.323 8.541 -38.186 Gold Word in Anchor Text -4.737 -2.235 -8.309 -4.769 Link Builder Score 0.598 1.223 0.644 0.679 TM 858.397.1500 www.covario.comPublished January 2011. © 2011 Covario, Inc. All rights reserved. 13