MOZ Releases Their Own Ranking Factors for 2015
In August, Moz published their highly-anticipated Search Engine Ranking Factors study. Every two years, the Seattle-based SEO platform gathers the opinions of industry experts and conducts correlation studies to advance their understanding of Google’s algorithms. This year, the company asked 150 of the world’s leading search marketers to give their expert opinions on over 90 ranking factors. For the correlation segment of the study, Moz teamed up with SimilarWeb, DomainTools and AHRefs and used their data for analysis.07 With the correlation study and the expert survey, Moz was able to come up with their biggest, most comprehensive study yet.
Part I: Correlation StudyThe primary purpose of Moz’s Ranking Correlation Study was to see which attributes of websites and pages can be associated to higher rankings in SEPRs. These include keyword usage, page load speed, anchor text and over 170 other attributes. Their methodology consisted of Data Set Construction and Statistical Analysis.
Data Set Construction
- Selecting a list of keyword queries (they obtained a final list of 16,521 queries)
- SERPs (they pulled the top 50 search results for each of the queries on the query list)
- Calculating ranking factors (they collected factors from a variety of sources, including Mozscape URL metrics, SimilarWeb factors, Ahrefs factors, and DomainTools factors)
Statistical AnalysisThey computed various metrics between search position and the ranking factors. They also determined a factor’s overall visibility in the search results. Using the analysis, they put the factors in order of most influential to least influential and gave an estimate of the relative influence of different factor types (e.g., social signals vs. link vs. on-page factors.) Moz reiterates that the study doesn’t reveal or confirm if search engines actually use these attributes in their ranking algorithm. Rather, it shows which site and page features are most linked with better rankings. The company says this is “a fine, but important distinction.”
SAMPLE OF THE FINDINGS:
Example1: Page-Level Link-Based FeaturesLooking at the chart, you will see the features describing link metrics of the individual page, such as page authority and number of links, and their correlation to higher rankings.
Example 2: Domain-Level Keyword Usage FeaturesThis chart contains features describing how keywords are used in the subdomain name, and how much value this can have on the rankings. Link-based and keyword features, as demonstrated in these examples, are only two of the categories they examined. Their complete correlation study includes 12 different categories of data.
Part II: Expert SurveyMoz believes that while correlation data can provide valuable insight into the workings of Google’s algorithm, SEOs can also benefit from the collective wisdom of search marketing experts. The researchers asked over 150 marketing professionals and SEO specialists to rate the influence of broad areas of ranking factors. The following data illustrates the respondents’ opinions on the value of factors assumed to take part in Google’s ranking algorithm. Respondents ranked Domain-level Link Features the highest (8.22/10). These features include quantity of links, trust, and domain-level PageRank. It’s followed by Page-level Link features (8.19/10), which involve the quality of linking sources and anchor text distribution.
CONCLUSION: Quantity and Quality of Link to the Domain and Page Level is Still #1There weren’t a lot of surprises in the study. In fact, it only served to confirm existing notions on what’s helping and hurting a website’s visibility. And despite a few rumors that claim the contrary, the results show strongest correlation between Google rankings and the number of links to a given page. On the page level, it appears that the most important factors include topical relevance of linking pages and domains, raw quality of links from high-authority sites, keywords appearing in the title element and the main content, the uniqueness of content, and mobile-friendliness. On the other hand, important domain-level factors include quality of linking domains and content uniqueness across the whole site. Here are other few important takeaways from the study:
- While there is no strong correlation between social share counts and high ranking, you can gain secondary SEO benefits through successful social sharing.
- Although page-level link metrics show the strongest correlation to ranking, Moz believes the overall links to a site’s subdomain also plays a prominent role in Google’s algorithm.
- Anchor text appears to be another prominent feature of high-ranking results, with the number of unique domains linking with partial-match anchor text (PMAT) on the lead.