Monthly Archives: May 2012

Links – Huge Correlation Between Link Building and Google Ranking

Links have been an integral part of SEO since Google joined the scene.

But recently link building’s popularity has taken a bit of a hit, with many believing that Google have reduced its weighting of PageRank in the algorithm. The emergence social signals and other factors indicating user satisfaction have according to many within the industry eclipsed (or will in the future will eclipse) links as the primary ranking factor.

But this speculation hasn’t been mirrored in my data. Over the course of this post we will examine over 40 link related factors, all of which correlate very well, and a number of which are the most heavily weighted factors in my study.

The main finding from this data, is how well links correlate to ranking in Google. I have tested over 150 potential ranking factors in 6 categories and without a doubt, links stand head and shoulders above any other section of factors.

Link building is a bit of an ugly duckling within the industry, everybody knows its importance, but very few are effective in its practice.

Unlike changing title tags, building quality links requires skill, creativity and determination. Its not easy work, its not the low hanging fruit, but based on the data below, it appears to be the most rewarding.

While I won’t discuss link building strategies in this post, I would like to mention that I feel many strategies are extremely inefficient and unproductive and a lot of the theory behind this area of SEO is fundamentally flawed. I will be publishing some more of these ideas, with anecdotal evidence in the future.

The project

The below data is based on a dataset of the top 100 results in Google, for 12,573 keywords.

I have analysed this data using Spearman’s Rank Correlation Co-efficient, looking for relationships between individual factors and ranking in Google.

I have already published some of the results from the study including domain name related factors, on page factors and domain authority signals.

This is all part of a greater project to bring more science to SEO and make it a truly data driven industry.

There are inherent issues with correlations and they don’t prove anything per se, but as I have covered these issues before I won’t rehash old information, what I will suggest is – that if this is your first time on the site, please read this and this.

I would like to thank SEOMoz for providing incredible access to both their amazing Mozscape API, from which the below results are derived and their expertise and advice. In particular I’d like to thank Rand Fishkin, Dr. Matt Peters and the API support team for all their help.

Data

This Excel Spreadsheet provides the keyword by keyword correlation figures from which the above mean correlations are derived.

Breakdown

Google’s algorithm doesn’t just look at how many links there are to a page, it looks at quality signals, website authority indicators and tries to protect against manipulation.

Basically, just building links isn’t good enough, there are certain kinds of links that are better than others.

Below I have covered the types and areas of link building that are thought to be utilised within the algorithm.

General Links

The correlations for general links, as compared to specific counts such as # of IPs/Cblocks/Domains/Subdomains are significantly lower.

This supports the fact that Google looks at several factors and classifiers when considering the quality of the source of a link.

While this certainly isn’t an interesting finding, it is important from the point of view, that such a conclusion supports a known fact and therefore increases the likelyhood that the data gathered and the resulting correlations are correct and do represent what’s actually happening within the Google algorithm.

I investigate which particular classifiers and types of links would be best in a link profile, below.

Cblocks and IPs

 

Both the number of unique Cblocks and IPs linking to a site are thought to indicate the diversity of a link profile.

Google want to see a variety of sites “voting” for a website’s content. The weighting of each additional link from the same site is reduced relative to a link from a new source.

Knowing this many webmasters began to build “lens sites”, that’s sole goal was to link to the mother site.

It is believed, that to counter this Google implemented an algorithm that could figure out if a link was coming from the same source (i.e. the same webmaster) as the site that was being linked to.

There are a number of factors that Google likely use in such an algorithm, but it would make sense that Google treat links coming from the same IP or Cblock as more likely to be coming from the same webmaster, and thus marginally less trustworthy.

While the data doesn’t prove or disprove this theory, it does show a higher level of correlation for the # of Cblocks/IPs linking than for a general count of the # of links to a page/site/subdomain. Although the difference is small it could support the above theory.

With this data and using some common sense, I would recommend following the current industry practice of building a diversified link profile.

Domains and Subdomains

 

Again the above data further enhances the argument for a diversified link profile.

It also shows a potentially interesting albeit small difference between the # of unique domains vs. subdomains linking. With the # of unique domains coming out on top.

While the difference is too small to make a concrete conclusion, such data would certainly point us in the direction of building links from a diversified set of domains, and treating subdomains on the same root domain as related to each other and therefore each additional link from a separate subdomain on the same root domain as slightly less valuable than the link before it.

Links to the page

The above data conforms to the seemingly obvious conclusion that if you want to get a page to rank well, then building links directly to that page is the best way to get that to happen.

While most SEO’s will find that stupidly basic, I have seen some SEO’s suggesting that domain level links would be more powerful or a better use of time. The data just doesn’t support that strategy if you are trying to increase the ranking of a specific page.

Links to the page’s domain vs. subdomain

 

Interestingly the strong performance of domains vs. subdomains as the source of a link, is not matched in the location/target of a link. If we are to believe that such marginal differences are important, then the data may suggest (as a number of industry watchers have stated) that Google treat subdomains as separate to the root domain in looking at the host’s (which could be the domain or subdomain) authority.

This seems strange, and I may be reading too much into the data but if the above statement was the case, then Google’s treatment of subdomains as separate sources of content would not be matched by their treatment of subdomains on the same root domain as essentially the same source of links.

If such a conclusion were to be made, then it would be most likely to explained away by the likelihood that Google doesn’t just look at whether its a subdomain or not, and it likely uses much more advanced algorithms to figure out whether a subdomain should be considered part of the same domain.

Thus Google would understand that blogname.wordpress.com is not related to wordpress.com but blog.exampledomain.com is related to exampledomain.com.

Nofollow vs. Followed

 

Here is a classic case of inter-related factors impacting on the correlations of each other, we know that nofollowed links carry no SEO benefit directly, although they may result in some other factors being impacted e.g. someone clicks on a nofollow link and then shares the page on Twitter.

A page with a lot of nofollow links pointing to it, is far more likely to have a lot of followed links pointing to it.

This is because there are standard ratios, different types of links hold within the link profile. And any deliberate alteration by a webmaster is only likely to result in a small shift in those ratios.

There are many inter-factor relationships going on in the above data. Nofollow links may indeed carry no search engine benefit, but could still show the strong correlations, as above.

Marginal differences in the correlations shown by different categories of links, e.g. followed vs. nofollowed may be more important than it appears as face value.

This is why I have read a lot into such small differences.

SEOMoz Metrics

SEOMoz have created a number of algorithms that are meant to mimic Google’s link related algorithms. I don’t know the exact make-up of these algorithms, but I thought it would be interesting the test the performance of these algorithms, to check whether using these metrics as a measure of the success of your link building is a good idea.

If you are interested, here’s the general make-up of these algorithms: MozTrust, MozRank, Domain Authority, Page Authority.
 

Wow! Moz really seem to have done a great job developing their algorithms. In keeping with the above data on the value of page level metrics, Page Authority comes out at an astounding .36 correlation, which is massive, making it the highest correlated factor out of the 150+ I have tested.

Comments

The link related data is in my opinion is on par with the on page factors as being the most interesting and important to the SEO industry. Both lead to the same conclusion, on page factors are by far less important than off page factors.

Links aren’t just about SEO

Building links isn’t just an exercise in SEO, its also an exercise in marketing. Links can drive a lot of direct traffic from people clicking on them and also can build your brand name.

Its important to factor the direct traffic value of links into your link building decisions. This is particularly evident where a second, third or fourth link from the same site, may seem like a step down in SEO importance but may still provide high value direct traffic.

Links aren’t dead!

If I read another article proclaiming PageRank or link building is dead, I’ll scream. Its very simple, the scientific data simply does not support the speculative accusations of the reduced value of PageRank or link building.

In fact in many cases their level of correlation has increased, not decreased since Moz conducted their 2011 study.

Link related factors are far and above the highest correlated set of factors.

While we in the SEO industry recognise the importance of links, I don’t think we covert this mental idea, into action. I don’t believe that SEOs spend the right proportion of their time on link building. And SEO blogs, conferences and experts certainly don’t talk enough about how to do great link building.

There definitely isn’t enough data available on what the best link building strategies are, with the majority of link related blog posts stemming from speculation, not data driven proof, something I hope to address scientifically through this project.

I welcome presentations like this from Mike King, that back up strategies with solid data.

Bottom line – spend a whole lot more time link building.

Domain Authority

New Correlation Data Suggests Enhanced Importance of Site Wide SEO

 

SEO’s are huge believers in signals relating to Google’s overall perception of a website.

It makes a lot of sense, if Google can understand that Wikipedia’s articles are typically of a higher standard than eHow’s then they can make better decisions on the quality and relevance of web pages on these domains.

By using this data search engines can also make quick decisions regarding new content published by these sites. This fresh content wouldn’t have gained the links and other time related ranking factors as an established article, but may still be relevant to the user. This may be particularly true with news or “query deserves freshness” results.

In addition to gathering data that might indicate the quality of content published on the site, it is thought that Google gathers data on what geographical location, type of user, industry, etc the site targets. Much of this data is difficult or in many cases impossible to gather without being Google, for example a site’s average SERP CTR or bounce rate.

Overall it would be fair to say that Google utilises different models to gather and analyse domain level data pointing to the authority of a website as a whole.

The potential value of domain level factors to the webmaster is immense. If you make a single site-wide improvement, it may impact the ranking of several thousand pages on the site. Domain level SEO offers easy to implement strategies that can hold a much higher ROI than page by page factors.

What data is collected by Google and how much influence it has in the overall ranking of a web page has been theorised and debated for many a year.

Overall what we will see in this article is that domain authority signals are relatively highly correlated, and that for the most part, many of the industry’s theories surrounding these factors have largely been correct, which is refreshing in light of some stunning on page factors’ correlation data.

The study

Over the past 2 months I have gathered data on 31 domain authority signals, for the top 100 results in Google, for 12,573 keywords.

I have analysed this data using Spearman’s Rank Correlation Co-efficient, looking for relationships between individual factors and ranking in Google.

I have also studied several other areas of SEO. I have published some of these results (including domain name related factors and on page factors) although some results haven’t been made public yet and will be published over the coming weeks.

This is all part of a greater project to bring more science to SEO and make it a truly data driven industry.

There are inherent issues with correlations and they don’t prove anything per se, but as I have covered these issues before I won’t rehash old information, what I will suggest is – that if this is your first time on the site, please read this and this.

I would like to thank Link Research Tools for generously providing me with free access to their highly useful API from which all the below correlations are derived.

Please note: while domain level link metrics could be included in this post I have decided to deal with all link related factors in a separate post which will be published in the near future.

Data

Chart: Domain Authority SignalsDescription: Tags: Author:

If you wish to see the keyword by keyword correlations that resulted in the mean correlations reported above, feel free to download this spreadsheet with all the relevant data.

Definitions

Here’s some handy definitions in case you aren’t sure what some of the above factors are;

  • Domain age, is the time since the domain was first registered.
  • PageSpeed rating, is the Google measured score out of 100 on how well a page is performing with regards to several indicators of how quickly a page loads. The higher the score the faster the performance.
  • Days to domain expiry, is the time until the domain expires or needs to be re-registered.
  • Alexa and Compete rank, are both independent measures of how much traffic a site gets. The lower the score, the more traffic the site is supposedly getting.
  • Basic, intermediate and advanced reading levels, are Google measures, of what reading standard a given page is at.

 

Trust indicators

Chart: Domain Trust IndicatorsDescription: Tags: Author:

Google are always trying to figure out how trustworthy a site and its content is. Many theories have emerged as to what factors likely impact the trustworthiness of a whole site.

Domain age, is a classic and while I personally am sceptical about its use as a direct ranking factor, it does seem to have a strong relationship to ranking well in Google, with a near 0.2 correlation, which is highly significant.

How much of this can be written off due to the increased time available to established sites to build links and content and of course just the pure common sense – that a site running for a significant length of time will only have survived by providing for a user’s needs, is hard to determine. Domain age is a factor that’s impossible to manipulate, only worthy for consideration in the procurement of a new web property.

But by saying that its impossible to manipulate, I am then strengthening the case for Google’s use of the factor. So the truth is, its difficult to say whether its a factor or not. It does correlate well, so I would suggest that if you come across a situation where domain age is being considered give it some but not substantial weight in whatever decision you are making.

Homepage PageRank, and PageRank in general is one of the most hotly debated topics on the SEO circuit. We all know of the PageRank Toolbar’s problems and unrepresentative view of the real PageRank Google calculates and uses within their algorithm.

But at the same time the social data Google may pull from APIs may be more complete than the data I have access to and the internal Google link graph is even larger than the gigantic SEOMoz link graph yet we treat these representations of what Google sees as perfectly good.

My point is not that social data and link counts should be disregarded but that perhaps some, if not all of our suspicion at the value of PageRank as a metric is misplaced.

The importance of PageRank is backed up in its mighty performance in the correlation study, the highest correlated domain level authority signal at .244.

This and data on domain level link metrics which I will be publishing in the coming weeks has solidified my view that Google certainly weights and utilises domain link popularity in the ranking of content on a site.

Thus it is reasonable to recommend the already popular theory of building links to the homepage and domain as a whole.

Whether homepage link building warrants special treatment, is dubious and I would in general advise a strategy of building links to a domain as a whole, linking to the homepage only when it feels right and not because of any particular strategy.

Days to domain expiry, is an intriguing and interesting idea, that how long the webmaster registers a domain into the future is an indicator of the webmaster’s intent at creating a long-term user resource.

The marginal correlation at .089 probably suggests its minimal to lack of weight within the algorithm. In saying that, it is an easy and inexpensive factor to manipulate and even a marginal boost in search engine performance would be worth the puny risk.

There have been theories in the past which suggest its importance to newly registered sites, which again complies with basic common sense.

I can recommend registering your domain for 3+ years as a simple, one time, SEO strategy that may or may not impact ranking but certainly has no significant downside.

Site size

Chart: Site Size Correlation DataDescription: Tags: Author:

Alexa and Compete rank, I doubt whether the amount of traffic a site gets is a ranking factor. But its significant correlation may be indicative of a deeper positive correlation from Google towards larger sites.

Whether this is due to ranking factors in favour of larger sites, these sites performing better in non-discriminative factors or something else is worth pondering.

What I will say is that in general sites are large because they are useful to users and its a search engine’s job to try to find sites that are helpful and useful for users.

The same logic should track for the number of pages in Google’s index of a site,while this is highly unlikely to be a direct ranking factor it is perhaps an indicator of other factors actually implemented in the algorithm.

If the data is taken at face value, the then it would appear somewhat surprising that larger sites are performing worse, although the reliability of Google’s provision of this data appears to have impacted results.

I would like to test this factor and other similar indicators further before drawing a definite conclusion.

Geographic targeting

Chart: IP Location of Web ServerDescription: Tags:

The near random correlations for the geographic location of host servers is not surprising and in fact not very interesting at all.

I tested it purely to check whether there was any significant correlation but I didn’t expect there to be as  I conducted my searches from which these correlations are drawn, on Google.com.

The theory of geographic targeting is largely protested to be in use in non USA countries. In the future I hope to conduct studies on non-US versions of Google and to recheck this factor, but for the meantime the data is inconclusive and the current theories within the industry on server location should be followed.

Reading Levels

Chart: Homepage (Google) Reading LevelsDescription: Tags:

While the data is somewhat flawed in that Link Research Tools didn’t return data on a significant number of domains for this factor and the fact that homepage reading levels may not be the same as page level reading levels, the idea and the testing of such a factor is very interesting.

It is something that I believe Google to be using as a factor in the personalisation of search results. For example if they have figure out you are an 8 year old, then maybe you don’t want Shakespeare or research papers returned and you want content written in the language that you as an eight year old use. Not to mention the fact that not many eight year olds are searching for “Macbeth” or “quantum physics”.

A broad correlation study is not conducive to making a recommendation on what language you as a webmaster should use, but it is an interesting topic and something that you should consider when you are writing. Who are your audience and are you writing in their language?

Registrar

Chart: Domain RegistrarsDescription: Tags:

This was a rather cheeky test, and was never likely to reveal a ranking factor, more likely to represent the success achieved by sites registered through the above registrars.

I wasn’t surprised to see GoDaddy with the worst correlation as its add-on products and the clientèle don’t quite indicate quality or high editorial standards, not that many registrars do.

Once you understand and are disciplined with your implementation of SEO and general website ownership standards and strategies then the registrar you choose shouldn’t impact your ranking. But if you are new to the game or likely lead astray, then a registrar and host that promotes these standards may prove a more fruitful path.

Miscellaneous

Chart: Other Domain Authority SignalsDescription: Tags: Author:

The PageSpeed ranking is important, it suggests that if a site follows good principals with regard to the loading of content it will be rewarded with higher rankings. Tests on a page by page basis would be even more conclusive, but this reasonably high correlation for homepage level PageSpeed vindicates some of the excitement generated by Google announcing it used site loading speed in rankings.

The incredibly large correlation for both total and nofollowed external links on the homepage of a site is puzzling to say the least, although the internal data seems more explainable.

While I have some ideas on what may be causing such large correlations, primarily surrounding the type of site that would link to another website from its homepage, I have no real explanation. If you have an idea, guess or have experienced this in the field then please leave a comment below the post.

Social metrics

Chart: Homepage Level Social Media MetricsDescription: Tags:

Wow! I saved the best till last.

Some super interesting social media correlations, with the general theme being that social media is really important.

The fact that Facebook and Google + links to the homepage of a site are the lowest correlated of the bunch is rather strange. The Facebook data could be explained by a possible block on Google accessing FB data. But Google Plus?

Perhaps this indicates that homepage social media shares are not used as a ranking factor but that the other social networks have such a strong user base, that recommend quality content that these social media shares actually represent a measure of the quality of the site as a whole, hence explaining the high correlation.

Also the fact that Google + has a relatively small user base, may mean that its disruptive influence on other factors such as links arising from the additional traffic sent to the site by high levels of sharing of the site on Google + is minimised.

Another explanation is that Google is using Digg, Reddit and StumbleUpon data more than we know about and we should focus more effort on these social networks and Twitter.

But again I’m not certain what these correlations mean, if you have any ideas on these correlations or you have seen Reddit, Digg or StumbleUpon marketing result in increases rankings for your site then please leave a comment below.

Further study of these factors on a page level basis would tell us more about these speculations.

Summary

The correlations for domain level authority signals are comparatively higher than those seen by on page factors.

Domain level factors are ideal starting points for an SEO and often provide a one time, easy change that could, based on the above results, have a substantial impact on ranking.

Even if you disregard the individual factors above as ranking signals, it would still be more than fair to conclude that domain level SEO is very powerful and you should be constantly trying to improve the domain, through site-wide enhancements.

Some of the results, in particular the social and homepage links are somewhat puzzling and I am looking forward to hearing what people think are the likely causes of such strong correlations.

I will be publishing the link related domain authority factors in the coming weeks, so stay tuned.