Links: Still a Powerful Ranking Factor?

The Stone Temple Consulting (STC) team published a new ranking study on July 20th. According to this study, links may be more important than studies have shown them to be in the past.

Previous studies by Searchmetrics and Moz have shown that links are important. However, the STC study says that statistically, they are more important than the previous studies have shown.

Here are some of the details of those two studies:

What Do the Searchmetrics and Moz Studies Show?

Both Searchmetrics and Moz have completed groundbreaking studies on various ranking factors. Each of these studies included links as one of the factors. You can view the studies here:

  • Searchmetrics Ranking Factors
  • Moz Correlation Factors

You can also view the basic data points on the following chart:

Each bar shows the level of correlation between the ranking factor and a higher ranking. In the Searchmetric and Moz studies, the correlation between the number of links was high. However, they were not significantly higher than other factors. STC asked, if the links are important, based on the fact that Google called them one of the two most important ranking factors, then why aren’t these showing in the form of higher numbers.

The key to understanding the Searchmetrics and Moz studies is knowing how evaluations are done. These studies evaluated each SERP on an individual basis. Then they took the mean of all of their results, which the STC refers to as the “Mean of the Individual Correlations”. Both of these studies only focused on commercial search terms.

So, while the approaches are valid, because of STC’s experience with the power of links in ranking, they decided to take a deeper look into the power of links. They took new approaches to expose the impact of links. Bottom line? STC believes the “Mean of Individual Correlations” approach does not provide a complete picture.

The Study Results

Based on consultations with experts Per Enge and Paul Berger, STC chose to use a different type of calculation, the Quadratic Mean. The reason for using this type of calculation is that it leverages the variables correlation’s square. In this calculation, the correlation value is R, and R-squared is used by the quadratic mean.

The R-squared value actually has some meaning in statistics. For example, if the R is 0.8, then R-squared is 0.64. That means you can say that about 64 percent of the variability in Y can be explained by X. According to Paul Berger, when explaining to Eric Enge, there is no meaningful sentence involved in the variable R correlation. However, R-squared gives you something meaningful to say about the relationship between the correlation.

Here is a visual representation of the calculation process:

In addition to using a different calculation method, STC also used various query types. They used commercial long tail terms, informational terms and commercial head terms. In fact, 2/3 of the queries were informational. This was one reason why the results of the STC study was somewhat different from Searchmetrics and Moz.

Our link correlation results were higher than the correlation scores of PA and DA as ranking factors. STC asked Rand Fishkin of Moz for a comment about the meaning of these results and here’s what he said.

According to Fishkin, Moz uses a different, broad corpus of keywords to generate the PA/DA algorithms. That’s why it makes sense that when using a different type of keyword query, there will be different levels of correlation. It’s interesting to note that raw link counts do better on these corpuses.

Fishkin hopes that one day, Moz will be able to offer various kinds of metrics and the correlation to a particular set of keywords. It would be awesome if you could see the correlation for thousands of keywords when you’re rank tracking.

It’s also important to note how high STC’s total link score correlation was when compared to Searchmetrics and Moz. The score showed above uses a different methodology. However, even when you use the same methodology, the Mean of Individual Correlation approach, you’d get higher results. Here are the head-to-head comparisons of all the link score calculations:

Aggregate Evaluation of Links as a Ranking Factor

STC believes that the Quadratic Mean and Mean of the Individual Correlations approaches are both valid. However, one of the limits of both approaches is that a small number of results that have a highly negative correlation can drop down the score significantly.

For that reason, STC chose to take other approaches to the analysis. The first of those approaches is to measure the links in an aggregated manner. To do this, they normalize the link’s quality. Then, they looked at the total for all the search results, by the ranking position. The equations for this looks like this:

The value of this approach smooths out the impact of the negative correlation in a different way. When you look at the correlation, here are the results you get:

STC took another look at this. In this view, STC continued to use the normalized links. However, they’re grouped together in ranking groups of 10. So, they sum up the total number of normalized links for the top 10, then did the same for ranking position 11 to 20, 21 to 30, etc.

Then they calculated the correlation to see how they look in terms of what it takes to rank for each of the 10 position blocks. These calculations will look like this:

This offers a bit more of a granular approach than just aggregating the SERP ranking position information. However, this approach is able to smooth out a few of the restrictions of the “Mean of Individual Correlations” approach. Here are the results STC attained by using this method:

As a result of this approach, STC was able to go from numbers in the 0.39 range to almost-perfect correlations. So, what do these numbers tell us? STC believes that this aggregated approach, when used to make these calculations will tell us that the links are much more important than what the “mean” based calculations would reveal.

Taking A Closer Look At The Facts

In order to gather accurate information, the STC team took a first-hand look at several hundred search results to determine which ones ranked well even when they lacked significant links. Three particular forms of results stood out:

  • In-Depth Articles
  • Diverse Queries
  • Local Results (not through Google Maps)

According to STC’s analytical work, these categories accounted for just six percent of overall results, indicating that linking might be more of a specialized tool than it once was. There’s more insight to uncover by looking at the calculations in more detail, though.

Google has always emphasized the importance of quality content, and links and content are always mentioned at the top of the search engine’s priorities for ranking. To build a (very) hypothetical example, you could imagine Google deriving an aggregate rank from multiplying a score for content by a score for links.

STC’s contention is that, in a simplified scenario like this, Google must weight their content score more heavily when compared to the link score. After all, the search engine’s stated goal has always been to deliver the most relevant and useful results. Content has a much greater influence on a page’s relevance than links do.

Take a look at the attached chart to see one possible way Google could set up the math between these two scores. The second example shown is going to end up with a better rank, even though its score for links is definitely poor. What would happen if the link score was limited to a simple 1-to-100 rating while content factors were considered exponentially? This would mean small reductions in relevance and quality would produce large drops in the score assigned for content. In a situation like this, simply building good links would not be able to compensate for weak content or low relevance.

Takeaway Lessons

Google is never going to declare its ranking algorithms perfect; they’ll always be evolving over time. Today we have to contend with a lot of different issues that can alter traffic coming from organic search results. Major factors include:

  • Losing SERP real estate to paid search
  • More slots being allocated to non-link-driven results, e.g. in-depth articles, diversity responses, and local web results
  • Pages offering fewer than 10 web results
  • The addition of multimedia content like images and videos to the results page

In the end, the clear conclusion is that there aren’t going to be 10 spots on the front page for non-link-driven results. That name might be deceptive; it’s likely that the importance of links for these results is de-emphasized, not tossed out entirely.

The underlying numbers from the STC study imply very strongly that links still matter, and our case study shows the same. Basically, links can be a deciding factor as long as you aren’t fighting quality or relevance problems.

In the end, closer analysis just serves to further justify our tried-and-true advice:

  • Always strive to provide great content and positive user experiences.
  • Take the initiative in marketing your site so that you get people both linking to and talking about you.


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