Searchmetrics Ranking Factors: Rethinking Search Results Based on Google’s Deep Learning and Content Relevance

Submitted by RealWire on Tue, 12/13/2016 - 12:25
Ranking Factors Algorithm

Searchmetrics' annual study of top Google ranking factors undergoes radical format shift to match industry-specific needs and results

SAN MATEO, Calif., December 13, 2016 - Today's search results are shifting dramatically to match answers to the perceived intent of a search, as Google and other search engines increasingly employ deep learning techniques to understand the motivation behind a query, according to key findings in a new Searchmetrics study.

Findings from the latest Searchmetrics Ranking Factors study, "Rebooting for Relevance," suggest marketers face new challenges as Google deemphasizes traditional ranking factors such as collecting more backlinks and employing enough focus keywords in text. As technical SEO factors become table stakes in online content strategies, marketers in various industries will be forced to adopt new techniques to succeed," said Marcus Tober, Searchmetrics founder and CTO.

"Google revealed last year that it is turning to sophisticated AI and machine-learning techniques such as RankBrain to help it better understand intent behind the words searchers enter, and to make its results more relevant," Tober says. "User signals such as how often certain results are clicked and how long people spend on a page help the search engine get a sense of how well searchers' questions are answered. That allows it to continually refine and improve relevance."

The findings come from Searchmetrics' annual study of Google ranking factors, which analysed the top 20 search results for 10,000 keywords on Google.com. The aim of the analysis (carried out every year since 2012) is to identify the key factors that high ranking web pages have in common, providing generalized insights and benchmarks to help marketers, SEO professionals and webmasters.

"The most relevant content ultimately ranks by trying to match user intent - whether a searcher is looking to answer a question quickly, shopping or researching," Tober says.

"Someone who types 'who won Superbowl 50?' wants a single piece of information, while a query like 'halloween costume ideas' is most likely to best feature a series of images," Tober explains. "A query on 'how to tie a Windsor knot' might be best served with video content. Our research suggests Google is getting better at interpreting user intent to show the most relevant content."

Here are five indications from this year's study that suggest Google is getting better at showing the most relevant results:

1.High ranking pages are significantly more relevant than those that appear lower

Higher ranking search results are significantly more relevant to the search query than those lower down, according to the study, an indication that Google recognises when content is more relevant, and then gives it a rankings boost. It's also clear it is not simply based on a crude analysis of the number of times web pages mention keywords that match those entered in the search box.

In this year's study, Searchmetrics has used Big Data techniques to calculate a Content Relevance score[1], a new factor that assesses the semantic relationship between the words entered in search queries and the content shown in results; in effect, it measures how closely they are related. To make Content Relevance more meaningful, its calculation actually excludes instances of simple keyword matches between search queries and search results.

In general the Content Relevance scores of results positioned near the top are higher, suggesting that Google knows when content is more relevant and then places it more prominently. This rule does not apply to results found in positions 1 and 2, which tend to be reserved for top brand websites - presumably because Google considers content from more recognisable and trusted brands will better serve searchers' needs than non-brand pages that might have slightly more relevant content. Results with the highest Content Relevance scores appear in results found in positions 3 to 6.

2. Word count is increasing on pages that rank higher, while keyword mentions fall

The number of words on higher ranked pages has been increasing for several years now, and this trend is continuing. According to Searchmetrics, this is because top performing results are more detailed, more holistic (cover more of the important aspects of a topic) and are hence better able to answer search queries.

But interestingly, even as text grows longer, the number of keywords (words that match the search query) on higher ranked pages is not increasing. This is because Google is no longer just trying to reward pages that use more matching keywords with higher rankings; it is trying to interpret the search intention and boosting the content that is most relevant to the query.

In fact, the top 20 results include 20% fewer matching keywords (on average) in the copy than in 2015. Also in 2016, just 53% of the top 20 results have the keyword in the title (compared with 75% in 2015). Less than 40% now have the matching keyword in H1 title tag (usually used in the HTML of web pages to tell search engines what the page is about).

On average, pages appearing in desktop results are a third longer than those appearing in mobile search results.

3. User signals suggest Google increasingly guides searchers to exactly the right result

If Google was presenting precisely the right results to answer searchers' queries, then more of them would visit those pages, take in what is there and leave without having to look elsewhere (having found exactly want they were looking for).

That is just what seems to be happening. Searchmetrics' analysis of user signals indicates that bounce rates (when a searcher visits a page and leaves without clicking more pages on the same site) have risen for all positions in the top 20 search results, and for position 1 have gone up to 46% (from 37% in 2014). This is not because more people are bouncing away from pages immediately - having found that the content does not answer their question. Because time-on-site has also increased significantly over previous years, with people spending around 3 minutes 10 seconds on average when they visit pages listed in the top 20 results.

4. Backlinks: The rise of mobile search is making them less important

The number of backlinks coming into a page from other sites has always been an important common factor among high ranking pages. It still has a strong correlation with pages that rank well. However, it is on a downward trend as other factors such as those related to the content on the page become more important.

As well as the growing importance of content related factors, backlinks are becoming less important because of the rise of mobile search queries: pages viewed on mobile devices are often 'liked' or shared but seldom actively linked to. 

5. Google shows longer URLs to answer search queries, not just optimised short-URL home and landing pages

Until now, marketers and SEO professionals have been able to use optimization techniques to help their site's homepage or favored landing pages rank higher. But the study shows that the URL addresses for pages that feature in the top 20 search results are around 15% longer on average than in 2015. Searchmetrics' hypothesis is that instead of the highly optimised home and landing pages that marketers might prefer to appear in searches (and which tend to have short, tidy URLs), Google is better able to identify and display the precise pages that answer the search intention; these pages are more likely to have longer URLs because they possibly lie buried deeper within websites.

Other important findings include:

  • Technical factors such as loading time, file size, page architecture and mobile friendliness are a prerequisite for good rankings, as these factors help to make web pages easily accessible and easy to consume for both humans and search engines. They lay the foundation for breaking into the top 20 search results with the quality and relevance of the content enabling further rankings.

    There are significant differences between high ranking content on desktop devices and that which appears on mobile devices. For example, high ranking mobile results tend to have faster page load speeds, smaller file sizes, shorter wordcounts and fewer interactive elements such as menus and buttons.

For marketers and SEO professionals the advice from the study is clear, Tober says:
"Since Google is becoming much more sophisticated about how it interprets search intent and relevance, you also need to work harder and be smarter at understanding and delivering on these areas in content you put on your websites. You need to use data-driven insights to analyze exactly what searchers are looking for when they type specific queries in the search box, and make sure your content answers all their questions clearly and comprehensively in the most straightforward way - and you need to do it better that your competitors."

Google's application of machine learning to evaluate search queries and web content means that the factors it uses to determine search rankings are constantly changing. They are becoming fluid and vary according the context of the search (is it a travel search? An online shopping search? etc.), and according to the intention behind each individual query. Because of this, Searchmetrics will in future no longer be conducting a single generalized universally applicable ranking factors study. Instead, in the coming months, it will be publishing a series of industry-specific ranking factors studies focused on verticals such as ecommerce, travel, finance and more. 

To download the new Searchmetrics Ranking Factors whitepaper, please visit:
http://www.searchmetrics.com/knowledge-base/ranking-factors/

[1]Content Relevance is based on measurement methods that use linguistic corpora and the conceptualisation of semantic relationships between words as distances in the form of vectors. For the semantic evaluation of a text, this makes it possible to analyse the keyword and the content separately from one another. We can calculate a content relevance score for a complete text on a certain keyword or topic. The higher the relevance score, the more relevant the content of the analysed landing page for the given search query.