Ranking signal studies and anecdotal feedback point toward the growing importance of user signals in search results. Historically, the link graph has been the primary mechanism for Google and other search engines to determine what content is best and most worthy of returning to users. However, the link graph does heavily favor desktop experiences, as a lot fewer people link to mobile sites.
With more people browsing on mobile devices and quality mobile listings growing in importance, Google has to reduce its dependency on the link graph. If the mobile webpage is not as strong as the desktop version it is linked to, clearly, the link-based method of assessing quality is not strong enough. The application of machine learning to ranking signals will accelerate progress, so it is only logical that user signals will be weighted more heavily as time goes on.
The message to marketers, therefore, is clear: Improve your user experience, and reap the rewards of improved positioning and more traffic from organic listings.
Unfortunately, the manner in which marketers measure user behavioral metrics, which are indicative of user signals, remains primitive — and in some instances, even detrimental to performance.
There is an assertion by many that low bounce rate and high time on site are indicators of successfully performing content. In some instances, this will be true; however, in many others, it will be a false flag. At worst, these metrics can even be indicators of poorly performing content. Here are some common misconceptions:
Bounce rate is often hailed as the king of behavioral metrics. A common recommendation is to identify pages with high bounce rates and lengthen the content to make it more comprehensive.
However, a high bounce rate can actually be indicative of strongly performing content. If the webpage serves the information need of the user perfectly, there may be no reason to have another interaction with the website. For instance, if a user is trying to find the address for a local branch or a particular recipe, a high bounce rate may be a measurement of success.
A common recommendation in Panda diagnosis audits is to reduce bounce rates across the site. Unless one is aware of the purpose of the content and the desired next action from the user, it is possible that this recommendation may even have negative implications for a Panda recovery.
Similar to bounce rate, average time on site can be misleading. It is common for marketers to optimize toward increasing time on site. The logic here is that if a user is spending a lot of time on the site, they are spending more time engaging with the brand, which signals to search engines that the content is high-quality.
Unfortunately, this is not always the case. The user should be able to retrieve the information they need as quickly as possible. The time it takes a user to get the information they are looking for on a webpage seems to be a quality signal for Google, as it is featured in the mobile section of their Search Quality Rating Guidelines [PDF]:
Mobile smartphones should make tasks easy, even for mobile users with a small screen device (i.e., size of smartphone, not a tablet). Users want results right away, at that moment, and may not be able to spend a lot of time to find what they are looking for.
It makes sense that a low time on site could actually be an indicator of content quality — otherwise, making critical information on a webpage difficult to find (thus lengthening average time on site) would signal a positive experience to search engines.
Moving into the publishing space can be a successful strategy for some brands; however, many have unrealistic expectations of how much their consumers want to interact with them. Brands should not expect that a consumer is going to enter the site via a piece of content and hold enough interest or need to visit multiple pages. This is unlikely.
Again, understanding the purpose of the content and having realistic expectations around this metric will only assist in decision-making. An article about how a no-claims bonus works for home insurance has a much higher propensity to develop into a second page view versus a contact details page for an insurer.
These misconceptions demonstrate the disconnect between a large proportion of SEO strategies and what the consumer actually needs. Having a “one size fits all” approach to your SEO content marketing measurement framework is likely to result in some poor decisions being made about optimization.
Applying effective measurement frameworks to your content marketing efforts will generate better goals, and therefore, better optimization decisions. To get started:
What these misconceptions do demonstrate is the incredible challenge for search engines in leveraging user signals as a ranking signal. Search engines need to qualify whether a high bounce rate was a consequence of the user receiving the information they need or the search listing not being relevant to their query.
Search sequence (analyzing the subsequent search queries by the user as a quality signal for content) is a more sophisticated user signal for search engines to use; however, it is significantly more difficult to measure and evaluate. As search engines become more sophisticated and the devices used by consumers more fragmented, the only way to future-proof your SEO content marketing efforts is to have a consumer-centric approach.
In other words, creating content with the informational needs of the user in mind is most likely to deliver success.
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