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Is Reading Level A Google Ranking Factor?



Is Reading Level A Google Ranking Factor?

Every SEO professional knows content is king. And not all content is created equal.

But does your content’s readability affect how Google ranks you in search results?

There are a lot of misconceptions about this. But what exactly is readability?

If you’ve done any content creation, there’s a good chance you’ve come across readability tools like the popular Yoast SEO WordPress plugin before. These valuable tools evaluate your copy and generate statistics such as passive voice, paragraph length, subheads, and transitions.

And included in this analysis is Flesch Reading Ease (FRE). FRE is a scale between one and 100, with 100 being the easiest to read and one being incomprehensibly dense.

For example, this piece scored 59 on the FRE scale, which puts it at a ninth-grade reading level. This score takes two variables into account: word length and sentence length. Generally, longer words and sentences will lower your FRE score.

While content that is easier to read will perform better with visitors, what about with search engines? How much do you need to focus on improving readability to secure a high ranking?

Let’s take a look.

And if you have questions about other ranking factors, download the Google Ranking Factors: Fact Or Fiction ebook for the whole story.

The Claim: Reading Level As A Ranking Factor

In 2010, Google added a short-lived “reading level” filter to its advanced search function. But the idea that readability affects search engine rankings has been around a lot longer than that.

And the rise of Google’s machine learning models BERT and MUM, which aim to understand language and content quality, seem to hint that it’s still important.

But what’s the truth? Should you be obsessed with turning all those red and orange circles on your reading analysis green? Will eliminating passive sentences and adjusting your vocabulary to a sixth-grade level send your page rocketing to the top of search engine results?

The Evidence Against Readability As A Ranking Factor

Despite claims to the contrary, reading level does not factor into your search ranking. Google’s Senior Webmaster Trends Analyst John Mueller confirmed this in a 2018 Google Webmaster Hangout:

“From an SEO point of view, it’s probably not something that you need to focus on, in the sense that, as far as I know, we don’t have kind of these basic algorithms that just count words and try to figure out what the reading level is based on these existing algorithms.

But it is something that you should figure out for your audience.”

FRE is a basic score with just two variables, so this makes sense.

To verify this, Portent ran a study analyzing the reading level of more than 750,000 pieces of content for 30,000 desktop search queries. This study found no correlation between Google search ranking and a page’s reading level.

So, SEO professionals can just disregard FRE, right?


Readability has an impact on user experiences, and that plays an ever-increasing role in SEO. If visitors to your website struggle to read and understand your content, they’re more likely to leave.

Challenging-to-read pieces are also much less likely to have incoming links directed to them, which is an essential ranking factor.

To quote John Mueller’s hangout again:

 “A common example is a medical site. You want to provide medical information for the general public because you know they’re worried about this. And all of your articles use these medical words that are 20 characters long. Technically, it’s all correct.

You could calculate the reading level score of that content. You come up with a number.

But it’s not a matter of Google using that reading level score and saying, this is good or bad. But rather, does it match what the people are searching for? And, if nobody’s searching for those long words, then nobody’s going to find your content. Or, if they do find your content, they’re going to be like… I don’t know what this means.”

So, it would seem that while your content’s reading level can have some effect on your ranking, it’s not a ranking factor.

Our Verdict: Reading Level Is Not A Ranking Factor

While not a confirmed ranking factor, the reading level is critical to content strategy. Every audience has different preferences regarding the complexity and reading level of content.

Write For Your Audience

The key to successful web content is usefulness. To rank highly, you must demonstrate that your webpage answers a search query better than anyone else.

And the way to do this is by understanding your audience.

For example, suppose you’re trying to promote a company that sells electron microscopes. In that case, you can probably get away with using a more sophisticated vocabulary than if you were selling mudflaps.

Just be careful to avoid talking down to your audience, which will alienate them as quickly as using $10,000 words.

Writing good content is a skill that every SEO professional would do well to cultivate. Adapting your writing to a specific reading level isn’t a ranking factor, but using words that don’t resonate with your audience will always be a problem.

Got other questions about what is and isn’t a ranking factor? Download the Google Ranking Factors: Fact Or Fiction ebook.

Featured Image: Paulo Bobita/Search Engine Journal

Ranking Factors: Fact Or Fiction? Let’s Bust Some Myths! [Ebook]

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Mozilla Acquires Pulse, A Hybrid-Workplace Collaboration Company



Mozilla, publishers of Firefox, acquired the team behind AI-based workplace collaboration product Pulse, announcing that they will work on Mozilla’s growing portfolio of products.

Pulse Team

The Pulse workplace collaboration product helped teams collaborate better by automatically managing their Slack presence, creating “focus times” that allow users to work without interruption, and display color-coded do no disturb notices when team members were in meetings.

Pulse was a product created specifically for today’s hybrid workplaces.

According to the archived Pulse page:

Adjusts with your work hours
Pulse puts an end to the ‘Always On’ culture by helping manage your team’s expectations around your availability — so teammates know when is best to connect with you and respect your boundaries.

Pulse uses AI to automatically display when you enter a focused state so your teammates know not to disturb.

You can also set calendar rules which change your status to show you’re focusing during blocked focus time or events marked as focus.”

The announcement did not hint at the future direction the new team will take within Mozilla.

However the fact that Pulse was a workplace collaboration product is notable.

It makes for interesting speculation that the acquisition may help Mozilla to begin introducing business-oriented products.

The quality that sets Mozilla apart from other companies is their commitment to creating products that don’t spy on or turn their users into a product to resell to marketers.

Free is increasingly common. Any product that can deliver quality at a free or near-free price and also respect user privacy would be increasing their value over more established products from companies like Google or Microsoft.

Google rapidly grew their email product by offering staggering amounts of storage space for free. Mozilla is doing with privacy what Google did with free, using it as a value-add that other companies do not offer.

And that edge is what makes the Pulse acquisition interesting because their machine learning expertise can be used to build privacy-forward consumer (and maybe business) products.

Ethical Machine Learning

The Pulse service used machine learning to help learn a user’s work patterns but in a way that respected their privacy, what Mozilla referred to as “applied ethical machine learning.”

According to Mozilla:

“Machine learning (ML) has become a powerful driver of product experience. At its best, it helps all of us to have better, richer experiences across the web.

Building ML models to drive these experiences requires data on people’s preferences, behaviors, and actions online, and that’s why Mozilla has taken a very cautious approach in applying ML in our own product experiences.

It is possible to build machine learning models that act in service of the people on the internet, transparently, respectful of privacy, and built from the start with a focus on equity and inclusion.”

First Project Announced

The first project the team will work on is improving Mozilla’s social sharing app called, Pocket.

Pocket is an app for saving content as well as sharing it with others. The app is available on a mobile device or desktop.

The author of the Mozilla announcement is Chief Product Officer, Steve Teixeira. He was hired by Mozilla in August 2022. Steve formerly worked at Twitter as Vice President of Product for their Machine Learning and Data platforms, and before that led the infrastructure Product Management, Design and Research team at Facebook.

Mozilla Chief Product Officer, Steve Teixeira, wrote:

“I’m particularly excited to enhance our machine learning capabilities, including personalization, in Pocket, a fantastic product that has only just scratched the surface of its ultimate potential.”

Mozilla offered no hint of future products beyond working on Pocket. They only published that they are looking forward to adding the Pulse team’s expertise to their growing suite of products.

Teixeira wrote:

“We are energized by the chance to work together, and I can’t wait to see what we build.”

It will be very interesting to see what Mozilla comes up with with the team acquired with Pulse.

Read the official announcement:

Pulse Joins the Mozilla Family to Help Develop a New Approach to Machine Learning

Featured image by Shutterstock/Kateryna Onyshchuk

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