Categories
Google Algorithm

Google’s Core Web Vitals: A New Ranking Signal In May 2021

Imagine this: 

You walk into a toy shop to get a last-minute present for your kid’s birthday. But the shop opened late. When you finally got in, you found out that the items had no price tags. So you had to ask about each toy. Worse, your item of choice had a defect. The staff wasn’t helpful enough either. 

You walked out of the store not buying what you intended because of the poor experience. It left you stressed out and unhappy. 

It’s About Great User Experience on a Page 

If there is one thing that users want, that is an interruption-free, flawless experience while browsing web pages. Optimizing for this will help you succeed — whether you’re a business owner, SEO specialist, or marketer. 

Enter Core Web Vitals. 

Here, you’re going to learn what Core Web Vitals are and their impact on your website rankings. Let’s dive in.

What Are Core Web Vitals? An Overview

Google defines Core Web Vitals as a set of real-world, user-centered metrics that measure a user’s experience which includes:

  • Load time 
  • Interactivity
  • Visual stability 

In May 2020, Google announced that it will be introducing a new page experience signal that combines Core Web Vitals with its existing signals such as mobile-friendliness, safe browsing, HTTP-security, and intrusive interstitial ads guidelines. 

See the diagram below: 

Learn more about page experience in Google’s detailed guide for developers

Here’s a sneak peek of each Core Web Vital: 

1. Largest Contentful Paint (LCP) – Render time 

How long does it take for the main content on a page to render? In a nutshell, the LCP measures render speed. A page should render within 2.5 seconds for good user experience. 

2. First Input Delay (FID) – Interactivity

When you interact with a page, for example, click on a button, how long does it take to respond? FID measures how interactive or responsive your website is. Be sure to aim for a FID value of fewer than 100 milliseconds

3. Cumulative Layout Shift – Visual stability 

Does an element, a button, or link, for instance, shift its location as you click it or as the page renders? As a result, you end up clicking something else. This phenomenon describes layout instability. A good CLS score is less than 0.1.

💡Key takeaway: Core Web Vitals are not optional — they’re essential for maintaining a healthy website. It doesn’t matter what industry you’re in or what pages you have. LCP, FID, and CLS should be measured by ALL WEBSITE OWNERS on ALL PAGES. 

Now let’s explore each metric in detail: 

Largest Contentful Paint (LCP)

Largest Contentful Paint describes perceived load speed. It measures the point at which the largest image or block of text becomes visible to a user who is on desktop or mobile. 

Below is a demonstration of the LCP, from Google: 

Take note that the largest image or block of text may change as the page continues to load. 

Look at the example. The text “View stories” appears first, and is considered as the largest element. But then the news headline appears, which now becomes the largest element — followed by the image (since it is larger than the headline). 

As you can tell, users need to see the main content on a page. Which helps accomplish their goals. 

So, you’ll want to aim for an LCP within 2.5 seconds. If it’s beyond 2.5 seconds, it needs some improvement. More than 4 seconds means poor performance! ⚠️

From Google Developers

Fortunately, Google provides tools that will help you easily identify your LCP. 

PageSpeed Insights and Web.Dev are two that show your LCP score. You’ll also find a ton of information that will show you the improvements to be made. 

Here is an example of an actual LCP score from a website (mobile). It shows that the page needs improvement: 

The same website, now in desktop, shows this poor LCP score: 

You can also use the Google Search Console. The difference is that Search Console gives you a list of URLs with good or bad results — instead of you having to check one URL at a time. 

Google identifies these as the common causes of poor LCP:

  • Slow server response times
  • Render-blocking JavaScript and CSS
  • Slow resource load times
  • Client-side rendering

Check out this document to learn about each cause and how you can optimize LCP. 

First Input Delay (FID)

First Input Delay measures interaction on a page. These “interactions” include clicks, taps, and keypresses. (Note: Actions such as scrolling and zooming are irrelevant.)

For example, if a person clicks a buy button on your page, how long does it take for that button to respond to that click? A delayed response, beyond 100 ms, creates a bad user experience. 

From Google Developers

Heavy Javascript execution is often the cause of a poor FID score. Because while Javascript allows us to create a rich interface, it can lower the performance of pages with complex code. 

💡For your knowledge: Not all interactions are relevant to FID. Google considers scrolling and zooming irrelevant.  
FID is a field metric. Meaning, it can only be measured if you have actual users. At the same, keep in mind that not all visitors who land on your page interact with it and that not all interactions are relevant to FID, such as scrolling and zooming

Google recommends the following field tools for measuring FID:

An actual FID score using PageSpeed Insights. This indicates a good score. 

You can also use a lab tool called Lighthouse to run a performance audit. It measures Total Blocking Time (TBT), which if improved, can also improve FID. 

For detailed information on how to improve FID, read this guide

Cumulative Layout Shift (CLS) 

The Cumulative Layout Shift metric measures the unexpected movement of content on a page while it loads. (Think: Visual stability.)

Here’s a sample scenario: Imagine being on an order confirmation page. You’re about to click the back button because you’re not yet done with your orders. 

Wouldn’t it be frustrating if you ended up clicking the “place my order” button? 

This phenomenon called layout instability leads to a poor user experience since it prevents them from achieving their goal — whether that’s reading a piece of content, making a purchase, checking out another resource, etc. 

Therefore, it’s important to minimize CLS. Aim for a score of less than 0.1:

From Google Developers

Google identifies some culprits behind CLS such as ads, images, and widgets without specific dimensions. This is why your developer needs to set size attributes to images and videos to avoid layout shifts. 

Custom web fonts that cause Flash of invisible text (FOIT) and Flash of Unstyled Text (FOUT) also lead to layout shifts. 

There are lots of tools to diagnose CLS and these include PageSpeed Insights, Chrome UX Report (CrUX), Search Console, and Lighthouse. 

An actual CLS score using PageSpeed Insights. This indicates a good score. 

See this detailed document that Google put together on how to optimize CLS. 

Does the User’s Device Affect the Core Web Vitals?

The answer is yes. Devices that are fast and powerful (CPU/RAM) can cause field data to be better than lab data, even if the website itself is content-heavy or unoptimized. 

This means that heavy sites seem to “perform well” specifically for people who are using modern devices. 

Here’s an example: 

  • Website A is content-heavy and gets visited by an audience using powerful devices. 
  • Website B is optimized and gets visited by an audience using slow devices. 

So, on a lab test, website A will perform poorly. However, field data will show good results because the real users are not experiencing problems – thanks to their devices. Website B, on the other hand, will show the opposite for both field and lab data. 

For the best possible outcomes, use both lab and field data to measure your Core Web Vitals. 

Will the Core Web Vitals Affect Your Rankings?

In a nutshell, yes. This update is expected to become a ranking signal in May 2021. Google announced it in November 2020, giving website owners enough time to prepare.

Categories
Google Algorithm

Google RankBrain: How It Works and What You Can Do

Have you heard of Google RankBrain? 

It’s the third most important ranking signal. 

Google scientist Greg Corrado said this in a Bloomberg news story in October 2015. That was the first time RankBrain’s existence was confirmed. 

Greg Corrado, Google scientist talking about RankBrain on Bloomberg in 2015.

However, Google RankBrain isn’t really a “ranking signal” in the traditional sense. Once you understand it, you can approach your content the right way. 

Here’s what you need to know.  

What Is Google RankBrain?

Google RankBrain is a system that uses machine learning to find the most relevant pages for a search query. It has been cited as part of Google’s Hummingbird — a major algorithm change in 2013. 

Here’s how RankBrain works, in a nutshell:

1. It takes an unknown query.

2. Figures out the intent and topic behind that query.

3. It brings back the best possible results for that query.

Then, RankBrain looks at how users interact with those search results. 

Do people click? Or do they try other queries to find a result that satisfies their query? 

Data from users helps RankBrain improve and optimize search results over time. 

As you can see, it is in a constant learning process. With over 40,000 search queries happening every second, there’s a lot to learn from. 

This is especially true as voice search queries continue to increase. Voice queries tend to be different than written ones, which leaves a lot of room for interpretation. 

Also, RankBrain doesn’t only affect queries in the English language, as tweeted by Gary Illyes: 

Source: Twitter
💡Bottom line: RankBrain makes Google a better search engine by giving users what they want. 

Now that you have an idea of how RankBrain works, let’s consider the scenario below. 

RankBrain In Action

Imagine that you entered this search query into Google:

“Where should I eat?”

Me, looking for a restaurant.

RankBrain takes that query and figures out what you mean with that query. 

Do you need suggestions on the best restaurants worldwide? Within your country/state/city? Or are you simply looking for restaurants nearby? 

RankBrain obtains data from Google, analyzes it, and recommends pages based on various signals like past search queries, location, device, and content freshness. 

Let’s say that you weren’t satisfied with the results that Google provided. 

Instead of getting suggestions for nearby restaurants (which you expected), Google showed you roundup articles of the best restaurants worldwide. And some trivia quizzes too, which were irrelevant. 

So you changed your original search query into:

“Where should I eat near me?”  

Me, looking for a restaurant in a slightly clear way!

Boom. This time, you got the results you wanted. That small tweak in your query made the difference. 

RankBrain takes your behavior into account. Since you ignored the results during your initial search, it now understands that it has to do a better job at serving more relevant content in the future for your first query. 

You see, patterns in searchers’ behaviors help Google refine search results to satisfy users. If you entered the same query a few months from now, you might see different results! 

Here, we appreciate the machine learning aspect of RankBrain — the ability of an algorithm to teach itself from experience without being programmed. 

By using machine learning, Google can show users results from a query even when that query was never searched for before. Over time, results improve as RankBrain continues to learn from users. 

💡Interesting fact: In 2015, RankBrain was analyzed only on less than 15% of queries. The following year, it was already used in all queries. 

Pre-RankBrain Era

Back in the day, website owners could “manipulate” search results by stuffing a piece of content with keywords. This bad practice is called keyword stuffing. See this example: 

Example of keyword stuffing.

So if you typed a keyword into Google’s search bar back then, Google would simply show you pages that contained that exact keyword without trying to understand your real intent. This often led to irrelevant results. 

Now, RankBrain can show you pages that do not necessarily contain your keywords  — thanks to its ability to figure out your purpose behind a query.  

Here’s what Google said on Twitter:

Source: Twitter

One way RankBrain operates is by using word vectors. Here’s how it works, as described by Greg Corrado: 

“RankBrain uses artificial intelligence to embed vast amounts of written language into mathematical entities — called vectors — that the computer can understand. If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.”

For example, if you searched in Google “how to eat a date,” there would be a ton of pages about dates. A date could mean different things meeting socially, the number on a calendar, or a fruit. 

What RankBrain does is that it looks at other words on a page to see if they’re connected to your search query. So if it finds pages with words like fruit, raisin, fresh, dried, or dessert, RankBrain will most likely show those pages to you. 

How to Optimize for RankBrain

As a business owner, marketer, or SEO specialist, how can you create content that’s optimized for RankBrain? Here are some actionable steps to take: 

1. Ditch the one keyword, one page practice. 

Once upon a time, SEOs tried to rank different pages for similar keywords. 

Take, for example, a blog post that targeted the keyword “guitars” and another blog post that targeted “guitar music instrument.” Since these keywords have the same intent, they should be condensed into one article. 

So if you find two or more articles on the same topic on your website, it’s best to combine them into one solid in-depth content. By doing this, you’ll be able to target keyword variations and avoid keyword cannibalization. 

2. Before using a keyword, try to understand its intent. 

RankBrain’s role is to serve content to the right audience. So while you’re researching a keyword, ask: Does the intent behind this keyword meet my audience’s needs? 

Try to put yourself in your audience’s mind. For example, if they wanted to know about the best mirrorless cameras before deciding to buy, wouldn’t they type “best mirrorless camera” into Google’s search bar?

As you can see, organic search results showed product review roundup articles because RankBrain understands that you’re not looking to buy anything specific yet based on your query, making it almost impossible to rank a transactional (product) page for this keyword.  

3. Write content that sounds human.

Gary Illyes said this:

“Optimizing for RankBrain is actually super easy, and it is something we’ve probably been saying for fifteen years now, is – and the recommendation is – to write in natural language.  Try to write content that sounds human.  If you try to write like a machine then RankBrain will just get confused and probably just pushes you back.”

Bottom line? Write in a conversational tone. Like you talk. Keep in mind that most voice search queries use natural language. 

Gary gives practical advice on reading your articles out loud and asking people if they sound conversational: 

“….But if you have a content site, try to read out some of your articles or whatever you wrote, and ask people whether it sounds natural.  If it sounds conversational, if it sounds like natural language that we would use in your day to day life, then sure, you are optimized for RankBrain. If it doesn’t, then you are “un-optimized”.

💡My 2 cents for you: Don’t worry if your article sounds silly at first. You can fix it later on during the editing process.Write for your target audience, not for Search Engines.

4. Know that different queries demand different signals. 

Depending on the user’s query, RankBrain is going to consider certain signals to provide the best content. 

For example, someone searching for the “best movies in 2020” will likely see articles that have been written in the same year. Here, we can see that content freshness plays a big role. Meanwhile, someone searching for “diabetic ketoacidosis” will likely be shown in-depth guides. For this, content comprehensiveness matters. 

That having said, consider the signals that could matter for the search queries you’re trying to rank your content for. 

Final Thoughts 

It’s no secret that most people use Google. We do that because we expect to get the most relevant answers to our queries and RankBrain has made this possible. Knowing how RankBrain works will enable you to take your content creation efforts more seriously. Is your content useful for your audience? Is it relevant? Conversational? 


References used for this article:

1. Bloomberg news story –  https://www.bloomberg.com/news/articles/2015-10-26/google-turning-its-lucrative-web-search-over-to-ai-machines

2. Google RankBrain as part of Hummingbird – https://searchengineland.com/faq-all-about-the-new-google-rankbrain-algorithm-234440

3. Google search statistics – https://www.internetlivestats.com/google-search-statistics/

4. Gary Illyes’ tweet – https://twitter.com/methode/status/879988330074689536

5. Machine learning definition – https://martechtoday.com/how-machine-learning-works-150366

6. Keyword stuffing definition – https://support.google.com/webmasters/answer/66358?hl=en

7. Google SearchLiaison’s tweet – https://twitter.com/searchliaison/status/1108776357880725505

8. Gary Illyes’ RankBrain quote – http://www.thesempost.com/google-how-to-optimize-for-googles-rankbrain/