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How to Optimize for Google’s Featured Snippets to Build More Traffic

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How to Optimize for Google's Featured Snippets to Build More Traffic

The author’s views are entirely his or her own (excluding the unlikely event of hypnosis) and may not always reflect the views of Moz.

Google’s featured snippets started as an experiment almost a decade ago.

They have since become an integral part of Google’s SERPs, showing up for lots of queries.

In fact, featured snippets are now considered organic position #1, so it is part of any SEO strategy.

What are featured snippets?

Featured snippets are selected search results that are featured on top of Google’s organic results below the ads in a box.

Featured snippets aim at answering the user’s question right away (hence their other well-known name, “answer boxes”).

The recent studies reveal that featured snippets have an average 35% click-through rate.

Being featured means being on top of everything (except for ads), in the most prominent spot:

Types of featured snippets

There are three major types of featured snippets:

  • Paragraph (an answer is given in text).

  • List (an answer is given in a form of a list)

  • Table (an answer is given in a table)

Each type can also include an image, and that image may come from a third-party page that is not featured. There may be 2 images included inside the featured box:

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An older study from STAT: the most popular featured snippet is “paragraph” type.

Featured snippets or answer boxes?

The terminology may still be pretty loose here. Many people (including myself) are inclined to refer to featured snippets as “answer boxes,” obviously because there’s an answer presented in a box.

While there’s nothing wrong with this terminology, it creates a certain confusion because Google often gives a “quick answer” (a definition, an estimate, etc.) on top without linking to the source:

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To avoid confusion, let’s stick to the “featured snippet” term whenever there’s a URL featured in the box, because these present an extra exposure to the linked site (hence they’re important for content publishers):

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Do I have a chance to get featured?

Yes.

According to another older research by Ahrefs, about 100% of featured pages already rank in top 10 of Google. So if you are already ranking in top 10 for related search queries, you have very good chances to get featured.

Featured snippets appear and disappear for the same queries but you have higher chances to get featured if there’s already a featured snippet showing up for your target query (i.e. Google has already identified search intent for your query as informational).

Obviously, based on the purpose of the search section (i.e. to give a quick answer), you have a higher chance of getting featured if you answer a lot of questions in your content.

Identify all kinds of opportunities to be featured

Start with good old keyword research

Multiple studies confirm that the majority of featured snippets are triggered by long-tail keywords. In fact, the more words that are typed into a search box, the higher the probability there will be a featured snippet.

It’s always a good idea to start with researching your keywords. Moz’s Keyword Explorer is a good place to start.

When performing keyword research with featured snippets in mind, note that:

  • Start with question-type search queries (those containing question words, like “what,” “why,” “how,” etc.) because these are the easiest to identify, but don’t stop there…

  • Target informational intent, not just questions. While featured snippets aim at answering the user’s question immediately, question-type queries are not the only types that trigger those featured results. According to the aforementioned Ahrefs study, the vast majority of keywords that trigger featured snippets were long-tail queries with no question words in them.

It helps if you use a keyword research tool that shows immediately whether a query triggers featured results. SE Ranking offers a nice filter allowing you to see keywords that are currently triggering featured snippets:

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You can also run your competitor in Serpstat and then filter their best-performing queries by the presence of featured snippets.

This is a great overview of your future competition, enabling you to see your competitors’ strengths and weaknesses.

Browse Google for more questions

To further explore the topic, be sure to research popular niche questions.

Tools like Buzzsumo and Text Optimizer can give you a good insight into questions people tend to ask around your topic:

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Identify search queries where you already rank high

Your lowest-hanging fruit is to identify which phrases you already rank highly for. These will be the easiest to get featured for after you optimize for answer boxes (more on this below).

Google Search Console shows which search queries send you clicks. To find that report,

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Note that Search Console labels featured snippet positions as #1 (SEO used to call them position 0). So when you see #1 in Google Search Console, there’s nothing to do here. Focus on #2 and lower.

You can then use the filters to find some question-type queries among those:

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Go beyond traditional keyword research tools: Ask people

All the above methods (albeit great) tackle already discovered opportunities: those for which you or your competitors are already ranking high. But how about venturing beyond that? Ask your readers, customers, and followers how they search and which questions they ask.

MyBlogU: Ask people outside your immediate reach

Move away from your target audience and ask random people what questions they have on a specific topic and what would be their concerns. Looking out of the box can always give a fresh perspective.

MyBlogU (disclaimer: I am the founder) is a great way to do that. Just post a new project in the ” Brainstorm” section and ask members to contribute their thoughts.

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Seed Keywords: Ask your friends and followers

Seed Keywords is a simple tool that allows you to discover related keywords with help from your friends and followers. Simply create a search scenario, share it on social media, and ask your followers to type in the keywords they would use to solve it.

Try not to be too leading with your search scenario. Avoid guiding people to the search phrase you think they should be using.

Here’s an example of a scenario:

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And here are the suggestions from real people:

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Obviously, you can also create similar surveys with tools like WP Forms or Google Forms.

Organize questions and keywords

I use spreadsheets to organize questions and keyword phrases I discover (see more on this below). Some of these questions may become a whole piece of content, while others will be subsections of broader articles:

  • I don’t try to analyze search volume to decide whether any of those questions deserve to be covered in a separate article or a subsection. (Based on the Ahrefs research and my own observations, there is no direct correlation between the popularity of the term and whether it will trigger a featured snippet).

  • Instead, I use my best judgment (based on my niche knowledge and research) as to how much I will be able to tell to answer each particular question. If it’s a lot, I’ll probably turn it into a separate article and use keyword research to identify subsections of the future piece.

Optimizing for featured snippets

Start with on-page SEO

There is no magic button or special markup which will make sure your site gets featured. Of course, it’s a good idea to start with non-specific SEO best practices, simply because being featured is only possible when you rank high for the query.

Randy Milanovic did a good overview of tactics of making your content findable. Eric Brantner over at Coschedule has put together a very useful SEO checklist, and of course never forget to go through Moz’s SEO guide.

That being said, the best way to get featured is to provide a better answer. Here are a few actionable tips:

1. Aim at answering each question concisely

My own observation of answer boxes has led me to think that Google prefers to feature an answer which was given within one paragraph.

An older study by AJ Ghergich cites that the average length of a paragraph snippet is 45 words (the maximum is 97 words), so let it be your guideline as to how long each answer should be in order to get featured.

This doesn’t mean your articles need to be one paragraph long. On the contrary, these days Google seems to give preference to long-form content (also known as ” cornerstone content,” which is obviously a better way to describe it because it’s not just about length) that’s broken into logical subsections and features attention-grabbing images. 

Even if you don’t believe that cornerstone content receives any special treatment in SERPs, focusing on long articles will help you to cover more related questions within one piece (more on that below).

All you need to do is to adjust your blogging style just a bit:

  • Ask the question in your article (that may be a subheading)

  • Immediately follow the question with a one-paragraph answer

  • Elaborate further in the article

This tactic may also result in higher user retention because it makes any article better structured and thus a much easier read. To quote AJ Ghergich,

When you use data to fuel topic ideation, content creation becomes more about resources and less about brainstorming.

2. Be factual and organize well

Google loves numbers, steps and lists. We’ve seen this again and again: More often than not, answer boxes will list the actual ingredients, number of steps, time to cook, year and city of birth, etc.

Use Google’s guide on writing meta descriptions to get a good idea what kind of summaries and answers they are looking to generate snippets (including featured snippets).

Google loves well-structured, factual, and number-driven content.

There’s no specific markup to structure your content. Google seems to pick up <table>, <ol>, and <ul> well and doesn’t need any other pointers. Using H2 and H3 subheadings will make your content easier to understand for both Google and your readers.

3. Make sure one article answers many related questions

Google is very good at determining synonymic and closely related questions, so should be you. There’s no point in creating a separate page answering each specific question.

Creating one solid article addressing many related questions is a much smarter strategy if you aim at getting featured in answer boxes. This leads us to the next tactic:

4. Organize your questions properly

To combine many closely related questions in one article, you need to organize your queries properly. This will also help you structure your content well.

I have a multi-level keyword organization strategy that can be applied here as well:

For example:

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Serpstat helps me a lot when it comes to both discovering an article idea and then breaking it into subtopics. Check out its ” Questions” section. It will provide hundreds of questions containing your core term and then generate a tag cloud of other popular terms that come up in those questions:

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Clicking any word in the tag cloud will filter results down to those questions that only have that word in them. These are subsections for your article.

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Here’s another good guide on identifying your keyword modifiers (groups) and using those to structure your content.

Here’s a good example of how related questions can help you structure the article:

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5. Make sure to use eye-grabbing images

Paragraph featured snippets with images are ridiculously eye-catching, even more so than regular featured snippets. Honestly, I wasn’t able to identify how to add an image so that it’s featured. I tried naming it differently and I tried marking it as “featured” in the WordPress editor. Google seems to pick up a random image from the page without me being able to point it to a better version.

That being said, the only way to influence that is to make sure ALL your in-article images are eye-catching, branded, and annotated well, so that no matter which one Google ends up featuring, it will look nice. 

Optimizing and branding your images well is crucial for featured snippet optimization because images are often included in featured boxes, and in many cases those images come from different domains.

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Clicking images within featured images enlarges that image inviting the user to go to the linked site. In other words, this can be a traffic-building opportunity for non-featured sites.

Google is pulling these images from Google Images search results, so image optimization is important for driving traffic from featured snippets.

Also don’t forget to update and re-upload the images (on WordPress). WordPress adds dates to image URLs, so even if you update an article with newer information the images can be considered kind of old.

Monitor your progress

You are already monitoring your organic positions, and featured snippets are tracked as #1 position these days.

For your most important keywords, you may want to set up closer monitoring to be alerted when Google changes anything:

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How about structured markup?

Many people would suggest using Schema.org (simply because it’s been a “thing” to recommend adding schema for anything and everything) but the aforementioned Ahrefs study shows that there’s no correlation between featured results and structured markup.

Conclusion

It takes a lot of research and planning and you cannot be sure when you’ll see the results (especially if you don’t have too many top 10 rankings just yet) but think about this way: Being featured in Google search results is your incentive to work harder on your content. You’ll achieve other important goals on your way there:

  • You’ll discover hundreds of new content ideas (and thus will rank for a wider variety of various long-tail keywords)

  • You’ll learn to research each topic more thoroughly (and thus will build more incoming links because people tend to link to in-depth articles)

  • You’ll learn to structure your articles better (and thus achieve a lower bounce rate because it will be easier to read your articles)

Update: We have released a featured snippet optimization tool. With it, you can see exactly what your featured snippet opportunities are and what it may take to grab each of them (based on where the featured page ranks organically, where your page ranks and what type of featured snippet to optimize for.)

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

Introduction

With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to YouTube.com through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).

Conclusion

YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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