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How To Optimize Your Content for Google’s Search Generative Experience

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How To Optimize Your Content for Google’s Search Generative Experience

Google’s ready to repackage the search experience to better deliver what searchers seek.

Its testing of Search Generative Experience (SGE) and other AI advancements reflects a strategic shift to empower AI interaction through natural queries. With SGE, searchers can see topic summaries and engage in dynamic conversational modes.

SGEs are meticulously designed to reward content that underscores Google’s EEAT principles – experience, expertise, authoritativeness, and trustworthiness. The system also prioritizes content rich in experiential depth and authoritative endorsements.

@Google is repackaging search results again with Search Generative Experience and generative #AI, says @JimYu via @CMIContent. #SEO Click To Tweet

Google provides users with short summaries or brief answers that are especially helpful for understanding complex topics and resemble the short information boxes at the top of search results.

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Additionally, it offers a way to explore more details by clicking links to the original sources. SGEs are powered by Google’s Large Language Model (LLM), its general-purpose model PaLM 2, and Multitask Unified Model (MUM).

Each SERP will be different, and SGEs are in an experimental phase. Content creators and marketers must be equipped and willing to experiment, test, measure results, and formulate a strategy for SGEs.

In this search for a “good bike for a five-mile commute with hills,” the AI-generated text highlights the aspects to consider when choosing a commuter bike and concludes an e-bike is best for hilly communities. Then, it lists the best e-bikes to consider. All that content appears before any organic or paid search listings.

Of course, any shift in searcher experience and the layout of Google’s search engine results pages calls for a shift in SEO strategy to seize new opportunities to rank and engage.

How to make your content part of SGEs

Though too early to gauge the full impact of this conversational AI approach, I expect the traffic effect will be similar to earlier zero-click results because many searchers will get the answer they need without going to another site. In that case, top-level traffic would decline, but conversion rates might increase because people who click to visit the sites are more interested.

Expect @Google’s new Search Generative Experience to cut down top-level traffic but boost conversion rates of site visitors from search, says @JimYu via @CMIContent. #SEO Click To Tweet

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To make the most of Google’s Search Generative Experience, optimize for these four types of content.

1. Images and videos

Visual content often wins prominent positions in organic search results and SGEs. Optimize your image and video search strategy for the following:

Speak to searcher intent across conversational queries

  • Use up-to-date keyword research.
  • Break long, complex videos into snackable clips that answer a single question or explain one idea.
  • Use professional quality, original images to clearly convey one point, product, or concept and stand out in competitive multimedia search results.

Review the site’s schema markup and structured data

  • Use structured data and schema markup to help search engines more easily understand video and image content.
  • Add descriptions, file names, and alt text.
  • Add images and video to your sitemap to ensure crawlers notice all your content.

Improve the visitor’s experience

  • Size images appropriately, compress file sizes, and optimize for the web. A content delivery network can help accomplish these steps on an enterprise scale.
  • Make images and the website responsive and mobile-friendly.
  • Use your target keywords naturally in the image, video title, alt text, captions, or descriptions.

2. Blogs and articles

If you refined your blog content based on Google Search’s helpful content system, you have a head start on building a strategy for Search Generative Experience. Google prioritizes useful, high-quality content and increasingly bumps out thin, generic content that doesn’t seem written by humans for humans.

With SGEs, think about the natural flow of conversation between the searcher and Google’s AI. How can you better meet searchers’ needs and make it clear to Google that your blog or article is the best choice for relevant queries?

Craft #content that thinks about the natural flow of conversation between the searcher and @Google’s generative #AI, says @JimYu via @CMIContent. #SEO Click To Tweet

Consider the following:

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Pay attention to blog/article structure

  • Make use of subheadings to break up blocks of text, highlight important questions and information, and help readers skim through the information.
  • Ensure the content in each section delivers on the promise of the subheading.
  • Audit your content library to identify good candidates for updating and optimizing for SGEs. Look for opportunities to add structure and more clearly highlight questions and answers in your existing posts.

Use natural language

  • Understand your audience’s needs, questions, and preferences, and address them in a conversational tone. Use language that resonates with your readers and makes them feel like you’re having a one-on-one conversation.
  • Incorporate longtail keywords naturally into your content to ensure they flow seamlessly within the context.
  • Always write for humans first and optimize for search second.

Schema

Schema.org provides the schema for content types, such as articles, recipes, events, reviews, and more. Carefully review your content to identify the key elements to highlight, such as article title, author, date, images, and any relevant details. Then, choose the corresponding schema types that align with your content.

While manually adding schema markup to HTML code is an option, structured data markup tools can simplify the process and help ensure accuracy.

Schema has become vital with the introduction of generative AI and Google’s Search Generative  Experience. Across all industry categories at BrightEdge, we have seen a four times greater presence of schema tags this year in top-ranking positions than in 2022. As marketers plan for the early holiday season in e-commerce, a big focus exists on images and product schema – a relationship trend we see in general as brands prepare for Search Generative Experience. They also ensure to tag essential organization and company information, such as locations, social media accounts, and third-party reviews.

Use Google’s Rich Results Test and Schema Markup Validator to see which content schema may trigger rich results.

3. Google Business Profile content

The shift to Search Generative Experience is designed in part to help searchers find accurate, helpful local business information. To that end, Google began sourcing reviews and photos from Google Business Profiles in June. This ties your local SEO strategy more closely with the organic strategy because the information in the business profiles presents an opportunity to appear higher up and more often in conversational query results.

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How can you use this to your advantage? Do the following:

Add more high-quality photos and videos

  • Bring in a professional photographer to refresh your photos and make sure they’re optimized with descriptive file names.
  • Add photos and video of the company’s interior and exterior, products/services, employees, events, and more on a regular cadence so Google recognizes the profile contains new content.
  • Create a process for removing outdated photos and videos so the body of content stays relevant and high in quality.

Improve review management

  • Respond promptly to all local reviews, positive and negative alike.
  • Use email or SMS to follow up after purchases and in-store visits to triage negative experiences and encourage reviews. Ask questions in post-transaction surveys to encourage more descriptive and keyword-rich responses.
  • Ensure the accuracy of the business name, address, and phone number.
  • Be aware that Google may change the contact information on business profiles based on user suggestions, other results on the web, information provided by data aggregators, and more. Use software to monitor and prevent poor experiences caused by outdated business data.

4. Messaging and chatbot content

You might wonder what chatbots have to do with ranking in Search Generative Experience. After all, customer chats aren’t indexed in Google search results. However, existing chatbots and messaging content can have a greater impact in an SGE world, including:

Examine chatbot insights

As people engage your chatbot, they’re directed by the AI technology to your content resources to answer questions and find more information:

  • What questions are people asking your chatbots most often?
  • What keywords are people using in chatbot interactions?
  • How can you incorporate those opportunities into your content?

Review Google Messaging responses

Google allows businesses to set autoresponders for frequently asked questions submitted via Google Business Profile Messaging.

  • Evaluate the questions asked because they may also come up in conversational searches. Do you have accurate, up-to-date content to answer these questions, or is it time to refresh?
  • Evaluate page performance on the URLs shared to answer the FAQs and instant messages. Which pages have resonated and resulted in conversions? How can you better optimize these pages to convert?

Expand your educational content library

  • Look for opportunities to repurpose text content into video or imagery in your knowledge base to populate chatbot and messaging answers.
  • In addition to keyword research, explore the live SERPs to see which types of content Google may prefer for specific queries. Do you have content to appear there? If not, here’s your opportunity.

Make a great experience

Search is becoming more of a conversation than a transaction, expanding potential interaction points through the audience journey. As Google Search increases the role of AI, and in particular generative AI, to deliver better results, marketers should assess the new opportunities. Then you can plan and execute a strategic content strategy that meets the evolving searcher’s needs and expectations.

Want more content marketing tips, insights, and examples? Subscribe to workday or weekly emails from CMI.

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Cover image by Joseph Kalinowski/Content Marketing Institute



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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.”

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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.”

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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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