MARKETING
How To Adapt Your SEO and Content Strategies for SGE and AI Experiences
A massive change is coming to search.
As Google experiments with AI in its standard search results and its Search Generative Experience (SGE), marketers must understand how to adapt their content strategies for new AI-impacted search experiences.
Since 2023, Google has been prolific in its AI experimentation, changing the way content is represented in search results. Its content-led SGE recently moved out of its testing lab to show up in a small percentage of results in Google’s main search interface.
Brands that produce content experiences that align with new search behaviors and focus on conversion stand a better chance to survive the search change.
Google adds generative AI, first-person reviews, and anti-spam actions
Your news feed says all. Search and generative AI investments are everywhere. And it’s not just Google — new entrants, such as Perplexity AI and You.com, are on the search scene. Meanwhile, OpenAI is working on a search engine powered by Microsoft’s Bing.
Still, Google owns the biggest market share in search, so let’s focus on the ways AI is affecting Google SEO.
Reddit and new content sources
Google added new content sources to its traditional results and Search Generative Experience.
In traditional search results, adding more content sources helps fine-tune its AI technologies. The recent content licensing deal with Reddit is a prime example. You can already see its content appearing more often in traditional search results.
This screenshot shows the search engine results for “Is Volvo a good car?” A discussion from the Volvo subreddit appears as the third result on the page (or fourth if you count the people-also-ask module.)
Click to enlarge
SGE appearance
The image below shows the SGE for the Volvo query. The first paragraphs are an AI-generated summary drawing on ratings from RepairPal (after an alert explaining the experimental nature of the generative AI content.)
Below the SGE summary, a search box prompts the visitor to ask a follow-up question. After that element, the Reddit discussion on Volvo reliability appears.
Click to enlarge
Showing Reddit content in SERPs lets Google show more first-person reviews and opinions (the experience element of Google’s EEAT (experience, expertise, authoritativeness, and trustworthiness) for search ratings.
But how will Google distinguish between subjective, objective, and informative opinions? With Reddit content, which can include positive and negative opinions readily on display, brands will need to follow relevant discussions on Reddit.
Google goes after spam sites
You may have read about Google’s latest update, which aims to avoid sites with low-quality (often AI-generated) content and give helpful content more prominence in SERPs.
This hammers home the message to avoid relying on generative AI alone for content creation. Content needs a human touch to earn the experience, expertise, authoritativeness, and trustworthiness that Google and, more importantly, searchers want to see.
Expect more penalties from Google for content that’s just churned out from AI prompts.
SGE’s impact on brands
SGE is the rollout that will impact every industry and content marketer.
My company, BrightEdge, built a tool to detect how and where search engines experiment with AI and new content formats. The chart below shows an estimate of the percentage of queries by industry affected by SGE results once it’s fully rolled out.
Health care will see the biggest impact, with 76% of its searches affected by SGE. Finance will be the least affected, with only 17% of queries impacted by SGE. Here’s how SGE will affect other industries:
- E-commerce (49%)
- B2B technology (48%)
- Insurance (45%)
- Education (44%)
- Restaurants (36%)
- Entertainment (36%)
- Travel (30%)
Click to enlarge
Once SGE rolls out completely, it will likely impact over $40 billion per year in ad revenue on Google for marketers per BrightEdge estimates.
How to prepare for SGE and changing search behavior
Google has always shown relevant sources and articles so searchers can make informed decisions. With the generative AI changes, Google’s engine now asserts an opinion. This represents a fundamental shift in how a search engine responds to queries.
Imagine you search the web to learn more about a BMW model you’re interested in. Previously, a Google search would display results with links such as BMW’s official site, Top Gear, Consumer Reports, and Carfax. The searcher then could choose the resources to explore and form an opinion about the vehicle.
In the generative AI world, Google’s primary result might not be a direct link to BMW’s website. Instead, it could be AI-generated content that provides an evaluative perspective. The AI content might include important factors to consider when looking at a BMW, such as the potential for high maintenance expenses or issues with parts availability due to supply chain challenges. This AI-curated summary will be presented before the searcher can see the resources with links for further exploration.
This shift may lead to reduced but higher-quality traffic. Brands are likely to experience better conversion rates. The reason? Consumers are more likely to act because they’ve been influenced by prior engagements and information provided by Google.
Still, you’ll need to adapt to the new search environment. Here are some tips on how to prepare.
Focus on the search basics
Solidify your foundation of SEO and website fundamentals. The essential elements will gain more significance as time progresses.
Make sure your website is optimized for user-friendliness and complies with Google’s guidelines regarding Core Web Vitals, Helpful Content, and EEAT (experience, expertise, authoritativeness, trustworthiness).
You may also want to review these tips for optimizing content for SGE.
Deepen your understanding of new search behaviors
Use data to grasp user and conversational intent, especially since these factors influence the AI-generated search results. Identifying high-value searches is essential.
Make sure that your content responds to the specific query and addresses its broader context to attract results for long-tail keyword searches.
Content generated by AI draws from reliable and credible sources. Ensure your brand’s content is considered an authoritative source.
The growing prominence of trusted sources and an increase in consumer reviews signal a pivotal change: Brands are likely to have less control over the customer journey.
Align content with other marketing disciplines
Search engine results now encompass an array of media types and formats, including social media, reviews, and news sources. So, teams in marketing, content creation, digital strategies, brand management, design, social media, and public relations must align closely.
Strategies for an AI-first future
According to BrightEdge research, 98% of enterprise organizations say they’ll prioritize SEO in 2024. And 94% of organizations are looking to integrate SEO into all marketing (omnichannel) strategies.
Strategies for adapting your content approach to new search experiences will vary by industry. Here are a few examples.
E-commerce: Google commonly presents content for e-commerce queries via product viewers. SGE replaces these with better, more visual, and informational (combined) content.
Google has experimented with several formats, including a general shopping result that details what a searcher would expect to see in a universal listing. However, as SGE results have evolved, so have the ways a user can view products.
This image shows an example of SGE’s integrated product viewer carousel with grouping for apparel, which displays multiple apparel options in a single display.
These tips will help you prepare for the various viewer modules (see viewer examples).
- Optimize for trend relevance: Aligning category pages with current trends can increase your chance of being included in SGE dynamic displays.
- Incorporate product reviews: Showing product reviews on your site boosts credibility.
- Present clear pricing Information: Use schema markup to highlight pricing details.
Travel, restaurants, and local: Places have long been a key module for Google. Now, we’re seeing the places module showing up in about 45% of SGE queries. So, make sure to include location-based keywords.
You might also try these optimization suggestions:
- Monitor and respond to reviews.
- Tailor your local listings for location-specific queries.
- Keep an eye on how and where SGE displays local modules. SGE displays local results even in queries without location-specific terms.
Entertainment: SGE entertainment results are primarily informational. But more reviews (and warnings for age-appropriate content) are appearing in both traditional search and SGE.
Get ready to shift your SEO thinking
Whoever provides the best experience for their target consumers will win in the new AI search experiences. Focus on third-party content reviews, social, PR, and brand authority. Expect your competitive landscape to change with new entrants that might eat into your market share.
Be aware, ready, and prepared to optimize for multiple AI search experiences.
All tools mentioned in this article were suggested by the author. If you’d like to suggest a tool, share the article on social media with a comment.
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Cover image by Joseph Kalinowski/Content Marketing Institute
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
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!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
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.”