MARKETING
Don’t Miss the Big News Hidden in Google’s Cool AI Tools Announcements
Last week, Google gathered to announce all the things they’re developing.
Google’s reveals focused on its main product and revenue model – search and advertising. Not surprisingly, those two categories pique the interest of marketers everywhere. But we’ll get to that in a minute.
Among the more fun news comes an immersive view for routes in Google Maps for some cities, an AI-powered Magic Editor for photos, and an AI-driven Magic Compose tool to rewrite more positively, professionally, or Shakespearean-like text. (Google seems to equate AI and magic.)
Google shared news about Bard, its ChatGPT competitor. The waitlist is gone, and the tool operates in English, Japanese, and Korean. Plus, it can surface images in its responses, some of which may be integrated with Adobe’s AI art generator Firefly and possibly modified in Adobe tools.
Now, onto the biggest-but-less-noticed Google announcement.
CMI’s chief strategy advisor Robert Rose shares his thoughts in this week’s CMI News video. Watch it below, or keep reading for the highlights:
The biggest news for marketers
What marketers care about came as almost a throwaway line in all the cool new features: Google plans to change the presentation of search results. To no one’s surprise, the look will integrate artificial intelligence.
@Google plans to change the presentation of search results and integrate artificial intelligence, says @CMIContent via @Robert_Rose. Click To Tweet
Robert says the fascinating development portends interesting implications for marketers who care about the future of organic search.
In Google’s demonstration at the I/O Conference, someone “asks” the search engine: “What’s better for a family with kids under 3 and a dog, Bryce Canyon or Arches National Park?” Google Search returns a lengthy answer detailing the pros and cons of each.
“Now, search does the heavy lifting for you,” explains Cathy Edwards, vice president of Google Search, during the conference.
But does it? Does it really?
“If you read the response, it reads very much like what’s now beginning to become a classically formatted generative AI response,” Robert says.
Here’s how the result returned by the experimental generative AI:
Both Bryce Canyon and Arches National Parks are family-friendly. Although both parks prohibit dogs on unpaved trails, Bryce Canyon has two paved trails that allow dogs.
“Bryce Canyon has distinctive features like hoodoos, natural bridges, and waterfalls. At the visitor center’s interactive exhibits, children can learn about the geology, wildlife, and people of the area. You can bring your dog on the paved sections of both the Rim Trail and the Shared Use Path, both of which are also stroller-friendly.
“At Arches, children may enjoy the rock formations, and some say that Arches has more variety than Bryce Canyon. Pets aren’t allowed on any trails, though they are allowed at campgrounds, pullouts, roads, and parking lots.
“Both parks offer guided tours, ranger-led programs, picnic areas, and restrooms, and both parks require pets to be leashed.
Robert explains, “The answer is quite logical, well-constructed, has a lot of adjectives, and, ultimately, provides little value.”
Even @Google couldn’t return a valuable #AI-generated result to the searcher example it shared, says @CMIContent via @Robert_Rose. Click To Tweet
It pulls relevant but general features from both parks. It attempts to distinguish between the two by saying Bryce allows dogs on two paved trails. But a bit more digging would have led the searcher to discover both parks have the same policy – dogs are allowed on paved roads. Bryce just has a few paved roads that are part of some trails.
Though the result attempts to draw distinctions, a vague partial statement acts as the only real hint at the differences, “… some say the Arches has more variety than Bryce Canyon.”
But what that means isn’t terribly clear, and it wasn’t asked in the search question.
At the end of the text response, Google offers up three options to explore further:
- “Ask a follow up.”
- “How long to spend in Bryce Canyon with kids?”
- “How many days do you need in Arches National Park for kids?”
Those closing options could easily be turned into sponsored links to keep the Google gravy train rolling.
2 steps to sidestep deathly predictions
“I don’t mean to pick on Google. The tech just demonstrates what may be coming,” Robert says. “But I do want to pick on the knee-jerk reaction that search traffic will diminish, or this will kill publishers.”
You can expect search engines like Google, YouTube, Bing, Amazon, and many other verticalized products to eventually evolve like what Google demonstrated this past week.
So, Robert says, ask yourself how your brand will respond now and what it will do about it in the long term. He sees at least two safe bets to survive the future impact of AI on search results.
First, create content that not only attracts but retains an audience. Focus on more than getting people into your sphere of influence – your website, email, content hub, store, etc. Plan on how to keep people at your content by becoming a trusted, bookmarked source.
Second, invest in owned media by understanding how to create content in the context of questions asked. The expertise powering any AI search relies heavily on accessing owned media. It also uses a large language model (LLM) to learn that information.
“Look at your content through the lens of a searcher who wants to distinguish between the most important aspects of their question,” Robert says.
Understand how to create #content that answers questions asked by searchers who want to distinguish differences, says @Robert_Rose via @CMIContent. Click To Tweet
Go back to Google’s example of the two U.S. parks. The searcher wanted to know which park is better for a family with a dog. When CMI’s human (aka Robert) spent 10 minutes digging into both parks’ websites, he found they did well detailing why dogs aren’t great to bring to the parks. However, neither explained why it would be suitable for a pet.
What haven’t you written about but should?
You often talk about the greatness of your business, products, and industry on your websites, blogs, and resource centers. But what’s not so great? Who do you not serve? Make it easier for searchers to see the distinctions.
“You can’t know where Google and other search engines’ AI will go, but you can know it’s going,” Robert says.
What do you think of the changes? Let us know in the comments.
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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.”
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