MARKETING
Should Your Brand Shout Its AI and Marketing Plan to the World?
To use AI or not to use AI, that is the question.
Let’s hope things work out better for you than they did for Shakespeare’s mad Danish prince with daddy issues.
But let’s add a twist to that existential question.
CMI’s chief strategy officer, Robert Rose, shares what marketers should really contemplate. Watch the video or read on to discover what he says:
Should you not use AI and be proud of not using it? Dove Beauty did that last week.
Should you use it but keep it a secret? Sports Illustrated did that last year.
Should you use AI and be vocal about using it? Agency giant Brandtech Group picked up the all-in vibe.
Should you not use it but tell everybody you are? The new term “AI washing” is hitting everywhere.
What’s the best option? Let’s explore.
Dove tells all it won’t use AI
Last week, Dove, the beauty brand celebrating 20 years of its Campaign for Real Beauty, pledged it would NEVER use AI in visual communication to portray real people.
In the announcement, they said they will create “Real Beauty Prompt Guidelines” that people can use to create images representing all types of physical beauty through popular generative AI programs. The prompt they picked for the launch video? “The most beautiful woman in the world, according to Dove.”
I applaud them for the powerful ad. But I’m perplexed by Dove issuing a statement saying it won’t use AI for images of real beauty and then sharing a branded prompt for doing exactly that. Isn’t it like me saying, “Don’t think of a parrot eating pizza. Don’t think about a parrot eating pizza,” and you can’t help but think about a parrot eating pizza right now?
Brandtech Group says it’s all in on AI
Now, Brandtech Group, a conglomerate ad agency, is going the other way. It’s going all-in on AI and telling everybody.
This week, Ad Age featured a press release — oops, I mean an article (subscription required) — with the details of how Brandtech is leaning into the takeaway from OpenAI’s Sam Altman, who says 95% of marketing work today can be done by AI.
A Brandtech representative talked about how they pitch big brands with two people instead of 20. They boast about how proud they are that its lean 7,000 staffers compete with 100,000-person teams. (To be clear, showing up to a pitch with 20 people has never been a good thing, but I digress.)
OK, that’s a differentiated approach. They’re all in. Ad Age certainly seemed to like it enough to promote it. Oops, I mean report about it.
False claims of using AI and not using AI
Offshoots of the all-in and never-will approaches also exist.
The term “AI washing” is de rigueur to describe companies claiming to use AI for something that really isn’t AI. The US Securities and Exchange Commission just fined two companies for using misleading statements about their use of AI in their business model. I know one startup technology organization faced so much pressure from their board and investors to “do something with AI” that they put a simple chatbot on their website — a glorified search engine — while they figured out what they wanted to do.
Lastly and perhaps most interestingly, companies have and will use AI for much of what they create but remain quiet about it or desire to keep it a secret. A recent notable example is the deepfake ad of a woman in a car professing the need for people to use a particular body wipe to get rid of body odor. It was purported to be real, but sharp-eyed viewers suspected the fake and called out the company, which then admitted it. Or was that the brand’s intent all along — the AI-use outrage would bring more attention?
This is an AI generated influencer video.
Looks 100% real. Even the interior car detailing.
UGC content for your brand is about to get really cheap. ☠️ pic.twitter.com/2m10RqoOW3
— Jon Elder | Amazon Growth | Private Label (@BlackLabelAdvsr) March 26, 2024
To yell or not to yell about your brand’s AI decision
Should a brand yell from a mountaintop that they use AI to differentiate themselves a la Brandtech? Or should a brand yell they’re never going to use AI to differentiate themselves a la Dove? Or should a brand use it and not yell anything? (I think it’s clear that a brand should not use AI and lie and say it is. That’s the worst of all choices.)
I lean far into not-yelling-from-mountaintop camp.
When I see a CEO proudly exclaim that they laid off 90% of their support workforce because of AI, I’m not surprised a little later when the value of their service is reduced, and the business is failing.
I’m not surprised when I hear “AI made us do it” to rationalize the latest big tech company latest rounds of layoffs. Or when a big consulting firm announces it’s going all-in on using AI to replace its creative and strategic resources.
I see all those things as desperate attempts for short-term attention or a distraction from the real challenge. They may get responses like, “Of course, you had to lay all those people off; AI is so disruptive,” or “Amazing. You’re so out in front of the rest of the pack by leveraging AI to create efficiency, let me cover your story.” Perhaps they get this response, “Your company deserves a bump in stock price because you’re already using this fancy new technology.”
But what happens if the AI doesn’t deliver as promoted? What happens the next time you need to lay off people? What happens the next time you need to prove your technologically forward-leaning?
Yelling out that you’re all in on a disruptive innovation, especially one the public doesn’t yet trust a lot is (at best) a business sugar high. That short-term burst of attention may or may not foul your long-term brand value.
Interestingly, the same scenarios can manifest when your brand proclaims loudly it is all out of AI, as Dove did. The sugar high may not last and now Dove has itself into a messaging box. One slip could cause distrust among its customers. And what if AI gets good at demonstrating diversity in beauty?
I tried Dove’s instructions and prompted ChatGPT for a picture of “the most beautiful woman in the world according to the Dove Real Beauty ad.”
It gave me this. Then this. And this. And finally, this.
She’s absolutely beautiful, but she doesn’t capture the many facets of diversity Dove has demonstrated in its Real Beauty campaigns. To be clear, Dove doesn’t have any control over generating the image. Maybe the prompt worked well for Dove, but it didn’t for me. Neither Dove nor you can know how the AI tool will behave.
To use AI or not to use AI?
When brands grab a microphone to answer that question, they work from an existential fear about the disruption’s meaning. They do not exhibit the confidence in their actions to deal with it.
Let’s return to Hamlet’s soliloquy:
Thus conscience doth make cowards of us all;
And thus the native hue of resolution
Is sicklied o’er with the pale cast of thought,
And enterprises of great pith and moment
With this regard their currents turn awry
And lose the name of action.
In other words, Hamlet says everybody is afraid to take real action because they fear the unknown outcome. You could act to mitigate or solve some challenges, but you don’t because you don’t trust yourself.
If I’m a brand marketer for any business (and I am), I’m going to take action on AI for my business. But until I see how I’m going to generate value with AI, I’m going to be circumspect about yelling or proselytizing how my business’ future is better.
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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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