MARKETING
The Future of AI in Content Is in Your Hands [Rose-Colored Glasses]
Have you heard a lot about ChatGPT lately?
I thought so.
In case you haven’t (maybe you’ve been too tied up with holiday shopping or closing the fourth quarter), ChatGPT is a prototype artificial intelligence chatbot developed by OpenAI that’s gotten a lot of media and social media coverage. This class of generative AI technology receives prompts from users, then generates new text or images (based on the data set used to train the model) in response.
That means if you’re a software engineer, you can ask it to write (or check) your code for you. If you’re a writer, you might ask it to write a blog post on technology (reasonable) or a history of London in the style of Dr. Seuss (Why? Because you can). If you’re a student, you might use it to write a college application essay. You get the idea.
The results are impressive – sort of. But I’ll come back to that.
The response to ChatGPT’s release last week (like other recent developments in AI for image creation and manipulation) has run the full spectrum of the Kubler-Ross stages of grief: denial, anger, bargaining, depression, and acceptance.
Some say ChatGPT will fundamentally “change everything in marketing, forever.” Others say it has “passed the tipping point,” and we must explore it. One writer even referred to it as a “pocket nuclear bomb … and should be withdrawn from our collective grasp immediately.”
Whether you agree or disagree with any particular take, the response has been dizzying.
Most of the conclusions in these pieces are tempered by the same word: “yet.”
I urge you to focus on the “yet” in these reactions (including this one, by the way). This technology is still in its formative stage. It’s likely to have profound effects on all manner of creative activities – including marketing and communications. The trouble is, we don’t know what those effects will be.
Yet.
#AI will have profound effects on creative activities, including #ContentMarketing. We just don’t know what they’ll be yet, says @Robert_Rose via @CMIContent. Click To Tweet
Some people likely will use generative AI technology in a way that harms the creative process and creators. But it’s just as likely that some people will leverage the technology to further the craft of writing – and challenge the rest of us to use the tool to get better at it.
There will also be every flavor of the messy middle.
We are the change, not the technology
A quote almost always misattributed to renowned media theorist Marshall McLuhan says, “We shape our tools, and thereafter our tools shape us.”
This means (and it’s the most McLuhan of ideas) we create technology, but its existence also changes us. It then follows that the meaning of any new technology we invent comes from how it changes us.
With artificial intelligence and content creation, we’re in the former stage of that process. But the latter is coming.
It seems a bit premature to latch onto the idea that artificial intelligence will disrupt the future of marketing. What was the last new technology to do that? Search? For sure. Social media? Probably. Mobile? Maybe.
It also seems unproductive to proclaim that future robot overlords will take over every creative activity in our strategy. And it’s equally fruitless to claim that generative AI is some kind of “uber-cheat code,” infringing, copying, or artificially producing content that will reduce our collective creative intelligence.
Instead, maybe we can just ask a few questions – to ourselves instead of to an AI engine – and see if we can’t plot an optimal path.
The truth is ours to tell
Worries about inserting technology into the very human creative process aren’t new. After the invention of the printing press, the Dutch humanist Erasmus is said to have complained:
“To what corner of the world do they not fly, these swarm of new books? … [T]he very multitude of them is hurting scholarship because it creates a glut, and even in good things, satiety is most harmful …. [Printers] fill the world with stupid, ignorant, slanderous, scandalous books, and the number of them is such that even the valuable publications lose their value.”
Erasmus was horrified that technology would enable any no-talent hack to publish bad content and that valuable content would be degraded as a result. Sound familiar?
The tension between human creation and technology continued with the advent of the word processor, digital photography, creative software editing suites, music editing software, and computer graphics.
Today, computer programs can simulate entire choirs, enabling anyone who can type in words to create choral symphonies almost instantly.
For years, I’ve been able to transform my keyboard into the Phil Collins’ drum kit and create my own versions of the classic In the Air Tonight solo. If I compose a song with that drum kit, fill it with a sampled choir that sings words I type, then produce an album with a cover painting I made in the style of Ansel Adams, am I an artist or a hack?
I suspect you’d have to see and hear it first. But regardless of the answer, the obvious follow-up question is, what if a tool existed where I didn’t have to type it or use the keyboard? What if I could skip all the typing and playing and just ask? Would it change your answer either way?
Using artificial intelligence for content creation is not innovative. It’s inevitable.
Using artificial intelligence for #Content creation isn’t innovative. It’s inevitable, says @Robert_Rose via @CMIContent. Click To Tweet
Technology makes us more creative, not less
Regardless of which creative technology you study, the tension-filled relationship with the human creative process has always been the same:
- The fear arises that people with no experience or talent will suddenly be granted unearned abilities to create.
Which leads to the second tension:
- The fear arises that human artisans will be replaced by “hacks” or machines.
Both tensions share one thing: Fear.
But in every case, fears like this have proven unfounded. Yes, many technological innovations have removed the need for human participation in a part of the creative process.
Digital photography removed the need for processing film in a dark room. Digital editing sites removed the need for physically cutting and splicing film together. Digital word processing and imaging software removed the need for manual typesetting.
But for each successful innovation, the new technology either added a capability, made an existing activity in the creative process more efficient, or both.
So, while the fear of being replaced is almost certainly legitimate, it will only be made real if creators choose the wrong way to be changed by technology.
Put simply, today’s content creator is no more or less talented or equipped to express ideas. ChatGPT and other generative AI only change the efficiency of those activities.
So, what is the short-term role of AI within our marketing and content creation teams? Earlier in this article, I called the initial results of ChatGPT (and the images created by DALL-E 2 and others) “impressive – sort of.”
Here’s what I meant:
If you move beyond the cute constructs like “create country song lyrics in the style of heavy metal” (yes, I did) and look at any of the essays or longer posts that ChatGPT routinely creates, you may notice the lack of a deeper human connection.
For example, I prompted ChatGPT to “tell me a funny story about a marketing guy having an existential career crisis about artificial intelligence.” Here’s what it came up with:
There was once a marketing guy who had a serious existential crisis due to the emergence of AI. Every day, he would go to work and worry that AI could do his job better than he ever could. He became so obsessed with his fear of being replaced that he decided to take drastic measures. One day he entered the office dressed up as an AI with a shiny metal face mask, blue LEDs flashing, and wires coming out of his ears. Everyone was so impressed by his transformation that they all applauded him and gave him a promotion. After that, the marketing guy was no longer afraid of AI and embraced its potential to help businesses grow and succeed.
You can see that ChatGPT is good (quite good, actually) at constructing sentences that logically flow from one to the next. But there’s no uniquely emotional point of view – or even anything that resembles building a story. Simply put, ChatGPT can do plot – it can tell you what happened. But it’s not great at telling you in a way that makes you feel anything.
AI has no wisdom.
Wisdom is the very human quality of having the experience, knowledge, emotional intelligence, and sound judgment to help with decisions. Unfortunately, AI can’t currently combine these things.
Therefore, it can’t judge the wisdom of or originate your next differentiated white paper or e-book. It won’t create the most original idea for how you should approach your new podcast. It won’t write the next visionary business book. But it can produce something that fits the model of each of those.
Think of it this way. If you’re writing the next great American romance novel, you can use ChatGPT to get a “meh” description of Charleston, South Carolina, from your character’s perspective. But the text it generates won’t help the reader feel her emotional connection to South Carolina.
Yet!
AI will be what we allow it to be
In describing the inevitability of disruptive innovation, business professor and author Clayton Christensen once shared the anecdote of a professor who dropped a pen and told his class, “I hate gravity.” After a moment, he added, “But do you know what? Gravity doesn’t care.”
The truth about artificial intelligence is that it’s here already. Arguing whether it will or won’t be used is a bit like asking digital photographers to put down their sim cards. We already routinely use AI to research things on Google, check our grammar, or search for the right hero image for our blog. Now it will help us construct the written word.
The only question that remains is how to harness it as professionals.
When it comes to artificial intelligence in content creation, many purveyors of new technology are doing themselves no favors by positioning the innovation as taking the “drudgery” (or “grunt work”) out of the creation process or as “magical.”
This is a critical point: Creators don’t view the activities or capabilities that are changing as drudgery, wasteful, or mysterious.
Digital film editing didn’t take the artistry out of cutting and splicing film together. It added an extension for content creators to do things they couldn’t do previously.
Digital imaging software didn’t remove drudgery from opening and mixing paints in a creative way. It added capacity to that process, giving artists an entire rainbow of color palettes to work with.
AI will open new doors and extend the capabilities of writers and other content creators, just as it closes doors on others. It will transform the process of written content creation in business. It will change all of us.
How it will do that, though, is still up to us.
It’s your story. Tell it well.
Get Robert’s take on content marketing industry news in just five minutes:
https://www.youtube.com/watch?v=videoseries
Cover image by Joseph Kalinowski/Content Marketing Institute
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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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