MARKETING
Marketing Tech Is So Bright, You Gotta Wear Strategic Shades [Rose-Colored Glasses]
I saw a stat not long ago that said marketers spend 30% of their work week learning, implementing, or searching for new technology to make content creation and management easier and faster. I can’t find it now, so maybe I imagined it.
But even if that isn’t true, it feels true.
My experience with two content teams over the last month shows why this happens.
One team uses a sophisticated tech stack with a modern content management system, a digital asset management system, and even AI-driven writing assistants. The other relies on a patchwork of shared cloud storage, HTML snippets in Excel spreadsheets, and ancient collaboration systems.
The teams produce the same amount of content – they’re getting the job done. But neither team feels like the technology they have serves them well.
As a result, they’re both vulnerable to the dream of a tech solution.
Many content marketers envision how much better their work could be if only they had the right technology. They see themselves happily using tools that automate processes, create insightful dashboards, or magically deliver the right content to the right people, at the right time, on the right channels and devices.
They spend so much time thinking about how to get the shiniest new technology they forget to consider how to use technology to get the most from their work and their team.
Too many marketers think about how to get the most exciting tech, not how tech can help get the most from their team, says @Robert_Rose via @CMIContent @Canto. Click To Tweet
The problem arises when people buy into the promises of new tech without first asking the most important questions: Do we need this? Why?
For example, I recently learned about a new technology that helps automate responses to data-access requests from consumers who think a brand isn’t using their personal data correctly. On its surface, the solution sounds neat.
But before buying tech like this, a smart marketing leader should ask: “Why is our strategy leading to so many disgruntled consumer requests? Is automated response tech the best choice to address their frustration?”
In other words, “Why do we need this technology?” The answer might (or might not) have anything to do with tech.
Cathy McKnight, who works with me at The Content Advisory, suggests a multistep process when selecting new technology. (Does it surprise you to learn that writing the request for proposal doesn’t happen until step seven?)
The first steps she suggests are essential, yet they’re rarely done. I’ll walk you through this critical part of her recommended process.
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Validate the need for technology
Validating your need for new technology seems like an obvious starting point, but it’s not.
Fear of missing out is strong, and it leads marketers to seek new tech because they’ve seen new tech. The tech they rely on today looks like a run-down neighborhood bar, while the latest tech solution looks like the hottest nightclub in town.
Don’t fall prey to FOMO. Before making any decisions, look at your current strategy, your plans, and your ability to get the job done today. Ask these questions first:
Do you have a technology problem?
Or is there another reason you’re not working in the best way?
One client I worked with considered a technology solution that would let them limit who could push the big red publish button. But they asked this question – and decided they didn’t need a tech solution. Instead, they started telling people who could (and couldn’t) push the big red publish button.
Can you solve the problem by adjusting the process?
This question reveals if you have process problems (or if you have any processes at all).
Let’s say you’re looking for ways to help a team member decide which website pages need updating more efficiently. First, ask how they do it today. If they look at a spreadsheet delivered to them through email, download all that information to their laptop, and prioritize the changes based on their experience, you don’t really have a process.
And that means technology shouldn’t be the first answer to that problem.
Could (or should) you update existing technology, or do you need new technology?
I can’t tell you the number of times I’ve seen marketing teams replace their CMS because they conflate it with their website’s design. When marketing leadership wants to redesign the website, they use it as an opportunity to replace the poorly implemented CMS.
Shouldn’t you at least see if an upgrade or reimplementation would suffice?
Don’t buy new marketing tech until you validate the actual need, says @Robert_Rose via @CMIContent @Canto. Click To Tweet
Create the business requirements
If you answer these questions and land on “Yes, we need new technology,” you’re ready to list your business requirements.
I won’t cover that process in detail as it’s well known: Audit and interview stakeholder groups to uncover the requirements in each of the relevant processes.
Ask whether the existing processes are the best way. You may find changing a process to better match how technology providers handle that process is easier than forcing tech to accommodate a non-optimal process.
Identify your focal needs
This third step is possibly the most important part of assessing your new technology needs.
You might think you have needs that no other business does. (And you’re not alone – nearly every marketing team believes it’s a special rainbow-colored unicorn.)
Spoiler alert: 90 to 95% of your business requirements are common. And this is a good thing.
Still, you likely will have a few processes unique to your business. And they may be too important to lose in a new technology implementation. These are your focal needs – the requirements that differentiate the technologies under consideration.
Focal needs will help you differentiate marketing tech under consideration, says @Robert_Rose via @CMIContent @Canto. Click To Tweet
Tech solutions may (or may not) be the answer to your problems
It’s easy to be blinded by shiny new technologies and approaches. But remember this: Your content technology stack won’t differentiate your strategy or content. It may make things easier – or it may make things more difficult.
But focusing squarely on your strategy and related needs always works as a nice pair of shades – you’ll see past the glitter and eventually find the gold.
Get Robert’s take on content marketing industry news in just about five minutes:
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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