MARKETING
A Framework for Discovery Today
Content optimization isn’t new. It started several thousand years ago when people began to organize content for discovery in libraries.
About 2,300 years ago, the renowned Greek poet and scholar Callimachus built the first Google – a topical catalog of the Great Library of Alexandria’s holdings.
No surprise – helping people find information today requires a vastly different approach.
A library’s organization offers a standardized way for people to search a large amount of information quickly when they know they’re looking for. But that style of organization makes less sense for content designed to engage audiences and introduce new experiences.
Think about it. You wouldn’t walk into a library with the goal of becoming smarter about the future of business. Yet marketers often default to organizing thought leadership like a hierarchical library.
Worse, many catalog it by content type. I’ve seen so many B2B resource centers organized at the highest levels as e-books, white papers, videos, and short articles. It forces audiences to pick their content experience before choosing a topic or question to answer.
Organizing #B2B resource centers by e-books, white papers, videos, etc., forces your audience to pick the experience before the topic, says @Robert_Rose via @CMIContent. Click To Tweet
Modern content optimization framework
To meet audience needs in 2023, you must optimize content for search engines, social channels, vertical channels, industry channels, and (yes) even the humans who ultimately navigate their way to your content. It’s a tricky balance to decide what to optimize for.
Historically, marketers optimized by the logical hierarchy because that was optimal for search engines. But with AI and other technologies, such as personalization and targeted content, coming to the forefront, I wonder if it’s not time to look at new ways of organizing your content.
A framework can help you think about each attribute of a modern content optimization model:
- Intent
- Authority
- Internal context
- External context
- Described
Modern #content optimization framework: intent, authority, internal context, external context, and described, via @Robert_Rose @CMIContent. Click To Tweet
Let’s look at this one by one:
Intent
Understanding your audience’s intent is almost more important than who they are. Think about it. If you have 1,000 new visitors coming to your website, what’s the most valuable thing you can know about them? Is it who they are? Or is it why they came to surf your content? You must place heavy importance on optimizing your content in a way that helps you understand their intent – before you ask them who they are.
How do you do that? You can cleverly organize and create your content. For example, perhaps you organize by task or desired outcomes rather than content type. Or maybe you provide more detailed content titles? For example, you might have a white paper titled: “Visions of a New Future for Our Industry: What You Need To Know as You Contemplate Change.” I went over the top on that title to make the point, but you get the idea. Somebody downloading a white paper is NOT a qualified lead at this point.
At this point, the goal should be to make the information that matches their intent easy to find.
Authority
When you develop your content – whether educating, inspiring, entertaining, or simply providing directions – authority matters, and details matter. Depth matters. You cannot deliver authority in a single piece of content. Instead, it’s communicated through your library of content. These attributes include linking, attaching, and serving relevant details and more in-depth content, so your content consumer never needs to go anywhere else.
Instead of organizing your content to host a virtual box full of PDFs, images, PowerPoint presentations, etc., build cross-linked experiences that serve the “best next” experience so the audiences can go deeper.
Build cross-linked experiences that serve the best next experience so the audiences can go deeper, says @Robert_Rose via @CMIContent. Click To Tweet
Internal context
The internal context attribute is about meaning. It might be your brand’s points of view about the world or its unique take or solution to a problem. It might be the information you provide in proximity to other information.
Organizing your content by points of view is similar to organizing it by intent. But you’re not doing it based on tasks or questions but rather by making a complete argument for the stories you tell. For example, a technology company focused on cybersecurity might organize its resource center by the brand’s point of view on the future of AI and include another section on the future of financial security in a digital world.
Your content’s clear, consistent, and differentiated point of view and/or meaning makes it stand out when people search for answers. How the content is displayed also communicates a context, which can deepen the engagement.
I call this the settle-the-bar-bet problem. Someone at a bar says, “What’s the answer to that question?” You answer. They search and find the answer to confirm what you provided. Usually, the questioner nods, puts their phone in their pocket, and moves on.
But what if your answer sparked further interest? It intrigues them, so they read it aloud to their friend, “Did you also know that …” Maybe, they even bookmark it for future reading. That’s the internal context you want to achieve.
External context
Technology and AI-driven solutions also enter the optimization framework to assist with conditional contexts – how the content will temporarily be organized at a user or account level. Or it may be organized based on a mobile vs. desktop context.
You could determine that first-party data, such as location, buying history, content consumption, and device type, will inform the content’s organizational appearance.
Also, you could use this data to decide which content to put into social media, vertical sites, and other interfaces where you don’t control the display.
Described
Directly related to external content, providing multiple ways to organize your content grows in importance today. If external context lets the consumer see content displayed based on their behavior, “described” organizations create content that describes your content – to help audiences filter (or automate), categorize, measure, personalize, and activate content. This content usually falls into three categories:
- Descriptive metadata – categorical terms about the piece of content, such as the audience persona, buyer’s journey phase, author, or supported product category.
- Administrative metadata– content management elements, such as publication dates, expiration dates, rights management, legal or compliance categorization, etc.
- Structural metadata– details that help connect one content asset to others, such as a set of data that reacts to a prompt like “If you like this, you might like this too.”
Go forth like a new Callimachus – the media company
I wouldn’t recommend attempting all these, but you can include multiple approaches to reorganize your content management. The web, search, and artificial intelligence will likely evolve beyond the static hierarchical, library-like means of providing information.
Start with optimizing for humans. When you understand your audience and their intent, you can optimize the content for findability. Once you create in-depth, valuable, informative, and engaging content with authority, you can bring out the best meaning in your content and drive better internal context.
With that achieved (or in progress), you can move to the tech side of optimization with external contexts, such as mobile, search, social, etc. You can describe that content so machines can understand and do more with it and use technical solutions to present it optimally.
Put simpler: You are Callimachus and the modern media mogul. Your brands are not only poets and storytellers; you are the media companies. You are here not just to provide a resource but to engage and guide people to the best stories when they need them.
It’s your story. Tell it well.
Updated from a June 2021 post.
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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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