MARKETING
Don’t Make SEO the Reason for Your Content Marketing Strategy
Historically, many businesses started their content marketing programs because they believed it would help them rank higher for organic search results. When their target audiences would search for potential solutions to their needs and wants, they would find the brand’s vast array of content and believe that brand is the one that provides the most value.
Unfortunately, what many businesses discovered was that a foundation built on being “found” in search meant they had to focus on content that chased traffic. That created an inherent pressure to create content designed to rank rather than content intended to lead, entertain, or inform.
Successfully organizing content to optimize organic search has become more difficult over the last decade. The quality of competition, the sheer quantity of content, and the growth of paid search advertising have made digital real estate on the first page of Google more expensive and more challenging to maintain. And appearing on anything but the first page is not just second place; it is tantamount to failure. As my good friend and SEO expert, Arnie Kuenn used to jokingly say – “the best place to hide a dead body is the second page of Google results.”
However, the classic SEO-first mentality still exists in building a case for a content marketing platform. In two recent conversations, clients expressed frustration about where they were in launching their new content marketing program.
Each had asked their digital agency to help them identify the best way to bring their content marketing program to life. In each case, the consultants came back with a 30-slide deck making the business case for content marketing by saying:
- Your audience searches Google X times.
- Here are the most popular search terms.
- Here’s what they are finding.
- Here are the terms they search that you care most about.
- Here is the gap (in other words – what they are not finding).
- Conclusion A: The number of searches you care about is limited.
- Conclusion B: The number of answers for the terms you care about and your audience isn’t finding is low (it’s going to be hard to compete).
- Recommendation: Focus short-term on creating content about the terms you care about but for which your audience isn’t finding answers. Focus long-term on competing for the highly sought keywords. Put simply: Game on – let’s start creating a lot of content.
- Last slide: We can help you with creating that high-quality content that will compete for that precious real estate on the front page of Google search results.
Now, if it sounds like I’m denigrating the fine work that good SEO firms do, let me be clear that I’m not. I absolutely understand good firms do amazing work in this space that goes well beyond my pay grade.
But that slide deck illustrates an all-too-common argument for launching a modern content marketing program. It presents two problems. First, SEO has arguably never been a good foundation for a content marketing platform. Second, and more importantly, is that web search itself changes in a way that fundamentally changes the content marketing equation.
#SEO has arguably never been a good foundation for a #ContentMarketing platform, says @Robert_Rose via @CMIContent. Click To Tweet
Let’s look at each.
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Lesson 1: Google isn’t here for your brand
Google has never been interested in helping you build an audience for your brand’s platform. Quite the contrary, it always has been interested in you helping them build an audience for theirs. They designed web search as a helpful tool to create just enough commoditization in results that advertising featuring exactly what the searcher seeks is more attractive.
In today’s world of web search, using Google results to form the foundation of your content marketing strategy is like watching the freeway from an overpass to determine what kind of car you should buy. Sure, you can count the traffic, but you have no idea about the value of any one of the cars.
You can’t know the social or emotional context of your audience’s needs or wants by seeing if they find what they’re looking for on Google. All you can tell by looking at search velocity and keyword competition is whether a topic is popular and/or well-covered.
For example, a high search volume term may indicate a huge search audience. But it also could indicate many in the audience find it difficult to filter anything that differentiates (and thus might not rank well). Therefore, popular search terms might indicate an audience desperately trying to find good quality content on a topic (so they search for it frequently). In those cases, you would mistake popularity for frustration.
On the other hand, a low search volume may indicate a small audience, making it not worth the time trying to rank for that keyword. Or perhaps the low volume indicates tomorrow’s new hot topic that few have thought to try and find it.
For example, if we used search volume in 2009 to decide whether to launch a platform to evangelize the topic of “content marketing,” we probably would have decided against it. Look what we would have missed. (In 2009, the term “content marketing” was 18. By 2020, it had grown to 100.) Spoiler alert: We didn’t look at the SEO of the term.
You should know more about your audience than Google does. When formulating a new content marketing platform, you should realize that Google search has been (and is) helpful for understanding the zeitgeist of popular topics and terms. But it hasn’t been as helpful in understanding what your audiences will be interested in tomorrow.
You should know more about your audience than @Google does, says @Robert_Rose via @CMIContent. #SEO Click To Tweet
Too many SEO plans for content marketing platforms feel like they are always chasing their tail. Teams spent 12 months chasing traffic on keywords popular a year ago. By the time they see progress, it’s too late. Great, you’re on the first page of Google, but it’s for a term no one cares about anymore.
But what’s changing now is even more important to content marketing. The transition of web search itself is incredibly important – and your business case must reflect this.
Lesson 2: Google still isn’t here for you
Content discovery is changing the way audiences interact with digital content. And Google still isn’t interested in that happening on any channel other than Google.
New research, as detailed in Search Engine Journal (SEJ), shows that 30% of search users are “forced to redo their search queries in order to find what they’re looking for.”
30% of search users must redo their queries to find what they’re looking for according to @sejournal research via @Robert_Rose @CMIContent. Click To Tweet
Audiences become more and more frustrated with the results Google provides. Many are simply wrong or unhelpful. The SEJ article references a user who searched for “calories in a bottle of wine.” The rich content returned on the search page showed 123 calories (the amount in one glass of wine). As the user exclaimed: “I swear Google gets dumber by the day.”
But interestingly, this isn’t because Google is getting dumber; it’s because Google is getting smarter. Of course, that “wrong” result is an early indicator that it can get smarter.
Consumption of digital content, and its sheer quantity, are getting to a place where broad informational searches are less efficient and useful. Instead, many search platforms, social media, and other big content platforms are leaning into what’s called content discovery.
Content discovery might be best described as “content recommendations.” The discovered or recommended content is delivered without an explicit ask. In the wine example, Google assumes what the searcher meant to ask and provides the answer. Google knows a lot more people care about the number of calories in a glass of wine than people who want to know how many calories are in a bottle. Thus, Google served up that content before the searcher even knew that’s what they wanted.
If you’re looking for the best example of content discovery, look no further than the astronomic rise of TikTok. The TikTok experience delivers more and more relevant content as the viewer uses it more and more. To varying degrees, “recommended” articles at the bottom of blogs follow the content discovery idea.
Content marketers should see this discovery trend growing. Content suggestions based on a customer’s intent, demographics, and other first-party data are growing in thought leadership resource centers, websites, and e-commerce platforms.
From a web search perspective, the manifestation of content discovery is that the content appears on the results page. Searchers don’t even need to click to get the basics of that enhanced content. While today that content may be wrong. Tomorrow, it will be better. And next week, it may be better than yours.
Remember, Google is still not trying to help you – the content creator.
HANDPICKED RELATED CONTENT:
Content marketing starts with your audience
If you look to launch a new content marketing platform, look at something other than search optimization as the core benefit. Those days are gone if they ever really existed. Yes, learn about SEO and how the evolution of search into content discovery will affect how your content is distributed.
Again, I’m NOT suggesting you stop employing the best practices of SEO, especially as they evolve in the content discovery direction.
What I am suggesting is that you will not find the foundational story that differentiates your brand by looking at SEO and the benefits of organic search. You’ll find that story in the hearts and minds of the audiences you want to reach – and by matching their desired value to the value you can deliver.
Then, and only then, should you look at how you might write the content, position it, and promote it so it can be found. Or better yet – discovered.
It’s your story. Tell it well.
Get Robert’s take on content marketing industry news in just five minutes:
Watch previous episodes or read the lightly edited transcripts.
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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