MARKETING
3 Questions To Help You Evolve Your Content and Marketing
Revolution brings sudden, radical, or complete change. And we’ve experienced enough of those 180-degree shifts to leave us all exhausted.
Evolving, on the other hand, happens more subtly over a longer period. Still, change for the better (rather than change for change’s sake) requires a series of decisions and actions.
Here’s the good news: You don’t need to radically change everything you’ve learned or processes you’ve relied on to meet content marketing’s challenges. But you will need to evolve.
Thousands of content and marketing professionals came to Content Marketing World in Washington, D.C., last week to share ideas on how.
As you might have guessed, many of the conversations involved artificial intelligence. Some of the brightest minds in AI shared their views on the state of AI and what it means for the future of marketers. I can’t share all the nuances and details in this recap without drowning out the rest of the week’s lessons (more to come in our ongoing coverage). But here’s a TL;DR version: AI will continue to have an extraordinary impact on our industry but so will humans.
With that understanding, I offer some provocative questions to consider based on the ideas keynote speakers shared for evolving to meet the challenges of 2023 and beyond.
1. Are you crystal clear about your content mission and purpose?
I’m sure you’re familiar with Zillow – the brand name has morphed into a verb to describe looking up home values.
You might think Zillow becoming a household term means the brand has achieved marketing rock-star status. Job done. Why would their marketing team change a thing?
But even established brands need to maintain and build on their reputation. As much as the Zillow team appreciated its funny and cool reputation, the company isn’t in the business of giving people a peak behind the curtains of houses – it’s an online real estate marketplace.
As Beverly Jackson, the company’s vice president of brand and product marketing (and Content Marketer of the Year finalist in 2018), explained, the team needed to evolve that reputation.
How did they do it? First, Beverly shared, they crystallized their purpose and centered their content on one mission – to make it easier for people to go through the home-buying process.
To do that, the team created a central hub where people can find everything they need. To promote it, they launched a campaign that embraced the reason most people know Zillow (i.e., to find out how much their boss paid for their home) and let them know it was so much more (i.e., a place to help them buy their own home).
That campaign returned a 94% unaided brand recall. “When customers started talking about Zillow the way we talk about our brand, we knew we were onto something,” Beverly said.
How can you adjust your organization’s marketing messages to get the company and the audience speaking the same language?
When customers talk about your brand the way you talk about it, you’re on to something, says @BevJack via @EditorStahl @CMIContent. #CMWorld Click To Tweet
2. Have you fallen for the biggest lie in marketing?
Derek Thompson is a writer and editor for The Atlantic, author of the bestselling book Hit Makers: How to Succeed in an Age of Distraction, and host of the Plain English podcast. So he was a natural fit to interview the insightful, smart, and funny actress, producer, and director Elizabeth Banks (we’ll bring you more on that talk another time).
But I’m still thinking about the ideas in his solo keynote speech a week later.
Derek challenged what he called the biggest lie in Hollywood, marketing, science, academia (and pretty much everywhere else): that people need (and like) new things.
“The truth is that the most fundamental human bias is toward familiarity,” he said.
He only needed to point to the top-grossing movies of this century (think Avengers, Star Wars, Guardians of the Galaxy, etc.) to get nods of agreement from the CMWorld crowd.
“In an infinitude of choice … we are pulled toward the familiar,” Derek said.
Need more proof? Think of Spotify. New music floods the platform every week. Yet, listeners opt for the tunes they already like.
Derek shared what happened when Spotify tried to push subscribers to new music by creating Discover Weekly, a playlist of 30 new songs that drops into listeners’ feeds every Monday.
A bug in the algorithm let a few familiar songs creep into the playlist. When Spotify fixed the problem, it found the number of people listening to the playlist plummeted. “A little bit of familiarity in a product designed for novelty made it more popular,” Derek said.
Derek used an acronym – MAYA – to describe the process of evolving beyond the familiar frontier. The letters stand for Most Advanced Yet Acceptable, a descriptor coined by Raymond Loewy, the father of industrial design. (Air Force One and the 1953 Studebaker, which launched the automobile’s more aerodynamic look, are among his more famous works.)
Here’s Loewy’s MAYA philosophy: You can sell something familiar by making it surprising. You can sell something surprising by making it familiar.
What new things can you sneak into old things to engage your audience or guide them toward something new?
The idea that people need and like new things is the biggest lie in marketing, science, and academia, says @DKThomp via @Editor_Stahl @CMIContent. #CMWorld Click To Tweet
3. Are you running enough content experiments?
Phyllis Davidson, vice president and principal analyst at Forrester, advocated for experimentation. I see that as the logical next step after following Beverly’s and Derek’s counsel.
But before I get into that, consider this jaw-dropping stat Phyllis shared from Forrester’s B2B research: 77% of customers are unlikely to expand their contracts with a brand if its content isn’t valuable or helpful. And that number jumped 10 percentage points between 2022 and 2023.
Bookmark that statistic for the next time you need to convince your boss of content’s value in the buying process.
According to @forrester’s #B2B research, 77% of customers are unlikely to expand their contracts with a brand if its #content isn’t valuable or helpful via @EditorStahl @CMIContent. #CMWorld Click To Tweet
Back to her theme of experimentation: Phyllis got a chuckle from the crowd when she explained no one at CMWorld could just go to the Olympics as a gymnast. We all got the message: You can’t be proficient at something if you don’t do the work to become an expert.
“Given how risky some of the new tech is in helping us to modify and improve our content, organizations have to learn how to experiment at the content level to use these technologies,” Phyllis explained.
How do you do that? It’s not by innovation, she said. It’s by experimentation. Then she shared this quote she attributed to Isaac Asimov: “Experimentation is the least arrogant method of gaining knowledge.”
But how should you experiment? Return to what you learned in your middle school science classes.
Phyllis refreshed us on the steps and provided a marketing example to illustrate:
- Ask a question: Will the AI-generated industry version of a white paper perform better than the non-AI?
- Research: Evaluate differences in knowledge requirements and preferences across industries.
- Formulate a hypothesis: AI-generated financial services and life science versions delivered in the same channels will perform 10% better.
- Make a plan: Use outbound email to test versions against industry audience members.
- Experiment: Run the test with list subsets using the same parameters/timing. Measure performance by the number of white paper downloads.
- Collect and record results: Compare results across all versions.
- Draw conclusions: Financial services met the key performance indicator (KPI). Life sciences did not. Run financial services white paper program. Evaluate input for the life sciences version. Consider testing a third industry.
The more marketing experiments you conduct, the more you can move quickly, and failure becomes a lot less painful, Phyllis said.
#Marketing experiments help you move faster – and make failure a lot less painful, says Phyllis Davidson via @Editor_Stahl @CMIContent. #CMWorld Click To Tweet
What will be your next marketing experiment?
Evolution doesn’t require a revolution (even with AI)
As I mentioned, AI was on everyone’s mind. I found these themes (shared by Avinash Kaushik, chief strategy officer at Croud and formerly of Google) particularly helpful.
AI manifestation falls into one of three categories today, he explained:
1. AI gives us tools that help in our work.
2. AI can operate as co-pilots to help us be smarter and faster.
3. AI serves as a muse to help us get started and speed up our human output and quantity.
But AI adoption isn’t a revolution. As Cassie Kozyrkov, former chief data scientist at Google, pointed out, AI has existed for years. What is new, she said, is the user experience and design around AI.
I would describe that as the evolution of AI – from tech to tool applied by people.
Marketers – educators, trust builders, and entertainers – must embrace evolution. We make conscious decisions day after day about what to do next, whether about adapting our messages to our audience’s changing needs, planning our content to guide our audiences along, deciding how we’ll use AI, or something else.
We don’t need a revolution. We just need to keep evolving.
ADVICE FROM CONTENT MARKETING WORLD 2023 SPEAKERS:
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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