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Marketing in 2024: AI, Brand, and the End of Social Media?

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Marketing in 2024: AI, Brand, and the End of Social Media?

As that song from Rent says, “525,600 minutes. How do you measure, measure a year?”

It’s been a heck of a year in marketing. We’re not going to miss a lot about 2023. It started as disruptive and tough. Many colleagues, especially in tech, suddenly found themselves without work, mostly based on the perceived best practices of some numbskull billionaire who played around with his tech company to see how far he could break it down before it broke.

But 2023 did have its moments. The explosive idea that remains generative AI prompted some amazing new startups and innovations. And, of course, the appearance of the predicted recession never happened.

Maybe the biggest thing in 2023 centered on all the handwringing about what to start in marketing, what to innovate, and what to change. If you were in the business of marketing change in 2023, you spent the large part of the year like Notre Dame’s Rudy — on the sideline just hoping that coach would call your name.

Watch CMI’s chief strategy advisor Robert Rose delve into 2023 and his hopes for 2024, or keep reading for his thoughts:

Almost one year ago to the day, Robert covered this new thing called ChatGPT. Demand was so high that OpenAI turned off access requests for the app. He advocated for exploring how it would expand your capabilities and fit into your marketing process rather than how it would replace you. He predicted generative AI would extend your capabilities as writers and content creators and close the doors on the need to do other tasks.

What does he think now? He’s still wrestling with which door (registration required) is best to open and which to close.

Is it still a Web3 world?

In January, Robert talked about the precipitous decline of Web3 and the metaverse. He did so by discussing the evolution of Web 1.0 and Web 2.0 and pointing out Facebook’s brand name change to Meta at the end of 2022. He talked about how NFTs (non-fungible tokens) and the metaverse attracted eye-popping valuations and headlines. Then, he delved into the buzzwords dropping into the conversation even as some of the experimentations continued.

Starbucks got a mention for its new NFT-based loyalty program called Odyssey. It still seems to be doing just fine as the year closes, as is Web3 after the crypto winter. It’s just that thing called AI gets all the type.

Search engines meet AI

As winter ended and spring arrived, AI continued its rumble and started more noise in the search engine market. Microsoft and Google announced AI chatbots that would power their internet search. Google made a big error during its chatbot announcement demo, quickly putting trust as a top issue for generative AI. How many errors would it make? What about hallucinations in which AI just made up stuff?

Robert talked about how searching the internet and generative AI were different use cases, and you needed to explore both. And now, Google tried again with the launch of Gemini, and well, it seems to have failed again with its demo being called fake news.

Giving podcasts and purpose a listen

As spring sprung, we talked about podcasts because YouTube got into the podcasting business. They announced the ability to create and label podcasts on the platform, allowing people to listen or watch. They also offered up new measurement techniques.

YouTube podcasts didn’t shake up the world this year, but the platform has become THE most-used podcasting platform.

The summer saw a pushback on purpose-driven marketing. Contention arose as marketing programs focused on social issues, as exemplified by the trouble that Bud Light’s use of Dylan Mulvaney during Pride Month to promote its products on Instagram. The story wouldn’t go away.

First, the company tried to backtrack and apologize for offending people. Then, the company threw the marketing team under the bus and blamed declining sales at the feet of their missteps. By the end of the year, many articles had appeared on purpose-driven marketing that included mentions of the potential risks it brings.

Robert says he expects brands to double down in 2024 and get even more involved with social and cultural issues. Brand—and purpose-driven brands especially—will be an incredibly important factor in marketing next year.

Social takes up sewing and exploding

As summer hit the dog days, the slow implosion of X, formerly known as Twitter, continued, and it went official with its X designation. In July, Meta debuted Threads, which became the fastest platform to reach 100 million users since, well, ever. Excitement grew that it might become the new Twitter.

But that thinking dissipated quickly as people kind of gave up on social media full stop. Now, at the end of 2023, X can’t get any lower or less useful. Advertisers and users continue to flee. People who stopped using the app increased by more than 30% this year and the company’s revenue is down some 50%

But the much smaller X still commands the biggest headlines and ranks 12th in popularity of worldwide social networks. That’s less than Snapchat and Telegram and slightly more than Pinterest.

Running in 2024

As you get ready for 2024, let’s just all put our collective hearts and heads together for a much more productive year. Predictions are always fun but kind of useless. We’ll let Robert share what he believes should happen in the new year:

  • Marketing teams will understand that AI really is a content strategy challenge, not a tech challenge.
  • Renewed action on Web3, blockchain, and perhaps a renewal of Web3 co-created community-building will occur.
  • Brand marketing will take center stage as the source of information. Investments will continue in influencer and subject matter expertise as a function of brand alignment, especially in B2B.
  • Social media’s upheaval will continue, becoming just another form of media available for renting or organically distributing your content for consumption. A small percentage of content creators will thrive, leaving most people to consume their content. Communities will grow in the form of owned media, especially through events. Both digital and physical brand experiences will be the new social media.

Finally, change will be sexy again in 2024. From innovation in AI integration to content and owned media strategy to the focus on brand, activity will center around how you become the trusted source of interesting things.

It’s time to roll up your leaves and get to work. You have 525,600 minutes.

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Cover image by Joseph Kalinowski/Content Marketing Institute

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YouTube Ad Specs, Sizes, and Examples [2024 Update]

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YouTube Ad Specs, Sizes, and Examples

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!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists

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Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.

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A deeper dive into data, personalization and Copilots

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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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