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AI is going to make us strategy-first content marketers in 2024

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AI is going to make us strategy-first content marketers in 2024


It’s the second week of January and although it’s a new year, I’m still the same old me. Back at work, I’ve got new enthusiasm powered by an endless stream of holiday treats that came across my plate in December, but I can already see the bright shiny content strategy I dreamed up in November slipping away. 

Sure, I’ll execute on the big stuff; those pillar posts will happen, for sure, and I’ll refresh some key pieces of content so they don’t fully atrophy. But the fun stuff that makes me love content marketing and pushes me professionally? It’s already disappearing in a sea of new priorities, limited bandwidth, and requests. Like I said, same old me. 

Here’s the thing: it’s 2024 and I can be the same old me but with a fleet of powerful new sidekicks. I’ve got a better chance of not just bringing my content strategy to life, but even strengthening it as I go through the year—because AI tools are fully coming into their own. And they’re giving content marketers a whole host of gifts including but not limited to: 

  • Free time: AI tools really have freed me up to think strategically with support in ideating, creating, and editing all types of content. Plus, you can send me whatever nameless, faceless voice recording/blurry images/notes you have, and I don’t have to spend a whole day sorting through them by hand. 
  • Automation of the time-sink tasks: Tools I’ve tried (and listed below) allow me to try new (and send more polished) content types without the time required to learn a new skill or spend hours on nit-picking editing. 
  • Augmentation for other core strategic skills: Data analysis with a co-pilot makes it so much easier to stay creative without missing a beat from all the data my strategy generates. 

I’m going to give you a look behind the curtain for what I’m planning for my own content strategy development, plus the tools I can use to bring it to life. 

AI is a whole new chance to improve our content strategy game 

A strategy-first approach to content isn’t a muscle we content marketers often fully flex outside of yearly and quarterly planning sessions. If you do, then good for you, and I am not jealous at all. 

I always set out to achieve based on a strategy and I do so every time with the best of intentions, but life and business and huge, urgent requests get in the way. And lately, AI-generated content is also becoming a bit of a distraction in its own way. AI is still young at most organizations, and I’m starting to find content floating across my desk created by well-meaning colleagues. Yet, they’ve created it with no guardrails, processes, or standards. And it definitely wasn’t created with our content team’s strategy in mind. 

Without some gatekeeping, this kind of content is risky for both our strategy and our brand reputation. 

Plugging a prompt into ChatGPT or any other tool doesn’t translate into great content: despite what some teams seem to believe, more content isn’t better content (even if it was relatively low cost). 

But rather than putting the onus on team members to leave the content to us, the pressure is really on us as the content team. It’s up to me to tap the sign and lean even harder into the strategic side of content marketing and sharing that strategy. 

 Here’s how I’m going to do that and how I will use AI to help:

  • Get in on the data action: Your wider org already has AI tools to parse customer and sales data. Plus, the brand, growth, and paid marketing teams have all this kind of data, too. Get yourself a copy of those reports and pull out those themes for content that aligns with what your customers are talking about. Pro tip: Get those into your own preferred/allowed AI tool for a complete summary that works for your content strategy purposes. 
  • Look for gaps in seconds: Ask AI about the most appropriate keyword opportunities for our ideas. Then, prompt AI tools to get an idea of saturation (i.e., is everyone creating content about this subject?) and summaries to help look for gaps that you can sift through. 
  • Share, share, share internally: We get lots of requests for new content because teams don’t realize how much content we already have that probably works (or works with a few tweaks) for their purpose. AI tools are great for putting together docs, guides, and libraries to let everyone access the content and content calendar. It’s life-changing busy work now available to complete in seconds. Add in an integration to Slack or Teams to share the docs whenever asked and all of a sudden, you have more time than you know what to do with (not really, but the automation does feel good). 

Remember: the value of AI for content marketing is parsing huge amounts of data quickly and accurately, which is half the battle in content strategy. 

If the above is my plan, the next question is: how do I stay focused while building out my strategy and chasing new requests? Well, look no further. 

4 content marketing trends we’re excited for in 2024 with the help of AI 

Content marketers (by content marketers, I mean me) have a lot of feelings about AI tools. There’s grief because I know that there will always be a cohort of (incorrect) people who think that an algorithm can replace me. There’s fear that I’ll be called a “cheater” by using AI. But then there’s opportunity in that AI might make the sticky parts of our jobs easier, and it comes with a big exhale. 

I’ve been to a lot of AI webinars hosted by content marketing practitioners & the AI tools themselves, particularly in the last few months of the year. As the year marches on, the sentiment in the group chat is starting to move towards closer to optimism than at any point in the last year. 

 AI isn’t a replacement; it’s a co-pilot so I can focus on flying the plane (the strategy) and have a second pair of eyes to assess the validity of my ideas and hopefully make them that bit better. 

Without further ado, here’s where I’m directing my AI tools’ efforts this year: 

1. Master Copy Creation 

Machine learning is an incredible tool for copy creation, and we’ve already been using it for years for suggested text, SEO, and more (I love Clearscope and Grammarly). But with the advent of ChatGPT, we’re able to use generative AI to shore up parts of content writing that we all hope to do better: perfecting tone of voice or writing for different channels. 

ChatGPT is actually really great for this, which is fantastic news because tone and switching mediums are where so much content falls down because of lack of time, briefing that misses the mark, and because it’s a difficult skill to master. By the time you do, you’re likely no longer in the content creation trenches anymore. 

At the same time, ChatGPT isn’t going to nail your specific brand voice with one round of prompts. You can and must edit the content because even as the outputs get smarter, it still sounds like…an algorithm wrote it. But what will it do for you in seconds? 

  • Transform reports & long-form content into exec summaries
  • Create one pagers and short-form content from lots of notes
  • Generate copy for slides based on a brief 

For this one, all you need is ChatGPT and a good understanding of how to prompt it. If you want to dive deeper, have a look at how content marketing influencers are using ChatGPT. 

If you’re an Optimizely user (like we obviously are), you’ll get access to Opal, the AI assistant we built to accelerate the entire marketing lifecycle. We launched our copy generator for Web Experimentation this year, which reduces time and effort in coming up with new ideas and covers all your bases by testing ideas you might not think of (or ideas you’re biassed against). 

Read more about copy generators for Web Experimentation. 

A word on the elephant in the room: 

There’s still some fear that Google is going to penalize the use of AI content. The consensus so far is that you won’t be punished just because you used automatically generated content. So, if you get a blog across your desk that clearly came from a tool, you don’t have to panic. 

With that said, quality remains the key guideline Google judges. If your content is valuable and relevant and follows the same principles you use today, then it’s all good. 

Where you’ll run into issues is if you pursue quantity over quality with poor, irrelevant, or duplicate content. But the same penalties already apply today. 

So, if you’re using tools to improve content that’s tied back to your strategy and you’re not using content to spam Google, then you’re all good. 

Gartner predicts that, someday soon, using human-generated content is going to be a differentiator, but it’s still very early to understand what will dominate the next few years. Having both skills is a must for the foreseeable future, and it’s nothing to be afraid of.

2. Create a video production house

We’re inspiring, educating, and selling with video—and we’re now doing it all in under 30 seconds.

ICYMI, 2023 was the year big brands started throwing resources at ultra-short form video content, and the early results suggest that we’ll see a lot more of it in 2024. 

The rise of YouTube shorts and its early adopters like Nike have shown impressive results, and that’s great news for content marketers. It hasn’t just scored improved conversions and engagement, but according to Think with Google, it costs less! Truly a way to do more with less that isn’t painful. 

Some compelling stats: 

Does growing interest in video make you feel like you’re in a hostage situation? Do you say “yes I do video” in the least convincing voice possible, knowing you’ll owe your design friends a favor? Or is it just me? 

Spending more time on video is way less daunting than it used to be, particularly if you’ve got a strong game plan to work from.  

Among a few of the web tools that will finally allow you to confidently create videos to your heart’s content (regardless of your level of video production experience): 

  • Descript lets you edit videos by editing the script, perfect for those who love words but not timestamps (plus, it works for podcasts, too!) 
  • Fliki takes the sting out of video creation with AI voices that never say “um” in 75+ languages 
  • Visla turns a script into a new video so you never need to learn how to edit a video 
  • Opus Clip takes your feature length film (if you’re like us) and creates a marketing sizzle reel (purpose for repurposing keynotes, full demos, and more) 

3. Data and analytics 

Every strategy comes with success metrics, and we can debate all day about the most effective content marketing KPIs, but one thing will remain true in 2024: we’ll need to share that data. 

But data and analytics are getting so much easier than they used to be. With tools like Whatagraph and Supermetrics, you can pull together your content data in minutes from places like Ahrefs, GA4, Hubspot, and anywhere else your content data lives. 

For me though, the joy of these tools isn’t just in the time saving and the superior visualization. I can also ask ChatGPT to help me interpret it (only available as the Marketing Data Analyst GPT via ChatGPT Plus at present). ChatGPT is perfect for simplifying enormous datasets generated by our big marketing websites and funnels. It doesn’t replace all my context, but it gets me started much faster and can sometimes pick up things I miss. 

If I’d had this tool when I first started, I would have spent far less time wondering and more time doing (and probably negotiated more raises).

Here are a few resources to get you started: 

The tool: 

The tricks: 

P.S. Don’t forget about the individual data tools now available for different mediums. In fact, before you do anything, go have a browse of all the AI tools currently available if your mar-tech stack and in its periphery. Some of them will be ChatGPT rolled up into your existing product, but you’ll also discover tools like Podder, which helps you build out in-depth podcast demographics so you can create content that they want. 

4. Reinvigorate your podcasting dreams

The state of podcasting is, some say, very much up in the air. 

Podcast listenership is only going to keep growing in 2024, particularly in Latin America where double-digit growth is still happening. Plus, the big networks remain positive about the medium, despite some pretty significant failures that ultimately led to layoffs at Spotify, Wondery, and iHeart Media in 2023 

And those same executives at the big media groups think 2024 is going to be the biggest year yet, in part thanks to AI. And that’s probably the one thing that we (me) and those executives have in common. 

The year 2024 can be the year you finally take the leap into podcasting—or revive the dormant podcast you had back in 2020. Why? 

AI can help you do the heavy lifting with your podcast so you can focus on making it the best it can be in your category. You’ll get tools for creating scripts, editing and processing, and even distribution. Even better, you can follow the lead of the industry and use your podcast to reach global audiences (customers) with the help of these tools. 

But for longevity, quality, and a bit more fun: where does a podcast fit into your content strategy in 2024? Where does it fit into the wider marketing strategy and more importantly the budget? These questions are more important than deciding the topic for your comeback episode. Because without distribution and buy-in from your teams, you still run the risk of shouting into the void.  

Once you know, these AI podcasting tools will change everything for you: 

  • Wisecut will cut and edit videos that are social media ready directly from your podcast
  • ChatGPT or Jasper can put together a basic script for you to edit
  • Podcastle will create better quality recordings and simplify your editing
  • Clean Voice cleans up your content by eliminating filler words, silences, and stuttering 

Here’s to 2024 

Call me a dreamer, but I see great things for content marketing in 2024. Getting by with a little help from new AI tools to augment the busy-ness that gets in the way of perfecting our strategy and taking more creative risks is the different between January 1, 2024 and this time last year. 

I’ll be back midway through the year to let you know how I’m getting on, but all going well, you’ll see the product of my eternal optimism across Optimizely’s marketing. More experimentation, more data, and more chances to really lean into this year’s trends. 

 

 


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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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