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Is Your Thought Leadership Stuck in ‘Mutually Assured Irrelevance’?

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Is Your Thought Leadership Stuck in ‘Mutually Assured Irrelevance’?

How is your thought leadership program going?

Is it more thought than leadership? 

Or are the thoughts more like what everybody else is saying?

New research from Edelman and LinkedIn says most thought leadership apparently doesn’t encourage or inspire much thought. It’s also mostly under-resourced and misused. Yet, if done well, it can strongly influence sales and pricing.

What gives? Are B2B marketers failing to use thought leadership at the right part of the customer’s journey? Are you gating too much of it? Are you not talking with the right influencers and subject matter experts in your organization?

Or are you failing to challenge your audience with true thought-leading thinking?

We took those questions to CMI’s chief strategy advisor, Robert Rose, for his take. Watch this video or read on:

In B2B marketing, thought leadership has forever stood front and center of content strategies. Back when B2B marketing was called “industrial marketing,” sales teams developed personal relationships with customers. When buyers needed a new widget or service, they would usually call their most trusted salesperson, who would recommend additional or other solutions from their company.

In those days, sales teams acted consultatively. They knew their industry backward and forward. They invited other subject matter experts in the business to accompany them on customer calls.

When digital came along in the early 2000s, all that changed, and buyers began their research on the internet. In response, businesses launched research programs, using academics to write white papers and articles for business journals. Instead of looking at thought leadership as a key product offering for customers, marketers saw it as a shortcut to get more eyeballs on other marketing content. They got wrapped around the axle of optimizing their websites for search to organically answer the customers’ most frequently asked questions in the most keyword-enriched ways.

In many ways, the last twenty years saw a rinse-and-repeat of that strategy. An inherent tension developed. You want to ensure your B2B brand organically appears at the top of the list for all the most common questions potential customers have about an approach, toolset, industry outlook, etc. Yet, you also want to differentiate yourself from all your B2B competitors who are trying to do the exact same thing.

The net result?

Thought leadership becomes an ocean of different ways to say the best and most common practices. You build content to feel familiar and align with current thinking rather than answering the critical questions no one knows to ask — aka thought leadership.

I call it “mutually assured irrelevance.” Everyone in the industry says the correct thing, but no one helps the customer do a different thing.

Edelman and LinkedIn’s Reaching Beyond The Ready report (registration required) encompasses a survey of 3,500 B2B management-level professionals in December of 2023. They sought to gain insights into the state of thought leadership and how it might do more than increase brand awareness.

Not unsurprisingly, the research found people consume a lot of thought leadership. Over half of decision-makers and C-Suite leaders spend more than an hour weekly with it. Seventy-three percent say an organization’s thought leadership creates a more trustworthy basis for assessing its capabilities and competencies than its marketing materials and product sheets. Both those things are good.

And yet, only 15% of those surveyed think the thought leadership is very good or excellent.

That’s not so good.

The researchers point out that what seems to be missing is the leadership part of thought leadership:

“When done right, it makes buyers look at their business and the challenges it is facing in new ways and protects you from competitors producing their own thought leadership.”

I’ll say it another way. Thought leadership is not about answering frequently asked questions. Thought leadership provides the rarely given answers (RGAs).

The research report indicates businesses don’t understand the measurement of thought leadership and see too few resources as the main barrier to producing more effective thought leadership. About 50% of thought leadership producers say their programs are under-resourced.

But I think the lack of sufficient resources is only a symptom. After all, no marketer has ever said, “I have too many resources and too much money.”

The real challenge is that most B2B businesses still view their thought leadership program as a short-term marketing campaign to generate demand or leads into the top of their funnel. Or they see it as a brand-building effort to attract more attention.

They fail to see thought leadership as a product or service that’s as (or more) important than the products or services they sell in the marketplace.

A great thought leadership program deserves the same level of attention as your best product or service offering. It deserves a PR strategy. It deserves a paid media strategy. It deserves internal comms support.

That doesn’t necessarily mean more money or more resources. (Well, maybe it ultimately does, but that’s not the key.) It means taking the time to make your thought leadership a business strategy, not another market tactic to attract more attention at the top of the buyer’s journey.

As the research points out, an effective thought leadership approach has three key attributes:

  • Shares strong research and data
  • Help buyers understand their business challenges
  • Offers concrete guidance.

That type of thought leadership is based on the intricate understanding of what your customers need, not what they’re asking for. It provides immediate value and is differentiated based on your brand’s take on the world.

In other words, thought leadership is one of your core products. Treat it that way.

Want more content marketing tips, insights, and examples? Subscribe to workday or weekly emails from CMI.

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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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