Connect with us

MARKETING

How a Weak Point of View Sabotages Your Content

Published

on

How a Weak Point of View Sabotages Your Content

Did you read the open letter from The Future of Life Institute?

That call to pause AI experiments more powerful than GPT-4 emerged a couple of weeks ago, and more than 6,000 academics and business leaders have signed it.

This fascinating read offers a takeaway that has nothing to do with AI. The letter demonstrates how a well-meaning and even learned team of communicators can sabotage their message.

Let me explain.

An open letter from @FLIxrisk demonstrates how communicators can sabotage their message, says @Robert_Rose via @CMIContent. Click To Tweet

Don’t craft weak and toothless content

Business writer and former Forrester analyst Josh Bernoff called the letter weak and toothless, filled with “passive voice statements about stuff that should happen, with no indication of who should do it.”

I agree. For example, the authors write:

Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. This confidence must be well justified and increase with the magnitude of a system’s potential effects.

Put more simply: Developers should only do things they are confident will produce a positive result with manageable risks.

No one could debate that opinion or possess a different point of view. But that statement fails to explain what needs to happen.

The rest of the letter reads similarly vague and pointless. In fact, the actual verbiage asking for a pause feels so surprisingly confident that it seems like a last-minute addition:

(W)e call on all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4. This pause should be public and verifiable, and include all key actors. If such a pause cannot be enacted quickly, governments should step in and institute a moratorium.

Therefore, the uniquely specific CTA stands out in a bad way. As the only actionable item in the letter, it fails to prompt a broader response – something every thought leadership piece should ask: What’s the best next experience for the reader?

The authors sabotaged themselves. To have the next best experience, readers must agree or disagree with the requested pause on giant AI experiments. Is that what the authors hoped for readers to do? Did they want the pause to be the only action taken after reading the letter (it seems to be given the resulting coverage)? Or did they want readers to take steps to address the complex and important challenges the authors brought up?

The writers fell into a common trap experienced by publishers of B2B white papers – their thought leadership is just a series of general benefit statements. I recently read a white paper from a telecommunications company in which the authors made the main point in the introduction:

Fiber cabling makes the best sense for modern commercial buildings, because today’s modern infrastructures need to be managed efficiently and in ways that meet the needs of new technology.

These frequent generic takes in business often happen when several subject matter experts contribute to the piece. The SMEs may want to present a point of view, but they don’t want customers or other SMEs to disagree with the content. In other words, they position things that are generally right, so little risk exists of them being specifically wrong.

Questions to prompt your specificity

In his book Good to Great, author Jim Collins talks about the hedgehog concept:

It’s not a goal to be the best, a strategy to be the best, an intention to be the best, a plan to be the best. It is an understanding of what you can be the best at. The distinction is absolutely crucial.

Marketers should apply that thinking to thought leadership. A vice president of content marketing at a technology company recently shared the extraordinary turnaround in their program. They discovered an area of content that none of their competitors covered. “We got specific, prescriptive and went out on a limb to talk about it because we knew we could be the best in the world at it,” they told me.

Don’t set a goal to be the best. Instead, understand what you can be the best at, says @Robert_Rose via @CMIContent. Click To Tweet

As you develop your thought leadership program, ask these questions to avoid the trap the authors of the AI-pause letter found themselves in:

  • What is our organization deeply passionate about? This answer seems like a no-brainer because your organization’s passion should feed the content engine. But, as the AI-pause letter demonstrates, expressing that passion in thought leadership can get tricky. The word “passion” suggests you have a distinct point of view and do not equivocate about things. It means as much as you’re willing to be generally right for some people, you’re also willing to be specifically wrong for others.
  • What can we be the best in the world at leading? What place can we be specifically prescriptive? As my colleague, Joe Pulizzi, says, “No successful media company sets out to be the fifth-best magazine or third-best news network.” Just because your business possesses competency in a vertical doesn’t mean you can or should provide thought leadership in that area. As Collins suggests, a critical distinction exists between asking yourselves where you can be the best rather than plotting where you should be the best.
  • What is the best next experience for our audience? If your audience gets terrific value from your content, what specific thing do you want them to do next? How might they “pay” you for that content? Might they raise their hands as active leads? Might they stay subscribed to your service longer? Might they be better served and decrease your service costs? Might they provide you with such rich, accurate data that you could better target your advertising and drive down costs? Might they literally pay you for that content?

Combined, these three questions form a sort of Venn diagram. Your thought leadership program lies where your answers overlap.

How much better could that AI letter from the Future of Life Institute have been if, instead of asking for a pause, the authors gathered their community, aligned on a “manifesto,” and presented the strong, actionable, and meaningful changes they purport to want to see in the world of AI?

If they had followed that up with a call to action for an event (I hear Paris is lovely in April) to discuss and finalize this manifesto as a prescriptive plan made achievable only by taking a pause in AI development, I think it would have made for a more robust and interesting discussion.

The more detailed CTA might have met with just as many objections, but at least they would be discussing the right things.

It’s your story. Tell it well.

Subscribe to workday or weekly CMI emails to get Rose-Colored Glasses in your inbox each week. 

HANDPICKED RELATED CONTENT:

Cover image by Joseph Kalinowski/Content Marketing Institute



Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address

MARKETING

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

Published

on

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!

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

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

Published

on

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

Amazon pillows.

(more…)

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

MARKETING

A deeper dive into data, personalization and Copilots

Published

on

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.”

Source link

Keep an eye on what we are doing
Be the first to get latest updates and exclusive content straight to your email inbox.
We promise not to spam you. You can unsubscribe at any time.
Invalid email address
Continue Reading

Trending