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For Better Content Marketing, Listen First, Create Last

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For Better Content Marketing, Listen First, Create Last

I write and talk a lot about creating content. But learning how to listen is just as (if not more) important.

Think about that last Zoom meeting you had. Your coworker was talking about the state of the business, the results from last quarter, or the proposed new project, and you had this internal dialogue going on as you nodded at the camera.

“Wow, that’s a lot of data she just laid out. Do I agree with it? Which statements should I respond to? Should I ask a question now? How about now? I’m ready with an answer. What should I say to sound smart? I wonder what time the dry cleaner closes.”

We hear, but we’re not listening.

Hearing is a simple physiological act. But listening involves taking in the meaning of the words and the implied communication in the silences in between.

As Henri Nouwen put it, “Listening is much more than allowing another to talk while waiting for a chance to respond.”

Most marketing involves waiting to speak

In the latest CMI research, 68% of all respondents said they prioritize their audience’s informational needs over the organization’s sales message in content marketing.

But when asked about looking forward, content marketers mentioned understanding what content appeals most to different roles within the target audience as their top challenge.

In other words, they want to say something meaningful, but they don’t know what that might be.

Research shows #Content marketers want to say something meaningful – they’re just not sure what that might be, says @Robert_Rose via @CMIContent @semrush. Click To Tweet

Many of my clients feel confident that the company they work for knows what kind of content it wants to produce for audiences. But they feel less convinced that the company understands what these audiences want.

Too often, content marketers are waiting to speak (or offer content) rather than listening to what’s happening with the audiences we’re trying to serve.

Here’s an example. The marketing team at a B2B IT services firm I worked with a few months ago sends leads to the sales team based on the number of articles or thought leadership papers a visitor downloaded. In one case, an audience member had downloaded two papers in one visit to the site. Conversion triggered!

The algorithm automatically tagged this person as a lead, and sales got the notification to call. The salesperson felt frustrated when the “lead” indicated she had no intention of buying and wasn’t even convinced she needed to change.

In this case, the prospect was saying, “I’m trying to understand this concept, and I have unanswered questions about why I would change.”  But marketing was waiting for the chance to say, “Great, thanks for all that information. How much change would you like to purchase today?”


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Active listening isn’t a technology problem

You may know that the answer to the “waiting to speak” challenge is active listening. This skill involves concentrating on what someone says, responding to it, and remembering it. Research shows that active listening can improve relationships, promote deeper trust, and motivate those we communicate with.

Many modern marketing technologies promise to help deliver more relevant, personalized content experiences. Some even say they use artificial intelligence to examine a customer’s content consumption and present the “best next” experience.

Don’t be fooled. Personalization isn’t active listening. While it removes some friction for some areas of the customer’s journey, personalization is just a faster way of waiting to speak.

Personalization isn’t active listening. It’s just a faster way of waiting to speak, says @Robert_Rose via @CMIContent @semrush. Click To Tweet

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Real active listening in content marketing

One of the most profound lessons I’ve learned in nearly three decades of marriage is to listen with no intention of fixing something. A critical component of active listening is to be present but resist the urge to improve, repair, or have a prepared response to the information given.

This may be one of the hardest things for marketers and sales practitioners. Most of us are trained to provide the next piece of compelling advice to fix a customer’s challenge or serve a need or want.

Active listening means resisting the urge to offer a prepared response – and that’s hard for sales and #ContentMarketing teams to do, says @Robert_Rose via @CMIContent @semrush. Click To Tweet

But listening to customers without the intention to prepare a response offers real value.

Here are some ways you might employ an active listening approach in your content marketing.

Polls and surveys

It’s easy to get so wrapped up in trying to find data to support your decisions that you succumb to the temptation to make every survey question multiple choice. Even “Rate this article” widgets at the end of thought leadership pieces offer a scale from 1 to 5 to feed an algorithm or analytics tools. Consider running polls or surveys where the questions are open-ended and designed to foster understanding rather than being able to serve up a chatbot response or other piece of pre-programmed content.

Customer persona interviews

Persona interviews often get lumped in with buyer research. The questions become about listening for opinions on products, services, or the brand. But customer or audience persona interviews should include fewer questions about what they think about us and more about what they think. Full stop.

Registration forms

Instead of asking visitors for an email address, name, and phone number in exchange for a digital asset, why not ask the recipient something that doesn’t require identifying information? For example, instead of requiring an email address for your latest white paper, just ask people: “Tell us why you’re downloading this paper.”

Each of these approaches can return valuable information to fuel your marketing and personalization efforts.

By actively (and consistently) listening to our audience personas, you can make better decisions about the what, where, and when of the content you create.

You can also better inform others in your business who may be still just waiting to speak. Active listening with your audiences can empower you to know when, where, and how to cue the many business voices to speak with greater intention.

That’s when your marketing can evolve from simply saying something to having something valuable to say.

Get Robert’s take on content marketing industry news in just three minutes:

https://www.youtube.com/watch?v=videoseries
 

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

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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