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3 Ways Artificial Intelligence Can Help Your Content Marketing Processes

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3 Ways Artificial Intelligence Can Help Your Content Marketing Processes

Artificial intelligence comes to fruition by teaching a machine to think and react like a human being.

Google refers to content created with the help of artificial intelligence as automatically generated content, better known as spam. Maybe creative thinking will be something machines can eventually master, but we are not there yet. Machines can’t grasp things like style, voice, and perspective, no matter how intelligent they might be.

Though a machine can’t do creative writing, artificial intelligence can be helpful in your content marketing processes. Here are three ways AI-powered tools can help you make your content marketing more productive:

Artificial intelligence tools can be helpful to your #ContentMarketing, says @SEOSmarty via @CMIContent. Click To Tweet

1. Put together content briefs

Creating a content asset often requires a lot of collaboration. For example, an SEO manager identifies a need for an article to address a popular question, an in-house person does research to create a content brief for the writer to use, and a freelance writer crafts the content.

In a smart process, you also make sure the customer support (and sales team) contribute their thoughts to the content brief (as well as the final article) based on their frontline experience with customers.

In any productive content creation process, a content brief is fundamental.

And this is where artificial intelligence can turn out to be helpful. It can consolidate many data points into one conclusive summary for your team to use.

Narrato uses artificial intelligence to put together semi-automated content briefs. It uses SEO data (relevant keywords and people also ask questions), semantic analysis, as well as input from team members (style guide, notes to the author from different roles, references, etc.) to create a single dashboard for your writer to create content.

@narratoio uses #AI to put together semi-automated #content briefs, says @SEOSmarty via @CMIContent. Click To Tweet

The tool also uses AI-powered grammar checks to help you (or your writer) create more readable, better-structured copy. In this example, the tool suggests changing “a large number of” to a specific number or using “many” or “numerous.”

1665423312 766 3 Ways Artificial Intelligence Can Help Your Content Marketing Processes

2. Diversify your content marketing tactics

Experts say the rule of thumb is to spend 20% of your content time crafting the content and 80% promoting it. This smart rule helps make the most of every piece you write, but it is seldom followed.

Promoting your content on social media requires a lot of time: You need to create diverse copy for your updates, put together attention-grabbing visuals, craft interesting captions, etc. The repetitive tasks often scare away content marketers, so they rely on automation tools that grab the new content from RSS feeds and share them on their social media channels.

Artificial intelligence provides smarter and more productive promotion by helping you create social media copies, captions, and even multimedia content (images and videos).

Text-to-image technology

Photoleap lets you create visual content on the fly. To experiment with the feature, click “Generate AI Image” and enter your text (for example, the name of your article).

1665423312 996 3 Ways Artificial Intelligence Can Help Your Content Marketing Processes

The app will generate an image. You can edit the image if you want. It is the fastest way to create images to diversify your social media content and promote on-site content.

Social media copy

Lately, an AI-powered social media copy creation tool learns based on your update performance and helps you write more engaging updates.

Copy and paste your article URL and select the preferred length of your social media updates. The tool will generate social media captions. You can select the ones to use and easily publish them to your connected social media profiles.

1665423312 992 3 Ways Artificial Intelligence Can Help Your Content Marketing Processes

The tool uses the page title and meta description to figure out the article’s focus and generate captions. However, it also uses on-page copy to inform the AI-created content.

AI-powered @LatelyAI tool uses page titles and meta descriptions to figure out the #content’s focus and generate captions, says @SEOSmarty via @CMIContent. Click To Tweet

Videos

Traditionally considered the most labor-intensive social media content, videos are created more quickly with AI-powered tools.

InVideo uses AI-driven automation to power its “text-to-video” feature. Copy and paste a few paragraphs from your article and upload your logo. The tool will come up with a video including a template, animations, and headlines. You can edit the video if you want.

1665423312 272 3 Ways Artificial Intelligence Can Help Your Content Marketing Processes

3. Proof your content

I mentioned that Narrato provides AI-powered grammar suggestions. But your team creates a lot of content – social media posts, newsletters, emails, etc.

Grammarly is the most popular grammar-checking app that uses AI to learn each individual’s writing habits and provides suggestions based on that style. The tool also learns its interactions with each user. For example, if you tend to ignore the same suggestion, the tool will ultimately learn not to suggest it.

In this example, Grammarly suggests a clarity fix – changing “which results in a very sudden price change” to “resulting in a sudden price change.”

3 Ways Artificial Intelligence Can Help Your Content Marketing Processes

Grammarly offers many integration options. While it can be used in text editors, it also offers a WordPress plugin. WordPress also can host a few more AI-generator plugins, including internal linking and translations that you may find useful and productive.

Maximize your content time with AI tools

Content creators shouldn’t feel threatened by advancing technology. No one can replace human creativity and ingenuity. Artificial intelligence can be a writer’s friend by handling tasks they have no time or skill to handle and letting them focus on what they do best – writing.

HANDPICKED RELATED CONTENT:

All tools mentioned are identified by the author. If you have a tool to suggest, please add in the comments.

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

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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