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MARKETING

What it is and why marketers should care

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What it is and why marketers should care

It’s been said, ad nauseam, that content is king. But these days, a more accurate statement is probably: customer experience is king. And, in our hyper-connected world where everyone is fighting for attention, good content is what drives good experiences. 

Businesses use content marketing strategies to generate brand awareness, educate prospects and customers and establish credibility. Increasingly, delivering a good customer experience means delivering relevant, personalized content to customers in a way that works for them. Providing the content customers need when they’re ready for it ultimately leads to better outcomes for marketers.

That means scaling content so it’s always fresh, relevant and personalized across the many touchpoints consumers use when interacting with businesses. 

How important is personalization in content marketing? About 71% of consumers expect businesses to deliver personalized interactions, according to recent McKinsey data. Nearly three-quarters of people will look elsewhere for whatever item or service they need when this expectation isn’t met.

In this post, we’ll cover:

Estimated reading time: 7 minutes

What is content marketing?

Content marketing is a marketing approach or discipline that relies on developing various content types and assets focused on getting people to act (e.g., sign up for a newsletter, place an order, ask for more information, etc.) 

Unlike paid advertising, content marketing primarily uses organic approaches to attract and engage customers. Content, in this context, includes written or visual assets (e.g., guides, articles, blog posts, graphics, videos, social posts, etc.) But paid content promotion sometimes factors into content marketing – for example, sponsored content on publications or gated content that requires a fee to access.

Content marketing is closely linked to inbound marketing and other customer experience-based approaches. It’s often used as a top-of-the-funnel tactic to attract prospects and turn them into leads or customers. Still, it can also be used to nurture existing relationships and convert leads into customers. 

The Content Marketing Institute’s (CMI) official definition of content marketing is:

“A strategic marketing approach focused on creating and distributing valuable, relevant and consistent content to attract and retain a clearly defined audience — and, ultimately, to drive profitable customer action.”

There are three types of content marketing models which include:

  • Paid: Content sits behind a paywall or requires some sort of purchase to access.
  • Owned: Content is produced by a business and published on its own channels (e.g., website, blog, social media).
  • Earned: Content is published by someone other than the company (e.g., user-generated content, influencer content, media coverage, etc.).

Regardless of where your content lives or lands, there are two unifying features that define a good content marketing strategy — relevancy and quality.

Why marketers should care about content marketing

The consumer buying cycle is an increasingly self-serve process scattered across multiple touchpoints. To adapt to consumer expectations and keep up with competitors, marketers must create a large volume of high-quality content that can be effectively shared across many different channels. 

Standing out in this cluttered content ecosystem requires producing personalized content at scale. Content automation tools and platforms allow companies to produce, manage, share and amplify content while facilitating scalability. In short, you need content to compete in today’s customer experience-driven landscape and technology to produce content at the volumes required to make an impact.

How effective is content marketing?

About 91% of companies said they achieved some level of success with content marketing in 2021, according to Semrush’s 2022 State of Content Marketing Report. Most respondents said they planned to increase content budgets and hire more content talent in 2022. 

Currently, content marketers measure success by looking at traffic, search rankings and leads. But this is changing. Content marketers are increasingly focused on other measures like engagement, conversion rates and ROI. Of course, there are tech tools that help with this. 

For example, customer journey analytics tools, such as Qualtrics, monitor every customer interaction with a company and analyze how each piece of the journey contributes to action, like a sale, conversion, or request for information. 

Journey analytics evaluates every piece of content a customer interacts with across the entire buying cycle and assesses how it impacts a measurable outcome (e.g., a sale, new customer, conversion, etc.)

Who uses or works with content marketing tools?

The most common teams that work with content marketing tools are those that deal with driving website traffic, engagement, leads and sales. This includes:

  • Marketing: Content is used to attract prospects and turn them into leads at the top of the funnel.
  • Sales: Content is used to accelerate the sales process by providing prospects with the information they need to make a purchase.
  • Customer experience: Content helps reduce customer churn and drive upsells/cross-sells by keeping customers engaged post-purchase.
  • Support and service teams: Content helps reduce the number of inbound support requests by proactively addressing common customer questions and issues.

Some job roles that work with content marketing tools include:

  • CMO: Guides content strategy and works with other C-level executives to establish content goals.
  • Content manager: Oversees content creation and distribution.
  • Content planner: Executes content strategy and plans content calendar. 
  • Content writer: Creates content. 
  • Editor: Reviews and approves content. 
  • Designer: Creates visuals to accompany content. 
  • Marketing analyst: Tracks and reports content marketing performance metrics.
  • Sales manager or agent: Uses content to support the sales process.
  • Customer success manager or agent: Uses content to keep customers engaged.

What types of tools or software enable content marketing?

A wide range of tools and platforms exist to help businesses create, distribute, target and measure the content they create. They include:

  • Content management systems (CMS) like HubSpot and Joomla let companies create, store and manage website content (e.g., webpages, blog posts, e-commerce product pages, etc.).
  • Digital experience platforms (DXPs) like Sitecore and Adobe Experience Manager provide robust content orchestration features including digital asset management, customer data management, personalization and testing and marketing automation.
  • SEO software like Moz Pro and Semrush provides tools for keyword research, content optimization, link building and SEO rank monitoring.
  • Social media suites like Sprout Social and Brandwatch (formerly Falcon.io) include features like social publishing, campaign optimization and social engagement to improve the reach and impact of posts. 
  • Content intelligence platforms like Ceralytics and Parse.ly help companies track content performance across multiple channels and touchpoints. 
  • Content planning and team collaboration tools like Asana and Trello help content teams manage projects and workflows, share files, create editorial calendars and assign tasks/to-do lists.

How content marketing can help marketers succeed

Gartner notes that companies demonstrating success with growth, margin and profitability typically prioritize customer experience. These companies are nearly 30% more likely to have higher CX budgets and focus on the entire customer journey, including what happens after a prospect becomes a customer.

Content plays a role in every stage of the customer journey — from attracting prospects to building relationships with customers. The payoff is high for businesses committed to delivering personalized interactions driven by high-quality, relevant content.

Fast-growing companies drive 40% more of their revenue from personalization versus their competitors, a recent McKinsey report revealed.

Consumers respond to this approach. That is, they want personalized, relevant content from businesses. Per McKinsey, nearly 80% of consumers said personalized content was a key factor in their decision to purchase or repurchase from a brand.

Getting it right means creating content at scale. Content powered by AI will be a key driver of personalization. Brands that have fully invested in content marketing are now turning to AI to create more personalized content experiences for their customers.

What’s next for content marketing

Globally, the content marketing industry is projected to reach 9.6 billion by 2023. The industry’s dominant players include Oracle, HubSpot, Adobe and Salesforce, but content marketing encompasses many types of software and services including marketing agencies, resellers and the technology vendors themselves.

As the demand for high-quality, personalized content continues, content marketing and the tech needed to facilitate it will become increasingly essential for companies of all sizes. The proliferation of touchpoints and devices: the “how” and “where” of the customer journey: is also a key factor in the growth of content marketing. 

Artificial intelligence and content technology will help marketers keep up with the demand for personalized content, automating many of the tasks inherent in content creation and planning. But human ingenuity — and creativity — remains an essential component of effective content creation and strategy. As companies continue refining and improving the customer experience, content marketing will continue to take center stage. 

Additional reading

Here are some resources to help level up your content marketing efforts:


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Jacqueline Dooley is a freelance B2B content writer and journalist covering martech industry news and trends. Since 2018, she’s worked with B2B-focused agencies, publications, and direct clients to create articles, blog posts, whitepapers, and eBooks. Prior to that, Dooley founded Twelve Thousand, LLC where she worked with clients to create, manage, and optimize paid search and social campaigns.

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MARKETING

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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