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Why You Struggle To Prove Content ROI

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Why You Struggle To Prove Content ROI

Measuring content ROI is a near impossible task.

Too often, that statement ends the conversation about proving the value of content marketing. But the difficulty in tying content directly to the bottom line doesn’t mean content marketing isn’t a contributor to a business’ success.

The failure to understand that too often leads to the demise or weakening of content marketing support.

Why is the ROI of content marketing so problematic? Because the premise too often is that content marketing should feed directly to the bottom line. Many see the “return” in ROI as synonymous with “sales revenue.”

Sound familiar? If that’s the challenge you face at your brand, let’s explore a few options to overcome it.

Traditional #ROI may be difficult to prove– but it’s still worth it to explain #ContentMarketing value in business terms, says @AnnGynn via @CMIContent. Click To Tweet

Think about why you’re measuring content’s value

A couple of years ago, Ahrefs CMO Tim Soulo shared a tweet thread listing the benefits the company knows it gets from its content marketing. Yet Ahrefs never intertwines return on investment and content marketing. Here’s how he explained why they don’t:

“We won’t track how many leads we get from our articles organically, let alone what is the CPA of running paid traffic to our articles. Measuring those things would be just the tip of the iceberg,” he wrote.

“And let’s say we measured those numbers and they turned out terrible …? We wouldn’t halt our content marketing operations anyway! We KNOW that it works for us, no matter what those ‘isolated’ numbers say.”

It’s a great lesson in measurement. Think about what will change based on the numbers. If the answer is nothing, consider measuring something else.

But most executives expect numbers. And content marketing leaders need to provide them.

Explain content marketing (and marketing content)

Even people who work in marketing get confused about the difference between content marketing and other content used in marketing. No wonder executives operating outside marketing wouldn’t know the distinction.

Before you try one of the options below, consider hosting a conversation to explain the difference between content used in marketing and content marketing to key stakeholders.

What’s content used in marketing?

Content used in marketing usually focuses on the sale. Think product pages, sales promotions, customer service instructions, ads, and other content designed to lead to a transaction – a sale.

What’s content marketing?

As CMI defines it, 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.

Think blogs, newsletters, guides, video and audio shows, and other content designed to inform, educate, or entertain. Sales aren’t the immediate goal (though, of course, they can and should be part of the “profitable customer action” that’s the ultimate goal.)

Content marketing aims to build an audience. Some of the people this content attracts will convert to customers. But those conversions represent only part of the value content marketing offers.

The audience represents an asset with quantifiable value, says Robert Rose, CMI’s chief strategy advisor. (Robert explains how to model the value of the audience asset in this article.)

Start with (what else?) specific goals

Though you can prepare your execs to think beyond traditional ROI assessment, you need to show how you’ll measure your content marketing’s impact.

Start by setting appropriate goals for your content marketing program. It’s not enough to say, “increase brand awareness” or “educate audiences.” Be specific: identify the goal, the target audience, the metric used to measure progress, the number you strive to achieve, and the timeframe in which you plan to complete it.

Here’s an example of a goal that covers each of those elements:

Our content marketing goal is to increase brand awareness online among women between the ages of 25 and 45. We intend to achieve a 10% increase in unique visits to our blog from this group in each quarter of 2023.

TIP: Make sure your content marketing goals align with your brand’s business goals. The example above only makes sense if the brand’s business goal is to increase sales within that target audience.

The more you speak the language of business, measurement, and success, the more likely business leaders will understand these essential points: Content marketing isn’t easily evaluated by traditional ROI. But it’s not far from a fuzzy nice-to-have – it’s vital to the business.

Make sure you use business terms to describe the value of #ContentMarketing, says @AnnGynn via @CMIContent. Click To Tweet

Redefine your content marketing strategy

CMI’s annual research shows the same top three goals for content marketing year after year: brand awareness, building credibility/trust, and educating audiences.

In our most recent study, at least 72% of marketers cited those goals.

In the same survey, sales-related goals ranked further down the list. Here’s how they factored for B2B marketers:

  • 5 – generating demands/leads (67%)
  • 6 – nurture subscribers/audiences/leads (54%)
  • 8 – generate sales/revenue (42%)

If you must operate under the premise that a return on investment means how your content marketing affects your bottom line, adjust the goals of your content marketing strategy. Focus on leads and sales.

If you make this switch, remember that your editorial approach will need to change, too. Don’t forget to adjust your metrics to align with your new goals. Website traffic and social media analytics shouldn’t be at the top of your list (they might not even be on your list.)

Invest in an attribution model

Of course, content marketing should have an impact on revenue. After all, why do it if it isn’t helping the business? But it’s not a direct line.

If your executives expect you to connect the dots to the bottom line, you must invest resources – experts, tools, and time – to develop a multi-touch attribution model.

By taking this route, you can keep using your current content marketing strategy until the data tells you it isn’t working for your brand’s business goals.

The first component to invest in is someone who loves data. Interest in content marketing is a secondary requirement. (Traditionally, too many content marketing teams make metrics an afterthought or last step in strategy and hiring.)

Look for someone who appreciates solving analytics puzzles and knows how to translate numbers into useful data for the content marketing team and the company’s executives.

A few years ago, Content Marketing World speaker Katrina Neal shared the three analytics categories where data scientists can be helpful:

  • Descriptive (what’s happened)
  • Prescriptive (what’s happening in real-time/near future)
  • Predictive (what’s going to happen and how you should react).

Once you have analytics talent in place, your team is ready to develop an attribution model for your content marketing. An attribution model follows a person’s content touchpoints and what actions they take.

This illustration shows a multi-point attribution model that reveals a person downloaded an e-book, read an email newsletter, had a badge scanned at a trade show, and attended a webinar before becoming a customer. (You can read more about this model in Pawan Deshpande’s article Marketing Attribution Models: A Primer for Content Marketers.)

1673570458 289 Why You Struggle To Prove Content ROI

Some companies use a single-touch attribution model that gives all credit for the sale to a single interaction (even if the customer has interacted with the content in multiple ways.) For example, say the person in the example above becomes a customer, buying $280 in products. In attributing the sale, a single-touch model would designate the webinar attendance as the only touch that matters. Thus, the webinar attendance value for that person would be $280.

TIP: In a single-touch model, the first or last touchpoint usually gets credit for the value.

A single-touch attribution model is better than nothing, but it doesn’t work for a comprehensive content marketing program. A multi-touch attribution model better reflects the value of interactions over time, which are the hallmark of a content marketing approach.

A multi-touch attribution model better reflects the value of interactions over time, which are the hallmark of a #ContentMarketing approach, says @AnnGynn via @CMIContent. Click To Tweet

With multi-touch attribution, a $280 sale gets attributed to four content marketing tactics. Using a linear multi-touch model, each tactic has the same value – $70.

In a weighted multi-touch model, the values vary based on the perceived importance of each touchpoint. For example, you might set up your model to assign 30% of the value to the first touch (in this case, the e-book) and 15% to reading the newsletter. The tradeshow interaction gets 20%, and the last step before the sale – webinar attendance – gets 35%.

In this model, each content marketing tactic has a dollar value – an indicator of its contribution to the sale.

This multi-touch attribution model I’ve used here focuses on a single sale. But you can create more complex variations of the models that look at lifetime value, repeat customer value, and so on.

Pivot from content marketing

If a strategy overhaul or a better approach to analytics and attribution modeling won’t work for your brand, stop doing content marketing. You’ll never have the long-term support necessary for success. Content marketing – building and growing an audience – takes time. (CMI founder Joe Pulizzi has estimated it takes at least 12 to 18 months to show results.)

It takes 12 to 18 months to build an audience with #ContentMarketing, according to @JoePulizzi via @AnnGynn @CMIContent. Click To Tweet

Shift your content marketing resources to focus on content created for general marketing purposes. By focusing your resources on that type of content, you can better connect your work to the bottom line – and get the necessary, ongoing support from leadership.

And if you want to bring content marketing back into the fold (or keep your existing audience), figure out how to create a minimum viable content initiative that can happen alongside the team’s marketing content work.

If you can show that marketing significantly impacts the bottom line, the executive team is more likely to support your content marketing MVP – and possibly more down the road.

Need more guidance to hone your content marketing skills? Enroll in CMI University and get 12-month on-demand access to an extensive curriculum designed to help you do your job more effectively.

HANDPICKED RELATED CONTENT: 

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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