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Is martech in a revenue bubble and how soon will it burst?

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Is martech in a revenue bubble and how soon will it burst?

Fasten your seatbelts. This article will be hotly debated. 

The martech industry is actually in a revenue bubble, like the dot-com bubble of 1995 and the housing bubble of 2008. And there’s no telling how soon it will burst. 

The revenue bubble happens when go-to-market teams, and the technologies they use, organize as one central group with one goal: Sales. The role of the chief revenue officer and the function of revenue operations emerged from this.

The problem? What started as a rallying cry for marketers to drive more impact has sadly devolved into a sea of sameness, with business brands that are eerily identical in how they look, sound, and engage customers. 

Before you get too upset, hear me out.

As a career B2B marketer, I’ve always been a champion of revenue. One of my favorite books is “Revenue Disruption” by Phil Fernandez, co-founder of Marketo. Every activity should lead to a sale! That was the motto. 

But the more I worked in marketing, the more I started to see that some of the best companies didn’t focus on revenue alone. There was more to their success, which we’ll explore in this article. 

Without revenue, what’s the point?  

Here’s why the revenue movement became popular. Marketers were tired of being treated like sales assistants. They were sometimes referred to as the arts and crafts department. I’ll admit, the revenue movement did a fine job in changing this perception.

The problem? The focus on revenue is short-term. 

And I may be biased, working for a company that obsesses over customer experience at the expense of short-term profits, but let’s look at both sides. 

Three powerful, durable spears pierce the revenue bubble. They are community, product-led growth and brand.

1. Community

Community is not, and never should be, about revenue. And while you can tie some attribution to community-led efforts, trying to extract money out of a community is inauthentic. Customers can smell inauthenticity. We’ve often seen members abandon communities that try to milk them for every last cent. We’ve also seen communities help skyrocket companies to become market leaders. Marketo and Salesforce are great examples, but there are many others. There are different skills and competencies required to grow a community, which revenue-focused operators may lack. 

2. Product-led growth 

Product-led growth refers to creating such a good product experience that users refer others, which becomes the primary method of adding new customers. The focus here is obsessing over user behavior and feedback, and implementing quick changes. A short-term focus on revenue (closing big deals) can be counterproductive to this effort. 

You’ve probably seen this first-hand in your organization. A team has dozens of planning and negotiation meetings with a vendor, only to discover that employees have already started using a different platform they paid for with their credit card. 

That’s not to say that enterprise sales and field marketing are irrelevant. Both can drive tremendous growth and awareness. However, product-led growth is tangible proof that there is more to the story than mere revenue. 

3. Brand 

Branding is the most obvious contradiction to the revenue movement. It’s incredibly difficult to attribute deals to branding. You can track branded search terms or ask, “how did you hear about us?” but much of the influence that brand has occurred without our knowledge. Branding is what happens when a buyer needs something at the moment, and your company is top of mind. Brand transpires when a buyer doesn’t make a rational decision based on facts but emotion. 

For example, I selected my car insurance provider solely because I liked the jingle “Nationwide is on your side.” Such a good tune! As a final example, take 10 seconds and think of your top three favorite companies. Got them? Now the question: Do you think they got to where they are today by aligning around revenue? 

The problem with every employee having the goal of revenue 

The problem with everyone having a revenue goal is that other critical aspects, such as customer experience, can fall to the wayside. Not to mention the historical examples of immoral company leaders who focused on revenue above the customer and drove the company’s reputation and stock price into the ground. 

But let’s take a practical B2B approach. Should graphic designers be given a revenue goal? What about corporate communications? What about legal and those who protect the security of customer data? And to take it a step further, if those roles do not have revenue goals, does that mean that those roles are unimportant? 

Here is where the revenue bubble begins to burst because if everything should be about revenue, nothing else matters. 

But other aspects of business do matter. And successful brands know that very well. 

How to stop the revenue bubble from growing and bursting

The solution to the revenue bubble is tension. Healthy tension, healthy debate and a natural, productive conflict that forces one side back into balance when it gets out of line. Should there be a revenue goal? Yes. But there should be a customer experience goal set in parallel. Customer experience can be measured by satisfaction, NPS, engagement, opt-out, and other indicators that show customers like (or dislike) your brand. 

Should there be a new sales goal? Of course. But in parallel, there should be a community-growth goal, a branding goal and a product goal not tied to sales. 

Balance your revenue goals with the customer experience and balance sales with your brand. 

To sum up, while companies have benefited from the alignment that the revenue movement has created, they need to be careful not to lose sight of the less measurable aspects of the business that can differentiate a brand in the long term. And while many operators are looking to revenue as the single answer to solve their business problems, the reality is that business, like life, rarely boils down to a single thing. 


About The Author

Is martech in a revenue bubble and how soon will
Darrell is an award-winning marketer and Martech professional. He was named one of the top Martech Marketers to Follow in 2020, won the Fearless Marketer award in 2018, is a 2X Marketo Champion, and is a certified Salesforce Administrator. He has consulted for several Fortune 500 companies including General Electric and Abbott Laboratories and currently leads marketing operations at Amazon Web Services where he helps empower hundreds of marketers to build world-class customer experiences. Darrell is a frequent speaker at martech events, and regularly posts thought leadership content on Linkedin and Twitter.


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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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