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5 things martech leaders wish their teams knew

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5 things martech leaders wish their teams knew

There’s something we don’t often talk about in martech: the growing disconnect between martech leaders and practitioners. Many practitioners, the ones managing technology day-to-day, are working overtime to deliver projects and keep the marketing lights on. When this hard work goes unappreciated, these subject-matter-experts move on to another company – hard to blame them. But is this the whole story?

Martech leaders agree that martech professionals and marketing operations are the unsung heroes of the marketing department. But in speaking with them, we learn that the problem of underappreciation doesn’t fully rest on the shoulders of marketing leadership. The issue is multi-faceted, and when asked the question “What are key things you wish martech teams knew?” the responses are quite insightful.

While you may not hear these points out loud or in one-on-one meetings, it’s important to understand the perspective of martech leaders and how they think the problem should be addressed. Here are five key things martech leaders wish you knew.


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1. The perception of the martech team has to be shaped, and it starts with you

The team that owns martech (typically marketing operations) has not always had the best reputation. Other teams have thought of them as the “order-takers” or the “button-pushers,” or even the IT of marketing, another obstacle they have to overcome. While many practitioners complain about this and jump from role to role, hoping the next company will be a different story, they often overlook the proactive steps they can take to change this perception.

Where to start? Start by making sure your current projects are tied to the business’s top priorities. If they aren’t, reprioritize, or find ways to link them indirectly if you must.

Make sure the projects you are working on are top priorities for the business. If not, find out how to link them, at least indirectly. Also, emphasize the downsides or negative impact if these projects are not put in place.

Find an opportunity to show off: most martech professionals may hide behind their technology, but this is the opposite of shaping perception. Put together a quarterly business review, schedule a presentation or start a biweekly newsletter highlighting all the great results martech generates.

2. Understand the dangers of opportunity cost

Here’s an interesting analogy: pretend there is a mix of bills spread across the field, in increments of 100s, 20s, fives, and ones. With limited time, which bills do you go after first?

Unfortunately, many martech teams spend their time working on projects worth fives and ones versus those worth 100s. This example brings stark reality to the meaning of opportunity cost: spending time on something with little value at the expense of pursuing something with higher value.

Nick Bonfiglio, founder and CEO of Syncari, says it like this: “Focus on quality over quantity every time.” To his team of martech operators, he says, “you can test programs that generate engagement, but what I want you to really focus on is initiatives that drive qualified opportunities. Spend your time on projects that will create opportunities with an above 25% close rate minimum.”

Does that mean his team never experiments? Never tries anything new? Quite the opposite, the Syncari team reserves time for innovation. The key difference is they are judicious about the majority of their project work.

3. Translate martech success to business outcomes

Here is another problem that plagues martech teams everywhere: doing great work that their stakeholders don’t understand. Years ago, I spent an entire month migrating a lead routing system from a decentralized model to a single, centralized workflow. After sharing this accomplishment with the larger team, I was met with many blank stares.

What was I missing? I needed to explain how the project would impact their work and the business at large in simple terms. Once I shared how the new lead routing cut their campaign management time by 25% and virtually eliminated all of the lead management errors they were experiencing, they sat up much straighter and appreciated the work being done.

“Figure out what your work will unlock for stakeholders,” says Jessica Kao, director at F5 Networks. “This is what I tell my team: If you are building something or implementing a new tool, communicate how it will translate to more leads, meetings, pipeline and revenue. We might be doing the right things, but being able to tie it back to the business reason is the key to success within an organization.”

Like Jessica says, take a look at your work and explain how it will impact the business. Explain how investments in data will turn into better targeting and better personalization. Articulate how investing in a new platform will improve productivity by 20%. Translate martech work into business results, and you will be on the right track to martech success.

4. Team structure isn’t as important as vision, goals and accountability

Should you organize your team into a revenue ops team or keep sales ops and marketing ops separate? While there are varying benefits for each organization, the truth is that any structure you choose will fall apart without an overarching vision for sales and marketing success.

Here is the truth: at micro-startups, sales and marketing are naturally connected because the entire team is only a handful of members. At the enterprise level, there is a high volume of projects requiring specialization that may not need input from other groups as frequently as with smaller organizations, though alignment is always critical.

You don’t have to be in revenue operations to help sales. “I want my teams to know that it is important to empathize with sales,” says Thao Ngo, SVP of marketing at Allocadia. “Sales is laser-focused on their current deals and don’t have the time to read all of our marketing material. Make it easy for them: summarize key points, consolidate all resources for them in one place, and identify ways for them to hit their targets.”

So what principles should guide us when so many different structures can work? Leaders should set the organization’s vision and goals that are shared widely and operationalized in everything. For example, revenue goals should be set by both sales and marketing, approved by top leadership and broken down into sub-goals that each team commits to. Customer experience goals should be the same way – sales can look at referrals or upsells, while marketing may set CSAT or NPS goals.

Read next: More on marketing operations from Darrell Alfonso

5. If you are constantly drowning in work, stand up and look around

What’s a common refrain from martech and marketing operations teams? That there is way too much work to do in too little time. How do martech leaders respond to this?

“It’s true that martech teams are busy,” says a top executive at a mid-sized SAAS enterprise. “But to be honest, everyone in high-growth organizations has too much to do. Effective teams will carefully weigh the different initiatives in front of them and focus their energy on where they can get the most return on their money and time.”

Unfortunately, while it is true that marketing operations teams everywhere could use more resources, many are spending time on low-value tasks.

My recent LinkedIn post on the importance of prioritizing high-value tasks at the expense of low-value tasks was met with general agreement, but there were one too many comments, such as:

“Well, what if my low-value projects turn into high-project later on?” and “It’s not all about the numbers, you know.”

To that, I can only sadly shake my head – any effective leader knows that low-value projects don’t magically turn into high-value projects, and those that do were not scoped and appraised correctly. It’s hard to truly look at your work, evaluate projects’ impact, and make hard decisions to determine what you will and won’t do. Making smart tradeoffs is an effective leader’s mark, especially in martech.


About The Author

5 things martech leaders wish their teams knew
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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