MARKETING
Being position-less secures a marketer’s position for a lifetime
On March 20, 2024, the Position-less Marketer was introduced on MarTech.org and my keynote address at Optimove’s user conference.
Since that initial announcement, we have introduced the term “Position-less Marketer” to hundreds of leading marketing executives and learned that readers and the audience interpreted it in several ways. This article will document a few of those interpretations and clarify what “position-less” means regarding marketing prowess.
As a reminder, data analytics and AI, integrated marketing platforms, automation and more make the Position-less Marketer possible. Plus, new generative AI tools like ChatGPT, Canna-GPT, Github, Copilot and DALL-E offer human access to powerful new capabilities that generate computer code, images, songs and videos, respectively, with human guidance.
Position-less Marketer does not mean a marketer without a role; quite the opposite
Speaking with a senior-level marketer at a global retailer, their first interpretation may be a marketer without a role/position. This was a first-glance definition from more than 60% of the marketers who first heard the term. But on hearing the story and relating it to “be position-less” in other professions, including music and sports, most understood it as a multidimensional marketer — or, as we noted, realizing your multipotentiality.
One executive said, phrasing position-less in a way that clarified it for me was “unlocking your multidimensionality.” She said, “I like this phrase immensely.” In reality, the word we used was “multipotentiality,” and the fact that she landed on multidimensionality is correct. As we noted, you can do more than one thing.
The other 40% of marketing executives did think of the “Position-less Marketer” as a marketing professional who is not confined or defined by traditional marketing roles or boundaries. In that sense, they are not focused only on branding or digital marketing; instead, they are versatile and agile enough to adjust to the new conditions created by the tools that new technology has to offer. As a result, the Position-less Marketer should be comfortable working across channels, platforms and strategies, integrating different approaches to achieve marketing goals effectively.
Navigating the spectrum: Balancing specialization and Position-less Marketing
Some of the most in-depth feedback came from data analytic experts from consulting firms and Chief Marketing Officers who took a more holistic view.
Most discussions of the “Position-less Marketer” concept began with a nuanced perspective on the dichotomy between entrepreneurial companies and large enterprises.
They noted that entrepreneurial companies are agile and innovative, but lack scalability and efficiency. Conversely, large enterprises excel at execution but struggle with innovation due to rigid processes.
Drawing parallels, many related this to marketing functionality, with specialists excelling in their domain, but needing a more holistic perspective and Position-less Marketers having a broader understanding but needing deep expertise.
Some argued that neither extreme is ideal and emphasized the importance of balancing specialization and generalization based on the company’s growth stage and competitive landscape.
They highlight the need for leaders to protect processes while fostering innovation, citing Steve Jobs’ approach of creating separate teams to drive innovation within Apple. They stress the significance of breaking down silos and encouraging collaboration across functions, even if it means challenging existing paradigms.
Ultimately, these experts recommended adopting a Position-less Marketing approach as a competitive advantage in today’s landscape, where tight specialization is common. They suggest that by connecting dots across different functions, companies can offer unique value to customers. However, they caution against viewing generalization as an absolute solution, emphasizing the importance of context and competitive positioning.
These marketing leaders advocate for a balanced marketing approach that leverages specialization and generalization to drive innovation and competitive advantage while acknowledging the need to adapt strategies based on industry dynamics and competitive positioning.
Be position-less, but not too position-less — realize your multipotentiality
This supports what was noted in the March 20th article: to be position-less, but not too position-less. When we realize our multipotentiality and multidimensionality, we excel as humans. AI becomes an augmentation.
But just because you can individually execute on all cylinders in marketing and perform data analytics, writing, graphics and more from your desktop does not mean you should.
Learn when being position-less is best for the organization and when it isn’t. Just because you can write copy with ChatGPT does not mean you will write with the same skill and finesse as a professional copywriter. So be position-less, but not too position-less.
Position-less vs. being pigeonholed
At the same time, if you are a manager, do not pigeonhole people. Let them spread their wings using today’s latest AI tools for human augmentation.
For managers, finding the right balance between guiding marketing pros to be position-less and, at other times, holding their position as specialists and bringing in specialists from different marketing disciplines will take a lot of work. We are at the beginning of this new era. However, working toward the right balance is a step forward in a new world where humans and AI work hand-in-hand to optimize marketing teams.
We are at a pivot point for the marketing profession. Those who can be position-less and managers who can optimize teams with flawless position-less execution will secure their position for a lifetime.
MARKETING
YouTube Ad Specs, Sizes, and Examples [2024 Update]
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!
MARKETING
Why We Are Always ‘Clicking to Buy’, According to Psychologists
Amazon pillows.
MARKETING
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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