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What does the Metaverse mean to consumers and marketers?

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What does the Metaverse mean to consumers and marketers?

A new study from Gartner found that consumer opinions about the metaverse are vague and largely uncertain. Marketers should keep this in mind as they look at new ways to engage consumers in virtual spaces.

Only 6% of consumer respondents told Gartner that they were “very familiar” with the metaverse and that they “understand and can describe it to others.” And only 21% said they were “somewhat familiar.”

That leaves nearly three quarters of consumers who have murkier ideas on the subject. 38% have heard of the metaverse, but aren’t sure what it means. A full 35% percent have never heard of it.

Why we care. Talk of the metaverse came almost out of nowhere last year when Facebook’s parent company changed its name to Meta. Since highs in September 2021, the company’s stock valuation has been cut nearly in half.

But there is more to this meta-talk than just saving an ailing tech giant. Marketers are always looking for new ways to connect with consumers meaningfully and deeply. Here’s a look at where marketing opportunities exist now, or in the near future.

Metaverses and other virtual experiences. Generally speaking, “Metaverse” can mean any number of ways that brands provide VR or interactive 3D-image experiences.

Read next: Marketers look to upgrade their 3D digital experience

“From the onset of the pandemic, companies have worked to aggressively reshape the digital experience for browsing and discovery, but also virtual try-ons and augmented reality furniture-buying experiences,” said Kyle Rees, senior director analyst in the Gartner for Marketing Leaders practice. “These are the companies that people today expect [to be involved in the Metaverse]. If it’s not Facebook, it’s a big retailer. Virtual shopping is not necessarily surprising, but it’s a signal to marketers – to what level should I pay attention to this?”

Trusting the metaverse. With all these different virtual experiences, and many more on the horizon, the association with Facebook might not help an early adopter brand.

In the Gartner survey, only 18% of respondents said they are “primarily excited” about impacts the metaverse may have, while 21% said they were “primarily concerned” about the metaverse. 60% had no opinion.

If consumers associate the metaverse with Mark Zuckerberg’s company, that opens a lot of negative associations pulled from recent headlines about the toxic effects some social media platforms have on impressionable minds, as well as public discourse and even democracy.

Adding to the distrust are reports of new poorly regulated virtual environments that cast all the evils of the old Internet into stark 3D.

The metaverse, or metaverses, have to define themselves outside of the company Meta, and they also have to demonstrate that they are safe and secure spaces.

“I think Facebook rightly or wrongly made a very deliberate trademark grab [by changing the parent company’s name to Meta],” said Rees.” There are a fair amount of consumers who associate Facebook with the metaverse. And a corollary to that, and they’re open-ended associations, is that ‘I don’t trust Facebook,’ or they think it’s more isolated and that the metaverse is just another way Facebook is trying to make more money off of them.”

He added that the association with Meta is not necessarily a positive one, and that there’s a great need for a massive learning and education initiative to help clear the air and build trust.

Gaming. If in the early stages, most consumers are confused, out-of-the-loop or distrustful, there is a cohort primed for metaverse adoption among the gaming community. Gamers have been interacting in virtual worlds with each other and with brands for years. 

“Gamification is already built into the metaverse,” Rees said.

The question for the future metaverse, and for marketers looking to get involved, is can this acceptance scale to an even larger audience of non-gamers?

Rees says a crucial feature that will have to be a part of this growth is interoperability. If a brand in retail, or in any other industry, builds a storefront in the metaverse, consumers will have to be able to access it with a number of devices in a seamless way.

Ads in the metaverse. A busy street in the metaverse won’t resemble the IRL world unless it has billboards and other branded environments.

London-based ad platform AdRunner is looking to help monetize the virtual real estate in the metaverse using a decentralized community-led ad interface built on the Ethereum blockchain.

“We are building a decentralized ad architecture that can best leverage the protocols used by dominating platforms,” said AdRunner’s CMO Chris Rios. “The metaverse landscape will take time to create a cohesive and shared experience across all platforms.”

Read next: Marketers – the Metaverse is coming

Tied loosely together with NFTs. “Until then we will see a set of disparate ‘intranets’ that are loosely tied together, similar to the late 1990s when pockets of interaction occurred in chat rooms and one-off websites until companies like Google, Facebook, and YouTube shaped the Internet into a cohesive social space,” Rios explained. 

He added, “We see the development of the metaverse happening in a similar way. There is huge value addition in spaces already leveraging internal payment structures, like Roblox’s Robux, as these will likely be tied to NFT marketplaces and provide users with customized experiences or abilities. NFT marketplaces will likely be critical to the adoption of Web3 and will work akin to certificates or “passports” within the metaverse.


About The Author

Chris Wood draws on over 15 years of reporting experience as a B2B editor and journalist. At DMN, he served as associate editor, offering original analysis on the evolving marketing tech landscape. He has interviewed leaders in tech and policy, from Canva CEO Melanie Perkins, to former Cisco CEO John Chambers, and Vivek Kundra, appointed by Barack Obama as the country’s first federal CIO. He is especially interested in how new technologies, including voice and blockchain, are disrupting the marketing world as we know it. In 2019, he moderated a panel on “innovation theater” at Fintech Inn, in Vilnius. In addition to his marketing-focused reporting in industry trades like Robotics Trends, Modern Brewery Age and AdNation News, Wood has also written for KIRKUS, and contributes fiction, criticism and poetry to several leading book blogs. He studied English at Fairfield University, and was born in Springfield, Massachusetts. He lives in New York.


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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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