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How Under Armour’s Curry Brand shoes are taking off in the metaverse

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Under Armour’s Curry Brand sneakers are moving as fast in the metaverse as they do on the court. While NBA three-point king Stephen Curry extended his legacy with a fourth league title (and fourth Finals MVP) this spring, hoops fans took to the metaverse to score special Curry Brand NFTs, called “NF3s.”

The cross-promotion was part of a long-term initiative executed by Under Armour and spearheaded by NFT branding and tech company Luna Market.

Curry Brand NF3 basketball. Image: Under Armour.

“For Curry Brand the push into Web3 has really been about finding new ways to connect to community and experimenting with goods and experiences,” said Ryan Drew, general manager of Curry Brand at Under Armour. “Curry Brand was founded on performance and purpose. So, technology and innovation, as it relates to the footwear world, is part of our DNA. Taking that mindset into the roadmaps we are building is a no brainer especially when Stephen is personally invested in these communities.”

Game tie-ins. With their latest promotion, Under Armour capitalized on fan interest from real games by tying special NFT drops to results on the court. Every time Curry hit a three-point shot during the NBA playoffs, nine rare basketball NFTs were released via the “Curry Counter” on the Curry Brand NF3 site.

Since Curry became the all-time leading three-point shooter earlier in the season, it was a safe bet that he would hit his shots in games. The promotion worked even better because Curry’s team, the Golden State Warriors, went all the way in the playoffs and won the championship, giving the campaign maximum leverage.

Read next: Gap partners with DOGAMI to release pet-themed NFTs

How Under Armours Curry Brand shoes are taking off in
Curry Brand metaverse serum for NF3 basketballs. Image: Under Armour.

Interactive and interoperable. The basketball NF3s that were released during the playoffs were free, but limited in number. Fans can now bid on them in the resale market on the OpenSea marketplace.

Through the Curry Brand NF3 site, NF3 basketball owners can combine the basketball with “serums” in a virtual “mixology room.” The result of this mad science experiment is a Basketball Headz avatar. Users can take this avatar and use it on different metaverse platforms, including Decentraland, The Sandbox, Gala Games and Rumble Kong League.

Earlier in the year, Under Armour commemorated Curry’s record-breaking three-point shot, which made him the NBA’s all-time leader. For that promotion, the Curry Brand released metaverse-wearable sneakers, called the Genesis Curry Flow. There were 2,974 of them, and they were randomly assigned five levels of rarity. They were priced at $333 and sold out in minutes. Under Armour gave the profits from the sale to charity.

1659121054 995 How Under Armours Curry Brand shoes are taking off in
Curry Brand Basketball Headz avatar. Image: Under Armour.

Genesis Curry Flow wearable users will gain exclusive access to bidding on the physical version of the shoe later this year.

Under Armour roadmap. Owners of the Genesis Curry Flow understand that having them in their possession will give them access to other real and digital promotions down the road.

Similarly, Curry Brand is invested in NFTs long-term. They plan to release more wearables for avatars in 4Q this year to keep fans engaged while the new NBA season kicks off. And next year, the plan is to engage Basketball Headz avatar users with activations across different metaverse platforms, in an interoperable way. Potential activations include IRL in-person events, as well.

Why we care. The multi-pronged long-term strategy by Under Armour shows how marketers can tap into real fan engagement across real-world sports action and NFT bidding in the metaverse.

It’s important to note that Stephen Curry is one of the most famous athletes on the planet, so he and Under Armour’s Curry Brand have special pull in bringing consumers to Web3 environments. But we’ve also seen over the last year a number of other brands, especially in fashion and apparel, testing the waters and building a ripple effect.

Fans who own NFT wearables will want to show them off in all metaverse environments. That’s why Web3 aspires to be interoperable, but it’s not quite there yet.

“From an interoperability standpoint, if I created a metaverse jersey, I need to transport that to metaverse games, including those owned by large gaming companies coming into the space,” said Billy Huang, co-founder of Luna Market. “So, it’s amazing from a brand marketing standpoint, but we still have to build those partnerships and connections. The onus is on partnerships. Agencies are coming in to centralize a lot of those connections.”

So, yes, this is still early stages for metaverse marketing because it lacks standardization and interoperability. But big brands and celebrities are carving out a path to multiple platforms and long-term engagement.


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About The Author

datafuelX launches predictive analytics solutions to improve linear TV and

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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