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MARKETING

AR/VR: Marketing in three dimensions

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AR/VR: Marketing in three dimensions

Can you interact with a salesperson or a product as if you were in the same room, even though you are on your computer, someplace else?

Volumetric storytelling is what we are talking about. It’s okay to admit you never it called that before. This involves rendering a 3D world that one can interact with via the computer, but it must be delivered to the user. Either take them into the world through the viewing goggle (virtual reality) or show them the image as it would appear in their home (augmented reality).

This technology is still in the “proof of concept” stage, with some tentative efforts at marketing. Perhaps one good example of volumetric storytelling in action was the holographic appearances of Ukrainian president Volodymir Zelensky at various European diplomatic gatherings, or ABBA’s recent virtual concert in London.

“I would define volumetric storytelling as deployed in AR or VR and leveraging 360-degree photography to produce a 3D model made through volumetric capture or motion capture.” Explained D.J. Smith, COO of VR and AR platform The Glimpse Group.

But how do you get there?

Stacking visual building blocks

First, you must start with the 360-degree capture of an object to render into 3D. This will involve placing the subject in the center of an array of cameras to capture the subject from all angles. In the case of the virtual ABBA concert, this took 160 cameras to capture the four band members.

“Volumetric capture is not cheap and is not lite,” said Courtney Harding, founder and CEO of VR and AR agency Friends with Holograms. The technique generates large-sized files that can choke on delivery over narrow bandwidths. If a volumetric file is delivered over a 5G network, that’s fine, but anything less will result in a “laggy” playback, she explained.

A 360-degree photo shoot has its own challenges to be worked out. How many people? Are they moving or standing still?  Are they speaking? Dancing? Juggling? One person — or four? “You have to capture all the data, all the people.” Harding said. And the video must be done in one take. If that scene takes 15 minutes, and someone sneezes in the last 30 seconds, you are stuck. There is no “cutting away” to another scene, so you may have to do it over again, she said.

How to deliver the goods

The volumetric story needs a platform to be seen. That means virtual reality (VR) or augmented reality (AR). Each method has its strengths and weaknesses, as well as its own sensibilities.

The 360 technology offers “great visibility into an environment, but it’s not comfortable in a VR headset,” said Smith,

AR provides a “unique experience, but isolated use cases and greatly hampered by the requirement to use phones.” He said. “Opportunities will greatly open with AR wearables.” Here Google and Apple are readying new plans for AR-friendly smart glasses, a concept Google tried once before.

As for virtual reality, it has “amazing and transformative experiential potential, however, [it is] hindered by early stage, bulky, expensive hardware and lack of great content in a wide variety of genres.” Smith noted.

Even the platform on which you plan to display a volumetric file will dictate the limits of your storytelling. The smartphone offers a small screen for an AR story. VR is bigger, offering a much wider field of view, Harding explained, but there will be a greater level of complexity.

“AR deployment is more subject-based,” Smith said. Think of showing a product in a customer’s living room, viewed through their smartphone. “Virtual reality is more environment-based. You are transported into the volumetric scene.” Smith said. “VR is an empathy machine. In the VR experience, the user has a sense of presence — you feel as if you are there.”

Showing rather than just telling the story

It’s that sense of presence that is the main attraction of volumetric storytelling. Shlomi Ron, CEO of the Visual Storytelling Institute, likened it to the science fiction experience of being teleported to another world. When executed correctly, volumetric storytelling should provide a “3D experience, letting the people interact” with the subject, be it a person or a product.

It is possible to replicate a real-life setting, allowing users to teleconference into a virtual sitting room, Ron explained. It would look like a real room. Users would be able to see everything and walk around in it.

Such a technology would be ideal for travel brands, “creating a sense of ‘being there’” when selling a destination vacation, Ron explained. The same technology can also be used for urban planning, product development and remote training.

Still, a creative would have to bring a different sensibility into the room when crafting a 3D shoot. “Think about it as game development,” Ron said. “You have to make sure that any potential angle and perspective has some value from the perspective of the user.”


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Still figuring it all out

The problem with new technologies is that potential can be demonstrated, but practical use is harder to show. There is no checklist of sensible practices a digital marketer can “check off” when constructing a campaign using volumetric storytelling.

Harding encouraged people put on a headset “and get a sense of what is possible”. One such piece of content is “On the Morning You Wake to the End of the World”, which Harding cited as an example of volumetric storytelling. The short film recounts a day when people in Hawaii woke up to a smartphone alert about incoming ICBMs.

“Understand what good storytelling is, and what is possible,” Harding said. Then it will be easier to figure out what is good for the brand.

“It’s up to the marketer to apply the teleporting experience to the goal,” said Ron.

“The best thing digital marketers can do is to keep a close eye on industry deployments to understand the potential and start experimenting with small proof of concept activations.” Smith said.

Marketers should make a start on discerning strengths and weaknesses of the volumetric technique. They will have to develop their own checklist of best practices the hard way — by trying it.


About The Author

William Terdoslavich is a freelance writer with a long background covering information technology. Prior to writing for MarTech, he also covered digital marketing for DMN.

A seasoned generalist, William covered employment in the IT industry for Insights.Dice.com, big data for Information Week, and software-as-a-service for SaaSintheEnterprise.com. He also worked as a features editor for Mobile Computing and Communication, as well as feature section editor for CRN, where he had to deal with 20 to 30 different tech topics over the course of an editorial year.

Ironically, it is the human factor that draws William into writing about technology. No matter how much people try to organize and control information, it never quite works out the way they want to.

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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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