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We’re implementing DAM! Where do I start?

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We're implementing DAM! Where do I start?

Congratulations! You have the approvals and budget for your company’s first digital asset management (DAM) solution and are ready to jump in. Now what? The excitement of the early days of your DAM journey can quickly give way to apprehension when faced with the question: Where do I start?

Where are my assets?

Before you can decide on an appropriate DAM system and the amount of storage you’ll need, you need a complete picture of what you’re working with regarding the number of assets and file sizes. If your company produces a large volume of high-resolution video assets that will be stored in the DAM, that can take up a significant amount of storage space. It’s never too soon to start unearthing and gathering your company’s assets.

To get the most value out of your DAM, it needs to be the single source of truth for all of your assets. Leave no stone unturned. Account for all file types, including images, videos, documents and source files. Don’t assume that all of your assets are on the company shared drives. Shared drives are an excellent place to start, but make sure you’re also looking at Sharepoint sites, putting out a call for any external storage devices, and finding out if your users have a habit of storing things on their hard drives. Does your company work with agencies? Ensure they’ve supplied you with all the files they’re contractually obligated to provide.

Early indicators

Once you’ve made progress with gathering all your assets, look at what you’ve collected and see if you can start identifying some broad preliminary requirements:

  1. What range of file types and sizes does your DAM need to accommodate?
  2. Given the volume, depth, and history of assets you’re seeing, should everything go into the DAM from day one? Or does it make more sense to select a key date and upload every asset created from that day forward into the DAM while maintaining archival assets in another location? Remember that if you maintain archival assets in a separate location, they should be quickly and easily accessible by designated users. You’ll typically find that some legacy assets still approved for current use will fall outside the scope of what you’ve loaded into the DAM for its launch. These assets will need to be uploaded into the DAM as users request them.
  3. Do you typically generate multiple renditions for single assets? For example, do you have not only the original version but also a thumbnail, small, medium, and large versions?
  4. Will you need to account for versioning? When you upload a new version of an asset into your DAM, do you need to retain all previous versions for archival purposes and have them associated with the current version? Do the specific changes across versions need to be tracked?
  5. Are there specific legal or regulatory requirements around some or all of your assets?

Seeing double. Or triple.

Another asset-related task you’ll want to address sooner rather than later is duplicates. With assets scattered across multiple locations, duplicate copies of the same assets are bound to be in multiple locations. They may all have the same file name, allowing them to be easily identified, or they may not. Often it can take the trained eye of your creative team or content experts to identify duplicate assets with differing file names.

The sooner you start identifying and weeding out duplicates while you’re gathering assets, the better. You’re likely already familiar with the “garbage in, garbage out” principle, and you should remember it when prepping assets for upload into your DAM. Sure, you could throw everything in there and clean it up later, but will you? And in the meantime, how much confusion is it causing for your end-users, some of whom are being exposed to a DAM for the first time? You need to find time and resources to address the duplicates sometime, so make it a priority to do it before you’re ready for that bulk upload of assets into your shiny new DAM. You could be saving yourself time in not duplicating work by putting metadata on assets that will likely be deleted shortly after uploading to the DAM.

Who’s driving this DAM train? And who’s along for the ride?

Seriously consider bringing in a DAM librarian. The sooner, the better. You may be hesitant about spending part of your DAM budget on a full-time librarian, and yes, I may be a bit biased about this point, but it will be worth every penny. Having a librarian dedicated to the project from the beginning is especially crucial if this is your company’s first DAM. And to get the most out of your investment, find someone with the trifecta of DAM experience: selecting, setting up, AND maintaining a DAM. Bring them in as soon as possible. It will save you time and money in the long run because they can save you from making decisions early on that you’ll have to devote resources to fixing later.

As a librarian who has helped three companies launch DAMs, I know very well what not to do, and I can guide you away from making decisions you’ll regret later. Waiting to bring someone in until you realize you’re in over your head and have made some not-so-optimal decisions means your librarian could potentially spend months, if not years after they’ve arrived in “fix-it” mode while doing damage control and trying to convince users they can trust the system that did not make the best first impression.

If your DAM Librarian is the driver of your train, your stakeholders are your first-class, VIP passengers. Identifying them and getting their commitment to the project should happen as early as possible. This allows time for them to get any necessary approvals from their leaders and prep their schedules for the time commitment. When identifying stakeholders, make sure you include people from each separate division of your company that will engage directly with the DAM. Any group or department that will include regular end users of the DAM should be represented. And don’t forget that the IT and Legal departments need to be included.


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While you want to ensure you have a voice from each relevant area of the company, be careful about establishing too large of a stakeholder group, which could make discussions unwieldy and lead to issues coming to a consensus. Part of the stakeholder’s role is to represent their respective division and be a single voice for them in meetings, so only one stakeholder per area is required. Clearly define for your stakeholders the parameters of the role and your expectations. Be sure that they know the time commitment that will be involved, and get their commitment that they’re willing and able to remain fully engaged for the duration of the work. The participation of your stakeholders can significantly help or hurt the progress and timeline of your project, so set clear expectations right from the start.

While your DAM journey will ultimately be rewarding, there will be ups and downs along the way. Taking these few specific first steps will start your journey off on the right track and set you up for future success.


Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.


About The Author

Rachel Edwards is an experienced digital asset manager who is passionate about metadata, taxonomies and data governance. She specializes in bringing order to data chaos since 2007.

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MARKETING

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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