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What is digital asset management (DAM)?

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What is digital asset management (DAM)?

Digital asset management software, often called DAMs, are marketing platforms that store, organize and make useful an organization’s entire library of digital assets. A DAM is the “single source of truth” where marketers can find every relevant version of the media assets (aka marketing asset management) that have been created for the brand — images, PDFs, photographs, audio, video and even virtual reality or other cutting-edge formats. The further benefit of a DAM is that these assets are appended with metadata that can provide information on anything the marketer might want to know before using the asset, such as whether the company owns the perpetual rights to use a photograph (and in what markets), whether the legal team has approved a video, and that an infographic or whitepaper has been checked to ensure it complies with the brand’s design standards.

Today, enterprises are using DAMs in a variety of ways. Marketing agencies might leverage DAM technology to help their customers maintain consistency across in-house content and creative developed by partners. B2B businesses might use DAMs differently, drawing on the benefits of a centralized hub for sales collateral and event marketing materials. DAMs are also being integrated with other technologies, especially content management systems (CMSs) and digital experience platforms (DXPs), to unify this marketing asset management with the ability to distribute digital content directly to the channels where they’re consumed.

Before the blossoming of software-as-a-service (SaaS), DAMs were installed software that resided on a company’s servers. But their utility has grown exponentially — especially for global and distributed organizations — now that most DAMs are cloud-based offerings.



This guide is for marketers who are looking to enhance their campaigns with digital assessment management technologies. Here’s what’s inside:

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Estimated reading time: 8 minutes

Capabilities of digital asset management platforms

What should a DAM platform do and what are the ways that vendors differ from one another? The answer is fairly wide-reaching. Digital asset management platforms offer a wide range of capabilities ranging from legacy features like file management to emerging capabilities due to the advent of artificial intelligence and machine learning. Let’s look at those capabilities in more detail.

Workflow management

DAM systems differ in the extent of their workflow management capabilities. Some DAMs allow collaboration through @ tagging, while others have more full-fledged project management offerings. This functionality can help marketing teams, along with outside creative resources, communicate about changes while an asset is in the development phase or being updated.

Later in the process, they can allow for approvals to be obtained from brand managers, execs and the legal team, while some systems also facilitate asset distribution. These capabilities may be built into the core platform or be offered as an add-on or integration. Most DAMs are offered as SaaS and can be accessed from modern browsers on a variety of platforms, but some have developed native apps for mobile or other platforms.

File formats and handling

One area of differentiation involves the varying abilities of DAMs to manage a variety of file formats. Though most players say they support the most popular video, image and audio formats, if your workflow requires the use of a specialized format you will want to ensure the vendors you’re considering can fully support that format.

Asset conversion, editing and customization

Once an asset has been uploaded in a particular format, some DAM platforms allow downloading or distribution in other formats — with conversions happening on the fly. Some offer lightweight editing capabilities within the platform, though connections with common image editing sofware (Adobe Photoshop, Adobe Illustrator, etc.) are typically more useful.

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Distribution and user permissions management

The content production supply chain can be long and complicated, involving many departments, agencies, freelancers and more. The ability to provide flexible permissions so that the right people have access to the right assets –– and only the right assets –– can be very valuable.

Within agencies, in particular, these capabilities can allow for offering clients/customers convenient self-service capabilities. The same dynamic can play out in large enterprises seeking to maintain a consistent brand message across geographies and verticals, where marketers and salespeople can help themselves to carefully-crafted materials like line sheets, production logs, catalogs, retail snapshots, etc.

Search and metadata

A DAM provider’s capabilities with regard to metadata and search are key to one of the most important benefits of a digital asset management system –– the ability to find assets after they’ve been created and filed away. Most providers now use artificial intelligence, either proprietary or through a partnership, for image and video recognition and tagging. A few years ago, the AI-tagging capabilities in many DAMs were nothing more than a gimmick, often creating more work than efficiencies. Now, however, these systems have grown in sophistication, in part because machine learning, by its very nature, improves as it’s fed more data. In addition, vendors are exploring ways to use these technologies to surface insights and automate content transformations based on usage patterns.


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Digital rights and corporate governance management

Most marketers license content — especially photos and videos — either from individual creators or from stock libraries. DAMs allow users to keep track of the specific license terms governing each piece of content, ensuring they’re not used in the wrong market, in an unapproved context or after the expiration of the license term.

Corporate governance of brand guidelines, as well as timelines associated with particular marketing campaigns, can also typically be managed with DAM functionality.

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Reports and analytics

Analytics capabilities are what allow marketing leaders to trace the return on the investment made in the development of digital media. These functions also let marketers determine which assets are being used most often, and in what ways, so they can use those insights when planning for future content creation.

Data storage and security

The majority of DAM providers have partnered with Amazon Web Services or Google to host their software and their clients’ assets, and so depend on their partners’ geographical distribution, regular backups and adherence to security protocols. However, some players offer clients a variety of options for data hosting, something that’s likely to be appreciated by enterprises that operate in markets with strict data governance regulations.

Integrations

Since a DAM system is meant to be the central “single source of truth” repository for all of a brand’s assets, a key factor for a successful deployment will be whether or not it integrates well with the other tools in your martech stack. Vendors differ greatly in terms of the number and types of integrations they offer. Some are also beginning to specialize in serving a specific sector with unique integration needs, such as online retailers using product information management (PIM) systems.


What is digital asset management DAM

Explore DAM solutions from vendors like Acquia, Widen, Cloudinary, MediaValet and more in the full MarTech Intelligence Report on digital asset management platforms.

Click here to download!


What are the benefits of using a digital asset management (DAM) system?

Digital asset management systems can play a vital role in your marketing organization, unifying online and offline marketing channels and leading to more efficient marketing resource allocation.

The specific benefits of using a digital asset management platform include – but are not limited to – the following:

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  • Improved communication between in-house and freelance /contract workers. Some DAM vendors offer specially designed interfaces for external creatives to submit their content and collaborate on needed changes and required versioning. Content in the creation/approval process remains accessible only to those
    involved at this stage, rather than being made available for deployment before it’s ready.
  • Improved distribution of assets to clients, partners or other outsiders. Some DAM vendors allow users to create “portals” customized for viewing and downloading by outside entities.
  • More efficient utilization of existing resources. Appended metadata and search capabilities of DAMs enable marketers to more easily find the right image or another asset for a campaign, without spending tedious hours flipping from image to image or watching video after video. This also saves time and resources that are often spent recreating something similar to an existing asset, because it couldn’t be found or the user wasn’t aware of its
    existence.
  • Increased efficiency in the workflow for internal approvals. Many DAM providers offer — either as part of core functionality or as an add-on — workflow or project management tools, which allow for smoother collaboration and transparent movement of an asset through an approval process.
  • Speed the conversion of assets into different sizes, aspect ratios and file types for different marketing applications. Though a file is uploaded to the DAM system in a particular format, many systems allow for automatic or manual cropping or editing within the system, as well as the conversion of the asset to different sizes or file formats as they’re downloaded or distributed for use.
  • Improved efficiency on the front end, in the creation of brand assets, and on the back end, in the distribution of those assets to various martech and ad tech systems. Many DAMs integrate with content creation software, like Adobe’s Creative Cloud, and also connect (either through native connectors or APIs) to systems that distribute content directly to the customer, such as ad servers, marketing automation platforms or website content management systems.
  • Easier compliance with changing brand standards and licensing terms. DAMs allow for an expiration date to be set on assets, so they are no longer used after the licensing term for a particular asset expires. For example, if a contract with a particular celebrity spokesperson is not renewed, a DAM can take those assets out of circulation so they’re not used beyond the expiry date.
  • Ease of presenting a more consistent brand face to the customer with an eye toward loyalty and retention. DAMs make it easier to enforce brand standards and distribute digital content so every customer interaction reinforces the brand values marketers intend to convey. This is one of the key advantages of a DAM at a time where the number of devices and media outlets is larger than ever, making it more difficult to maintain consistency among the assets designed for consumption in various places.
  • Ability to quantify the usage of each individual digital asset, and therefore track ROI on the cost of creation and distribution. DAMs enable marketers to track the distribution and efficacy of marketing assets, which allows them to invest more in the most cost-effective content creation and distribution methods. Some systems are able to automatically track this data, while oth

About The Author

Does your marketing team need a digital experience platform DXP

Pamela Parker is Research Director at Third Door Media’s Content Studio, where she produces MarTech Intelligence Reports and other in-depth content for digital marketers in conjunction with Search Engine Land and MarTech. Prior to taking on this role at TDM, she served as Content Manager, Senior Editor and Executive Features Editor. Parker is a well-respected authority on digital marketing, having reported and written on the subject since its beginning. She’s a former managing editor of ClickZ and has also worked on the business side helping independent publishers monetize their sites at Federated Media Publishing. Parker earned a master’s degree in journalism from Columbia University.


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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.”

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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.”

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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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