In our recent discussions with Fortune 500 retailers, a common theme has emerged: the need to consolidate digital asset workflows. These industry leaders have invested heavily in Digital Asset Management platforms (DAMs) with the intention of creating a centralized hub for product and marketing assets. 

‍The reality of digital asset management is complex. Designers move assets into Figma, project managers host workflows in Airtable, website managers upload pictures to the CMS, marketers track performance of assets in PowerBI.

‍Leading retailers today can see significant productivity gains in consolidating this workflow. But how can they make DAMs more powerful and tightly integrated, so that production teams can do more from a single interface?

DAMs: the promise vs. the reality

In theory, a DAM is the backbone of a digital content pipeline. It's supposed to be how modern companies source all assets and metadata across the entire content lifecycle, from ideation to audience and analysis.

The benefits should include:

• Making assets easier to find through better metadata
• Providing a single source of truth for assets and metadata 
• Creating a single streamlined workflow across all platforms 
• Allowing scalable performance as media archives grow

For instance, a retailer may integrate their DAM with creative tools like the Adobe Creative Suite, a Content Management System (CMS) like Wordpress, a Marketing Automation Platform like Hubspot, an e-Commerce Platform like Shopify, local machines, and other tools. Integrations bring missing capabilities to DAMs, and work best when they’re “systems” or “platforms”, meaning that users can solve multiple problems in one place. But those integrations themselves are still dependent on the underlying quality and discoverability of digital assets within the DAM.

2 hours per day – that’s the average amount of time knowledge workers are wasting on inefficient searches for internal information.

(Source: Obrizum research 2023)

The key challenge for retail businesses is that traditional DAMs are underperforming at content discovery and analysis – making it hard for teams to efficiently utilize digital assets.

There are three main reasons for this:

1. DAMs provide limited search capabilities. As a result, even after costly manual metadata generation, DAM users struggle to discover relevant digital assets.
2. Most DAMs were built before the advent of multimodal AI. This means that retailers must rely on humans to add structure to visual content. But manually-created metadata is costly to create, and low in quality compared to modern alternatives. 
3. DAMs only have basic analytic functionalities. The limitations of the tools are compounded by the underlying metadata and discoverability issues. This collectively impairs the ability of analysts to generate meaningful insights through the DAM.  

In other words, traditional DAMs are not designed to enable the efficient searching or optimization of image, video, or audio assets.

Let’s explore some use cases, to see the impact on real workflows.

Campaign Managers: struggling with asset discovery

Campaign Managers face daily frustrations trying to locate specific assets within their DAM. This is due to incomplete or inconsistent metadata. For example, a campaign manager searching for "winter sweater" might miss relevant images because they were tagged only with generic file names like "IMG_230897". This forces marketers to waste time manually searching through folders, chasing down colleagues for 1:1 assistance, or recreating assets from scratch. Search is dependent on someone correctly describing each individual asset with accurate labels or metadata. Without that information, images are non-existent to search and productivity is hampered. This can lead to inconsistent brand representation across marketing channels. 

Digital asset Managers: limited analytics capabilities

Digital Asset Managers are unable to track asset performance effectively. They need to be able to see which images, videos, and audio files are being used, and by which teams, so that they can monitor performance across channels. But inconsistent data entry, taxonomies, and storage processes between teams is a huge headache. These issues prevent managers from assessing asset usage and performance in depth. Additional metadata enrichment within the DAM is costly and time-consuming, and doesn’t overcome the limitation of the DAM’s in-built search or analytic tools. Collectively, this prevents asset managers from making informed decisions about future content creation and resource allocation.

E-commerce Website Managers: delays in launching new products

E-commerce Website Managers are often racing competitors to launch new product lines and capitalize on consumer trends. But inadequate metadata and limited DAM capabilities are slowing them down. When product assets lack detailed, consistent tagging and descriptions, the process of uploading, organizing, and searching for new items becomes time-consuming and error-prone. This delays product launches, and can cause missed market opportunities. The limitations of traditional DAMs are causing website managers to prioritize data management over strategic initiatives, hampering their ability to drive growth and maintain competitiveness in the fast-paced online retail environment. 

Marketers are spending 63% of their data-related time on tasks that could be automated.

(Source: Funnel research, 2024)

Industry research shows that these inefficiencies are resulting in higher business costs and missed sales opportunities. (Funnel, 2024, Obrizum 2023). From our conversations with national retailers, we’re seeing two common approaches:

1. Let the burden fall on DAM users – reducing staff efficiency & capabilities while raising costs
2. Cobble together a variety of in-house and off-the-shelf tools that each solve a different party of the problem – adding friction and complexity for your teams

But there’s a new solution available that can unlock the full potential of your DAM. Let’s talk about multimodal AI.

Enhancing DAM Capabilities with Multimodal AI from Coactive

Multimodal AI shifts the paradigm. It makes it effortless to generate metadata and apply it across thousands of visual assets. This can unlock the power of your DAM in new ways. The Coactive platform offers:

1. Content Discovery: Search across images, videos, and audio, using our semantic, image-to-image, and intelligent search feature.
2. Content Enrichment: teach Coactive your unique enterprise taxonomy with a few clicks. Create metadata by showing or describing visual assets, and the Coactive platform will automatically improve and re-label them based on user feedback.
3. Content Analytics: Understand the contents of an individual video as well as your entire visual dataset. Analyze using SQL, and visualize the contents of your dataset. 
4. APIs and SDKs: Seamless integration with your existing DAM. Benefit from cutting-edge AI without the risky and complex upheaval of changing your core infrastructure.

We want to help businesses get more out of their existing DAMs, so that they can better monetize their digital assets.

– Sergey Astretsov, Head of Product at Coactive AI

Your DAM can fuel AI-powered automation and personalization, with the Coactive Multimodal Application Platform.

Client example: Marketers couldn’t find images

The marketing team of a national retailer had an image problem. (Not like that – they’re beloved). Their digital assets lacked metadata, and their DAM’s built-in search tools weren’t good enough to compensate for this. This meant that finding the right image was taking hours. Their marketing team was spending more time searching for assets than actually creating campaigns.

Enter Coactive's AI-powered solution. The Coactive API seamlessly integrated with their existing DAM, massively upgrading the marketing team’s content discovery abilities:

• Natural language queries made searching more intuitive and nuanced. No more cryptic keyword combinations and filters - just ask for "a family sitting on an outdoor furniture set in a backyard with food" and voila!
• Search time dropped from hours to seconds
• Marketing team freed up to spend more time on campaigns, improving the company’s overall ROI on its DAM and media infrastructure

Comparison: regular DAM vs DAM powered by Coactive AI

Standard DAMs are limited to basic keyword searches, manual metadata enrichment, and limited analytics. This makes image, video, and audio assets difficult to find, and makes usage and performance hard to measure. The high time costs and reduced quality output of standard DAMs are impacting businesses' competitiveness in the age of multimodal AI.

By contrast, DAMs enhanced by the Coactive Multimodal Application Platform (MAP) can generate nuanced metadata at the speed and scale of AI. The Coactive Platform also enables customizable search terms unique to your enterprise taxonomy, natural language text prompts, visual searches, and advanced content analytics including SQL queries and data visualization. Teams benefit from faster, more relevant search results, and actionable insights from high quality analytics, all of which drives more impactful marketing campaigns and helps optimize content.

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Connecting your DAM to multimodal AI 

Here’s a brief, non-technical overview of the process:

1. Your internal user (e.g. marketing team) submits a search query
2. The request is routed to Coactive’s Search APIs which produces a ranked list of results
3. The Coactive platform feeds the results to your application, which displays them to the user

Hungry for more technical detail? Our Product Team would love to talk with your engineering and product teams. Just request a demo.

Summary

For retailers looking to consolidate their digital asset workflows by maximizing the performance of their DAM, you can now monetize your digital assets with less risk and better ROI with multimodal AI.

You can upgrade your existing DAM’s capabilities by integrating seamlessly with the Coactive Multimodal Application Platform. Get all the benefits of cutting-edge AI search and analytics, without the hassle of reinventing your digital architecture. 

To learn how multimodal AI can enhance your DAM's capabilities and streamline your digital asset workflows, request a demo today.