The Top 10 DAM Best Practices: 
Organizing The Chaos

Published On: June 24th, 2024|By |5 min read|

Implementing a DAM system can help organize your business processes, but choosing the wrong software can lead to costly mistakes and a poor customer experience.

The science of Digital Asset Management (DAM) emerged in the 1990s in response to the rapid influx of images and other media files created by digital cameras, scanners, and personal computers. DAM became the only logical way to organize, identify, and store these huge, typically unstructured data files “piled up” in local hard drives and servers. Potentially, it could undo the chaos and help businesses find and use digital assets efficiently.

The potential benefits of DAM have been evident since the beginning; realizing those benefits is another matter. Large retailers and other complex businesses must handle millions of digital assets from many different sources. They must also coordinate their data usage with other systems, such as Product Information Management (PIM) and other data systems. Most importantly, their DAM system must be optimized for their primary business objective.

Sustainable DAM Strategies

Retailers’ mission is to effectively market and sell products, using DAM and PIM data to communicate with shoppers on a massive scale. With so many products and digital assets and so many marketing channels to be filled with promotions, marketing directors must plan accordingly—for the long-term health of their business. To that end, here are ten essential DAM best practices that they and their product and design managers must follow:

1. Define goals that align with business objectives.

For retailers, the goal of a robust DAM strategy must include effective, measurable advertising and marketing campaigns. That means always using the right digital asset for each product and in every marketing channel—from print catalogs to flyers, shopping apps, and e-commerce websites. DAM implementation must be done with efficient, measurable marketing workflows, such as that provided in Comosoft LAGO.

2. Audit existing assets.

Information in a typical retailer’s DAM system is subject to problems that occur over time. New versions of images may be difficult to distinguish from older ones. Data entry may be inconsistent among different departments or manufacturers. Color assets used for print production may be confused with those suited for digital. Dozens of similar errors can creep into a DAM. A systematic audit can identify these errors and pave the way for a more sustainable DAM approach.

3. Establish naming and metadata standards.

A retailer’s DAM system contains data from hundreds of manufacturers and third-party distributors, each with its approach to metadata. Many use similar data field names, but there are enough differences to cause chaos when imported data are given an SKU number. A single naming and metadata standard is essential for DAM consistency and effectiveness. When importing new data, fields must be mapped and missing data accounted for. Also, a system must be in place to automate the import process going forward.4. Centralize product data.

Retailers’ DAM systems may often involve multiple data repositories, not to mention the related information stored in PIM and other systems. Product data spread over multiple locations can quickly become fragmented and duplicated. To achieve the “single source of truth” goal, DAM and PIM data must be consolidated in on-premises installations or the cloud. This can be overwhelming, so Comosoft offers a custom systems integration service for LAGO users.

5. Identify stakeholders and roles.

An extensive, complex DAM system has many uses by different organizational departments or groups. Each person accesses the system for various reasons and with varying levels of responsibility. For example, a graphic designer needs to find assets quickly but should only be able to change the data with permission from someone who does. Conversely, when someone is authorized to make changes, doing so should not interfere with ongoing work. So, it is vital (preferably early on) to identify each stakeholder and their job responsibility and access permissions while using the system.

6. Identify other integrations with DAM.

DAM systems seldom, if ever, exist alone, especially for retailers and manufacturers dealing with multiple products. Other data repositories, including PIM, marketing, CRM, pricing, and inventory, are almost always in play. Each source is an opportunity to connect product and customer data in meaningful ways to optimize retail business. Recently, AI has opened the door to meaningful integration with customer purchase histories to improve retail sales, as documented in a recent case study.

7. Establish viable workflows.

Successful retail marketing campaigns depend on fast, efficient, and measurably effective DAM-related workflows. Comosoft LAGO includes all three, linking DAM, PIM, and other data sources to a planning and production workflow for both print and digital publishing output.

8. Plan for asset versioning.

DAM systems may easily contain multiple product photo or video versions—all under the same SKU identifier. Duplicate versions of other assets are common as well. A sound DAM strategy allows for the clear identification of such assets, both with labeling and clear visual cues. (Ideally, in an integrated production workflow environment, the original version of an asset should be replaced with an updated one automatically as soon as the original was superseded in the DAM system.)9. Institute organizational training.

Even the most automated DAM system requires skilled users at every level. Every position in a company—from advertising and marketing directors to product managers and output designers—should have a thorough, practical understanding of the DAM system’s capabilities.

10. Plan for future maintenance.

Over time, the data contained in a DAM, PIM, or other system will grow and change—as will the technology interacting with that data. Always plan to hold periodic audits of your data, its metadata, the DAM itself, and the workflows dependent on your DAM infrastructure. As the onslaught of AI techniques and tools has proved, the future can hold both promise and peril. The onslaught of AI techniques and tools has proved that the future can hold both promise and peril.


Find out more about Comosoft LAGO and its potential to transform your retail data and marketing strategy. Or book a demo to see for yourself.

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