Where’s My DAM Value?
Defining success metrics unlocks the potential of your digital assets
By Brian Courtney, Erica Hornung, and Kristie Satzberg
Welcome to our ongoing series on understanding and optimizing the Return on Investment (ROI) of a Digital Asset Management (DAM) system. In this article, we examine ways to increase your company’s productivity and efficiency by using data-driven principles to improve asset use and DAM utilization.
Know your Success Metrics
To get the most out of your DAM system, it's crucial to first determine what's important to your business – and use that information to improve utilization of your DAM. Identifying your business’ key success metrics first is crucial to determining if your current DAM system can meet your needs – or if your organization needs to upgrade. For example, are you seeking to measure asset ROI or striving to make better use of your creative assets? Are your users frustrated by irrelevant search results? Or is there another problem statement you need to solve?
Once your success metrics are defined, work with your DAM vendor to determine how your current or future DAM can report these metrics in a way that satisfies your requirements.
Not all DAMs track, report, and display information the same way. Some might have more robust usage analytics reports out of the box, while others might require additional services or interventions to meet goals. One DAM system might display results in a visual format, like a pie chart or table chart, while another may only support CSV export of critical data. Which format best suits your needs?
Dive into Data Discovery
Once your DAM is implemented and your assets have been successfully migrated, data analysis can begin. Use your newly collected data to identify areas where adjustments can be made to your system, metadata model, or data governance policies to improve asset reuse, thereby boosting ROI.
Search
Search is at the core of DAM system functionality. Users perform various types of searches to find images, videos, and other assets needed for projects. But if users can’t easily discover what they need, time to market is delayed, costing your organization. Worse, users might recreate assets that already exist because they couldn’t be found.
To improve search in your DAM, consider the following questions:
Are user searches coming up with no results?
Are search terms returning inaccurate results?
Are different search terms returning the same results?
How often do users search before acting (save, download, share) on search results?
Measuring search performance metrics can indicate how much effort it takes users to find what they need. Search history reports might reveal that users often misspell words or phrases, or search for synonyms that are not in your metadata model. They could expose content gaps in your asset library, or indicate that users simply need more training on the system. Improvements in any of these areas can lead to increased search efficiency in your DAM.
Good search results rely on good metadata, which leads us to the next point.
Metadata
Metadata is the information used to describe an asset - data about data. Metadata allows your assets to be searched, and the proper design and application of your metadata model is crucial to optimizing search results for your users. Poor metadata can impact content performance by causing assets to be under or over-utilized.
Metadata questions to consider are:
Are there assets without any metadata?
Do certain metadata fields have null, or empty, values more often than others?
Have assets been tagged incorrectly? How many?
Are there too many free-form text fields causing spelling and formatting inconsistencies?
These questions can shed light on needed changes to your metadata model or data governance practices. If your users often leave certain metadata fields blank when uploading assets, you may consider making these fields required, or eliminating them, depending on the needs of your business. If your assets frequently have inaccurate metadata, you may consider training users more extensively in the problem area. While some systems can use AI (artificial intelligence) capabilities to automate metadata application, eliminating labor intensive tasks, the highest quality metadata will always be defined by users. Consulting with DAM users about metadata issues creates a feeling of ownership, understanding, and participation, improving metadata quality. Even so, assets may have inaccurate metadata applied for a variety of reasons. Perhaps your business would benefit from implementing a quick review process for user generated metadata that can be performed without interrupting a user’s workflow.
Once your data analysis strategy is in place, it’s essential to continuously monitor the system to ensure your DAM continues to deliver value over time. Evaluating trends by asset type, user type, permission level, or region can reveal how your DAM is actually used in practice. Even simple reports can reveal data cleansing needs, limiting, or better yet, eliminating, null values, resulting in increased DAM value.
Summary
By evaluating your businesses data analysis needs and designing a metadata model to accomplish your critical goals, your DAM system (and its content) will be more useful, valuable, and powerful. Once your needs have been established, check your DAM system’s capabilities to verify if your system can answer your data questions.
At Salt Flats, our experienced DAM implementation consultants help organizations realize the full potential of their DAMs. If you’re looking to implement a new DAM, our team can set up a system for success starting on day one. If you already have a DAM system but are looking for more value, we can optimize and streamline your system and data practices to ensure the best results for your users. If your DAM system isn’t living up to its maximum potential, consider contacting Salt Flats to provide a technology assessment.
