Examples of metadata and taxonomy structures done right
Comprehensive and accurate metadata can be an invaluable tool to help companies of all sizes organize, manage, deliver, and get the most value out of their digital assets.
In one example, I have worked with a cultural heritage organization whose digital asset metadata schema spanned a mind-boggling 98 fields. While this metadata structure was comprehensive, it was often ignored by overwhelmed uploaders, and as a result, very little metadata was entered, making it almost impossible to find assets in the DAM.
With input from key stakeholders, both digital asset consumers and producers, we managed to reduce the DAM metadata to approximately 16 of the most relevant metadata, powered by business rules and dependencies in the DAM and an organization-specific taxonomy.
Not only did a metadata and taxonomy structure help the uploaders reduce the time spent and confusion during uploads, but it meant that end-users could easily search and filter their search results in the DAM using the standard terminology they used within the business.
Another client used complex relational metadata to easily track and link assets to each other. Assets in the DAM could be linked by Name of the Creator, Photoshoot sets, Campaign Name, as well as versions and variants linking back to the original key visual.
When users found an asset they wanted to use, they would easily be able to explore and discover related assets to find the editable InDesign package to make changes to the asset, a previous version, or inspiration from another asset in the same campaign.
Metadata can also assist in tracking digital assets across multiple locations, automate delivery, and gather insights. One of my clients was keen to track the value and popularity of assets within each campaign they executed throughout the year.
By ensuring that each asset from the campaign was labelled with the correct campaign name (based on a controlled taxonomy list), we were able to track asset usage, whether videos or images were more commonly used, which users and departments had accessed each asset, and make data-driven decisions on where to invest in creative production for future campaigns.
Return of investment
Correctly employed metadata across multiple systems spanning the digital asset lifecycle also allows organizations to gain deeper insights into the return on investment for each digital asset which results in the ability to make data-informed decisions. Retail, eCommerce, and manufacturing companies I have worked with often use embedded metadata to track the marketing effectiveness, customer engagement, and sales related to each digital asset and channel.
With the right metadata and taxonomy structure built into your DAM, organizations can save time in pinpointing hard-to-find digital assets while discovering valuable trends in user behavior or organizational strategy from metadata analysis. Not to mention, a good metadata and taxonomy structure will make your DAM much more user-friendly, making it easier for users to adopt and love your DAM system.
Ultimately, leveraging the power of metadata allows companies to manage digital assets more effectively and make informed decisions about their future content needs.