Why your customer experience strategy needs a DAM
- Posted on June 16, 2021
- Estimated reading time 5 minutes
This article was originally written by Avanade alum Timur Asar.
This article was originally published in CMSWire.
Your digital asset management (DAM) platform has a superpower, one that still isn’t being exploited to its full extent.
Metadata capabilities, baked into many platforms or otherwise added via specialist tools, could take your DAM from being just a repository for assets to a personalization powerhouse.
It’s time to rethink the role of DAM in your digital experience strategy.
Why use a DAM at all?
DAM platforms have a long history, stretching back to a time where ‘digital’ itself was unheard of. The first platforms that we could really call DAMs were those catalogues of media, music and information created by broadcasters and news agencies. Consider the expansive archive of the British Broadcasting Corporation (BBC) as an example.
Such archives are rich sources of content for creators and ensure a ‘single version of truth’ for each asset. But they require careful organization, cataloging and marking to be useful, otherwise it’s just a mountain of material.
Today’s DAMs are much smarter than the physical archives of the past. Instead of requiring 60 miles of shelving over several sites (as the century-old BBC archive does), DAMs now provide a lightweight central hub for businesses to organize, store, receive and retrieve media, accessible from any device. These assets could be structured data, like names, addresses, facts and figures. Or they could be unstructured data like creative works, video, photographs or even print material.
Primarily a DAM is vital for digital marketers looking to deliver a connected experience, but it is also an important tool for ‘pure’ marketing activities. Designers, writers and other creatives can use it as a reference to ensure consistency across assets.
No matter how they have evolved, the key drivers behind DAM investment have stayed largely the same:
- Brand consistency
- Decreased time to market
- Decreased cost of production
- Decreased risk of rights infringement
- Seamless integration into marketing operations
Today, this is changing. A DAM is no longer just a library of assets. With the rise of AI and machine learning, a DAM can take on a whole new role. In fact, intelligent DAMs should be used to automatically curate and power experiences.
The problem with data
According to IDC, the amount of data created over the next three years will exceed the data created over the past 30. We’ll also be creating more than three times the data between 2020 and 2025 than we did since 2015. In 2020, it was predicted we would capture, copy and consumer over 59 zettabytes (ZB) of data over the year — that’s a truly astronomical figure. If printed out, it would certainly need more than the BBC’s 60 miles of shelves to store.
Even if we scale this back to your own operation, you’re more than likely to have more data — and more marketing assets — than you really know what to do with. How much of this is being delivered to the right people at the right time?
If you’re struggling to stay on top of your assets or to personalize experiences, it could be because you’re not getting the most out of your DAM’s capabilities. You might not be exploiting the potential of metadata.
Metadata: The currency of personalization
I call metadata ‘the currency of personalization’ for a reason. It’s an investment in your personalization capabilities, and you get a return for what you put in. All successful digital experience strategies will need you to effectively manage assets metadata. You’ll need it to process, share and deploy assets in the appropriate way.
Take, for example, an online clothing retailer with thousands of unique items. To personalize for a specific visitor, the digital experience platform would have to know which images to pull from the DAM onto the page. Simple enough. But how does this automated system distinguish a color or style of shirt from another based only on a photographic asset?
This is where the value of well-structured metadata really becomes obvious. Tagging assets with the appropriate information (for example, color, style, material) is absolutely essential, not just for your content authors (who will need it to identify assets) but also for your DAM, which can use this structured information to get content where it needs to be.
But, let’s face it, manually tagging hundreds or thousands of assets is not exactly fun. The fact that it can be such a tedious task is often what causes DAMs to become clogged up with useless content.
To overcome this hurdle, we can look to artificial intelligence (AI) for help.
The role of artificial intelligence
With advances in AI’s ability to recognize visuals and patterns, it’s possible today to set up fully automated personalization — from initial asset creation, metadata tagging and DAM-side management, all the way to delivery and analytics.
If you can feed a machine with enough customer data, it should eventually be able to recognize similarities in unstructured data and suggest appropriate metadata tags automatically.
With an AI-enhanced DAM and an effective metadata strategy, you’ll go from manually identifying and uploading content to simply feeding in new rules for the machine to accomplish automatically. Capturing and using customer data from interactions with these published assets then leads to a virtuous loop, making personalization and tagging even more accurate and effective.
Experience metadata potential
The dream of effective, fully automated personalization is closer to reality than ever, and it’s all thanks to the metadata capabilities of DAM.
So, ask yourself now, how confident are you that all the assets in your DAM are tagged with powerful metadata?