How Metadata Supports AI in Customer Experience


The Gist

  • AI advantage. Leveraging AI in customer experience significantly boosts digital engagement strategies.
  • Metadata matters. Metadata’s role in creating more personalized digital experiences can’t be overlooked.
  • Balance required. While rich metadata is crucial, an overload can cause diminishing returns and increase maintenance challenges.

Artificial intelligence (AI) has created a new realm of opportunity for brands and marketing technologists. With this comes the need for an updated roadmap outlining the avenues, driving lanes and turning points to navigate the new terrain — all of which should lead to the destination of improved digital customer experiences. Organizations are still designing the blueprints for how they want to use AI in customer experience.

Three rolled scrolls of blueprints sit on top of a flat blueprint on a table or surface, suggesting the importance of a blueprint for AI in customer experience.
Compiling blueprints for your plan for using AI in customer experience is essential. Maksym Dykha on Adobe Stock Photos

As they go through that process, they should not overlook metadata. It contains key information that, when combined with customer data, can be used to power AI to help create digital experiences. Also, AI can be used to generate metadata about content. Having accurate and consistent metadata about content allows it to be used to create more personalized digital experiences.

As marketers consider their digital experience strategies, and how to make the best use of their available content, maximizing use of metadata should be a cornerstone of the strategy. Incorporating AI into their use of metadata presents an opportunity to change the way they manage and use content and digital assets shaping the customer experience.

Related Article: AI Customer Experience Ushers in a New Era of Engagement

Metadata: The Digital Asset Control Center

As its name suggests, metadata is “data about data.” For marketing content, metadata may include attributes of a document, image, video or other asset. These might be language, location, license, keywords or more. Metadata about products could describe things such as product name, product line, color, size, or materials.

The aggregate of metadata about a piece of content includes information and details collected from all relevant sources across an organization. Once this information is brought together, it can be used to organize digital assets and to make it available as part of digital experience platforms.

Metadata can be categorized into three classes based on its capabilities and the various roles it can play:

  • Structural metadata provides information on the way assets are organized, structured, and associated with one another to paint a picture of how content pieces together, such as pages, product numbers and chapters.
  • Administrative metadata assists in the management of assets — such as the date of creation and format of an asset.
  • Descriptive metadata delineates a resource to make it discoverable, with examples being authors, the subject and descriptions.

Marketing teams should determine which metadata they will collect by considering what matters to their organization and aligning to business needs. Take one of my favorite brands – New Balance. The New Balance DAM has an asset metadata field for “product display name” to help ensure consistency and speed to market when syndicating the appropriate product shots and display name across various marketing channels. This metadata also helps users find and reuse assets based on how the product is marketed.


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