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How Metadata Makes Content Authors More Efficient and Improves Customer Experience

The term “metadata” for computer systems has been around since 1960s. But how exactly should it be used for your content so that both you and your customers can benefit?

Let’s explore some use cases.

Finding Content to Be Updated or Reused

As content author, you spend some time trying to find the content that you want to update or reuse. If you don’t use a component content management system (CCMS), you’re probably relying on a folder structure on the file system. Properly organized folders may provide a good way to get to the piece of content you are looking for.

But what if you need to find multiple pieces of content that span multiple folders or your search needs to meet criteria that cannot be satisfied by the folder structure? For example, you want to see if you have anything already written about configuration and troubleshooting of a specific issue that might occur in a certain release of a certain product.

Metadata lets you label content in a way that represents multiple perspectives all at once: subject, audience, product, release, product’s module, and so on. This allows you to easily construct search requests, such as “Find the content whose subject is Configuration, written for our Selling Partners, describing the Configuration Prerequisites in the Release 10.0 of Product ABC”.

To be able to label your content this way, you would need to build a metadata model. It should reflect the way you think about your products and customers. For example, the metadata model that would allow to define the query above might look something like this:

  • Subject

    • Configuration

      • Configuration Prerequisites

      • Configuration Process

    • Installation

    • Administration

    • Troubleshooting

  • Audience

    • Customers

    • Selling Partners

    • Internal Users

  • Product

    • Product ABC

      • Release 10.0

      • Release 11.0

    • Product XYZ

      • Release 15.0

      • Release 16.0

By the way, the search request doesn’t have to come from a human user. It can be, for example, a chatbot that parses the user’s question asked in a natural language, constructs the search requests, and then sends it via a search API.

Filtering Content

If a company produces multiple products, there is a good chance that each content author has a long list of documents and files they are working on. It’s not necessarily that all of them should be actually displayed in every moment of time.

The content author may want to say “Show me only the Master DITA maps for the Release 10.0 of Product ABC, but don’t show any of its Submaps because I don’t want to get an overloaded view of the content repository”.

The metadata is not used for search per se in this case, but to control the view of the content repository.

Finding Content to Solve a Problem

After the content becomes available to your customers, they need to find a specific piece of content that addresses the issue they have. Just like content authors, customers may have requests, like “I’m a Selling Partner and I need to explain to my client the Configuration Prerequisites of the Release 10.0 of Product ABC”.

The same metadata model and labels assigned to specific pieces of content that content authors use to find content in their content repository also allow customers to navigate through the product documentation.

For example, this is a screenshot of a customer support portal of one of our customers. The content subjects – Before You Buy, Getting Started, Configuration, Troubleshooting, etc. – are coming from the content’s metadata. It’s displayed on the customer support portal to help end users to navigate.

Similarly, the list of the products to which the current article is applied is also coming from the metadata assigned to the article.

Propagating the metadata model down the stream means that not only content authors can benefit from the metadata for purposes to make their work easier, but also end users can use it to access the content more efficiently.

Processing Content Automatically

After the content is created, it’s delivered to customers. The delivery channels may vary. It can be anything from a good old PDF to a centralized content delivery hub from which the content is further distributed via portals, chatbots, websites, and so on.

In any event, continuous delivery of large amounts of content can’t be done manually. The delivery manager should be able to request something like

I want the Changed and Approved parts of the Configuration section of the product documentation for the ProductABC in English, German, and Spanish to be automatically pushed to our Staging environment”, or

I want all Reviewed and Approved content in All Languages from the Staging environment to be pushed to the Production environment every night at midnight”.

In this case, the metadata (which includes not only semantic metadata, but also data about the lifecycle and translation status) is used by a delivery engine to pick up the content that satisfy certain criteria.

Do you want to know how metadata can be used for these and other use cases with DITAToo DITA CCMS? Contact us at, and we’ll be happy to show you!

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