Adaptive content: what is a content model?

Skyline view of Paris with Eiffel Tower in background.

In the second of our five-part series on adaptive content, Noz Urbina explains content models, and why they are important to adaptive content.

Content model – a definition and example

Yesterday we looked at what adaptive content is and how it helps both businesses and customers get more from their content. Today we go a little deeper to understand how it works through the use of content models.

Dive in with me and I promise by the end this paragraph will make sense to you:

A content model defines a series of content types and their relationships to each other. Each content type in turn defines the shape (structure) and nature of the content that’s supposed to go inside it. The content type specifies the semantic categories that can be applied to each of the different components inside that type of content, and sets rules about how many, where and so on.

Clear as mud?

Let’s use the example of a recipe on the community site of a major consumer goods business. We could define the structure of a recipe and it would have several semantically categorised types of content inside it…

 

Content types define specific subcomponents for content, formalising them, creating extra metadata inside the content body itself.
Content types define specific subcomponents for content, formalising them, creating extra metadata inside the content body itself.

This is your defined content type for ‘recipe’.

Adding deeper levels of metadata

In What is adaptive content?, we discussed simple personalisation and contextualisation, where we were putting category tagging only on the whole content piece. In this case, that would be the whole recipe. But when we have structurally defined a content type like this one, we can start to apply tags to the different sub-components – effectively adding categorisation to the categories – and adapt them too.

The introduction, for example, is an area where we might want to make alternate variations that would appeal more or less to different profiles of user. To appeal to users of a certain geography or social demographic, we could create an alternate “Introduction” and tag it as being for “millennials”. We would then have two introductions, which we could select when we detect one of our millennial users is viewing this recipe.

We could similarly use a tag like “audience:vegan”, but this has other implications: whereas many recipes will have “Notes and variations” at the bottom (as indeed this one did, as you can see if you view its full image on Wikipedia), why not adapt the body of the content itself? Why not give the user what they want, the first time?

Anyone who has bought home electronics will have experienced reading convoluted, painful instructions that say: “If you have model ABC, follow steps 1-5 and see image 1. For model XYZ, follow steps 3-5 and see image 2.” This is cost-effective for the content creator but barely acceptable to the user. In print, it almost works, but in an electronic age, with various consumption channels, users expect what they want and only what they want.

If we were to provide an optimised experience for a vegan, we could tag several components of the recipe, including the whole recipe and the title itself, as “vegan”. If we did this, then we could:

  • Adapt the introduction to be relevant for vegan readers.
  • Adapt the ingredients so that certain non-vegan ingredients could disappear completely for vegan readers, and vegan substitutes could replace others.
  • Adapt the instructions to remove or substitute steps as needed to make the recipe vegan.

Adding other categories like “event” which could take values like “event:holidays” – or whatever else makes sense for your content – would allow further variations.

Adaptive Content adds extra labels to content so that different variants can be created from the same source. This enables more sophisticated personalised or contextual delivery where content appears differently depending on whatever parameters you define – audience, time, place, purchase history, ambient factors, and on and on. Systems that leverage adaptive content can use all the available knowledge and user context to drive optimised content experiences, but rely on this embedded metadata in the content.
Adaptive Content adds extra labels to content so that different variants can be created from the same source. This enables more sophisticated personalised or contextual delivery where content appears differently depending on whatever parameters you define – audience, time, place, purchase history, ambient factors, and on and on. Systems that leverage adaptive content can use all the available knowledge and user context to drive optimised content experiences, but rely on this embedded metadata in the content.

From content types to content models

Taking several content types together and relating them with reference and reuse rules, creates a content model. For example can you make a composite recipe by reusing two recipes in one? For example, a pie with a reused crust recipe from other pies, but a unique filling?

A content model defines relationships between content types. For example, a type being reusable in itself.
A content model defines relationships between content types. For example, a type being reusable in itself.

Parts of the recipe, for example, the intro and title, could also be (automatically) reused in other content types, such as a landing page that serves as a portal for a specific personas, eg, a page about ‘Living Vegan’ that pulls together parts of various content types (articles, recipes, blog posts) to create a new type.

A content model can define relationships between types to create completely new content types and new reuse opportunities. The model can be as open or as prescriptive as your content needs require. Too limiting is inflexible, but too open is hard to manage for both people and machines. Finding the right balance is the content modeller’s skill.
A content model can define relationships between types to create completely new content types and new reuse opportunities. The model can be as open or as prescriptive as your content needs require. Too limiting is inflexible, but too open is hard to manage for both people and machines. Finding the right balance is the content modeller’s skill, guided by a content strategist.

Modelled content enables multichannel delivery

These semantic categories can also drive automatic publishing to various formats. Once you’ve defined your content, you can define how it’s rendered automatically in print, or via syndication to various sites and properties around the web, to apps – really, whatever you want.

For further reading on content models, read Rachel Lovinger’s Content Modelling: A Master Skill on A List Apart, or see more of my examples of content types in Content Types and models, What can they do for you?

Join the workshop

In our next post, Noz will be asking why businesses should invest in adaptive content? What is the commercial advantage and is simple personalisation enough? Or you can read all five adaptive content posts in the series.

For a deeper understanding of adaptive content for content creators, Noz is also holding a series of training workshops in the UK and the USA this autumn on Content Personalisation Workshop: Adaptive Content Modeling – to explain the trend, and why it is increasingly on the radar of both businesses and content professionals alike.

Firehead readers can get a a 10% discount offer for any Urbina Consulting-run workshop (this doesn’t include workshops run in conjunction with conferences or third parties). Register with the code ‘UCNW10’ and you’ll get an extra 10% off entry (right now that means London but not New Orleans).

Noz Urbina is an author, content strategist and founder of Urbina Consulting.

CJ Walker

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