Beyond information architecture
“Getting information off the internet is like taking a drink from a fire hydrant.” — Mitchell Kapor
Information architecture (IA) focuses on organizing, structuring, and labelling content. It is a cornerstone of positive digital experiences. While there is a justified focus on creating content that’s valuable to users, it’s of little use if they cannot find it.
Content architecture is a subset of information architecture. It brings the same structure and rigour to specific pieces of content. It’s information architecture with greater granularity.
Digital experiences are always evolving and becoming ever more ingrained in our day-to-day lives. The content we create must be understood on a number of levels. Of course, it should easily be understood by a person but it should also be described in a way a computer can understand.
Starting at the end
As with any UX effort, it makes sense to start with our user and their goal — we can then consider the experience they have in getting there.
If I ask a search engine ‘where is Paris’ on a laptop, the answer I get is a map with Paris sitting right in the centre and then additional info that reinforces that answer. If I ask a voice assistant ‘where is Paris’ I receive a different answer — “Paris, France is 755km away”.
Knowing where the user is (their context) matters. We should respond to their context and give them what they need at that moment in time. Nothing more, nothing less.
Users shouldn’t just be served the right information, but also the right amount of information.
How it works
Content architecture is all about describing the content in a way that computers can understand. This isn’t anything new. When Tim Berner Lee described a semantic web in 1999, he said the goal is to make internet data machine-readable. If it’s not machine-readable, then the content loses much of its value — ‘garbage in, garbage out’.
For those familiar with digital marketing, this is similar to efforts around SEO and keywording content. Content architecture involves ‘tagging’ your content with descriptions (metadata) so it can be understood by a computer.
These descriptive tags should be captured during the content’s creation — a joint effort between the creator and developers. Cleve Gibbon recommends that we assess the content creators workflow and review how the content is structured. They can then create a data model for that content. By considering the creator experience, we ensure they can easily describe the content.
The benefits of content architecture
One of Dan Brown’s principles of IA is the principle of disclosure — if we show just enough information to help people understand, we allow them to better absorb it. If they’re interested in that information, they can dig deeper.
Once we understand what content is made up of, there are lots we can do with it. It can be segmented and used in logical ways. This is content management. Ultimately this is about creating a truly responsive user interface. This is just not about adjusting the view based on the screen size, but adjusting the content to suit the user at that moment in time.
We know more about our user’s preferences and context than ever before. We can tell a lot by just considering the device they’ve used to retrieve some information — be it a smartphone, smartwatch or AI-driven voice assistant.
This is an opportunity to create great experiences, to give the user what they want! We must deliver content to them that supports this.
