Analytics apps don't tell you much about usage behavior. You might be able to see how many users performed an event, or how many times they did it. But none of the analytics packages out there are good at showing you how often people do things. Are they using to-dos once a week? Every day? Only signing into the app once a month but happily paying for years?
Time matters. You can't understand usage without time.
Here I describe an approach for defining new information architectures for large organizational websites managed by many stakeholder groups.
Broadly speaking, there are four general phases to the approach:
Auditing. Begin by immersing yourself in existing content and encourage stakeholders to adopt a critical, audience-minded perspective of their content.
Diagramming. Work with stakeholders to develop new conceptual categories that better serve audiences and organizational direction.
Elaborating. Think through content in detail and test new categories against specific instances and edge cases.
Producing. Prepare content teams for production using a shared database of new sitemap pages and editorial considerations that you’ve developed incrementally.
The type of nitpicking behavior that I mentioned earlier, is especially problematic since it often causes the loss of writer’s authenticity. With time, these criticisms cause one of the following:
The writer stops publishing their work.
The writer stops reading comments and minds their own business.
The writer learns their lesson and sands off their edges in order to fit better in the society du jour.
The larger the writer’s audience, the more likely it is for the writer to pick the last option and tone down their voice. You can experience this first hand when reading the essays of prominent bloggers. Their early work is usually interesting and fun to read, which naturally brought a large audience to their doors. But the more the show goes on, the more they will waffle around the topic, since with a large enough audience every thought will be misunderstood and nitpicked mercilessly.