Information Architecture

Role: Researcher and designer

Timeline: 8 months

Tools: Optimal Workshop, Lucidchart, Zoom, Calendly, SurveyMonkey

Outcome: New information architecture


Problem Statement: Users of the Contributor Community website can’t find what they’re looking for.

The Contributor Community website is a large knowledge base of information for Getty Images and iStock contributors. It contains user guides, legal documents, FAQs, and more. The navigation had been unchanged for many years—I identified a need to improve how the content was organized. Our support teams were swamped with questions from contributors, questions that our content answered, but was undiscoverable to users. The Contributor Community website had poor search technology, which made the effectiveness of the IA even more important. Improving the information architecture could help solve our problem.

Original Information Architecture

the OG

Card Sort Study

To understand our user’s mental models and what a new information architecture could look like, I started this project with a card sort study. The study ran over a 2-week period.

Method
  • Used Optimal Workshop to run the studies.
  • Performed 11 moderated open card sort studies, each 45 minutes long.
  • 67 unmoderated open card sort studies completed.
Participants
  • Getty Images Creative contributors – current users
  • Getty Images Editorial contributors – current users
  • iStock contributors – current users
  • Non-contributors
    • These individuals were sourced via Craiglist and were qualified based off a survey they completed. This group of participants matched a defined persona.
Cards
  • A total of 30 cards were created, all representing the current navigation of the Contributor Community website.
  • The names of the cards were altered, to prevent bias from current contributors participating in the study.
  • Each group of participants were presented with a distinct set of cards.

After completing the study and awarding compensation to our participants, I analyzed both the qualitative and quantitative data. I presented my findings to stakeholders via a deck.

Executive Summary
  • We identified 6 new themes: Scary Legal, Personalization, Customization of Content, Community, Simple, and Optimize My Content.
  • The current categorizations in the Contributor Community website are aligned with contributor’s mental models but can be further optimized by adding new categories and using action-based naming conventions.
  • Recommendations are
    • Personalize, customize, humanize
    • Make legal fun
    • Content strategy
    • Creative inspiration

New Information Architecture Proposal

Using the data and insights collected from the card sort study, I created a new information architecture that supported user’s needs. The IA went through a few different iterations based off feedback from stakeholders.

What we ended up with supports a few different goals:

  • Choose your own adventure. We knew from our study that users want content tailored to their skill level. Our system would never be smart enough to know their skill level as a photographer, or videographer, but we could group content by skill level. This gives the user the option to choose their path—content for a newbie, or content for a skilled contributor.
  • Less is more. I enforced a limit on the number of articles nested in each section. I also suggested utilizing a long page scroll design for certain content where we knew content would continually be added.
  • Ever-present legal. Since we knew the word ‘legal’ in itself was enough to scare someone away from reading important content. I removed the word Legal from our IA. Instead I threaded legal document throughout the content. This meant there would not be a section of the IA devoted to legal content, but it would be included in the places where it was important.

Content Audit

Another important piece of this project was auditing our current content and identifying where it would fall in the new IA.

I reviewed every single article—this included looking at Google analytics, and discussing with subject matter experts. I reviewed a total 282 articles. Of these, we removed 100 articles, consolidated 10 and only kept the most important and relevant pieces of content.