User Journeys: Pt 1
Understanding our current user journeys
Aim of the overall User journey project:
Introduce an overarching methodology which can be applied to the Drinkaware website content to strategically guide users to complete the digital AUDIT tool, regardless of their initial purpose for visiting the website.
The Alcohol Use Disorders Identification Test (AUDIT) is a simple screening tool designed to help people identify potential alcohol-related problems. Developed by the World Health Organization (WHO), it’s widely used around the world by healthcare professionals as a standardised way to assess how much alcohol the assessed person drinks and the potential risk of alcohol-related problems.
Discovery
I wanted to understand how users currently moved between different content types (and therefore forward in their journey if applicable), so using Google Analytics I carried out some analysis from different aspects of user entry points to see if there were any patterns or similarities:
Tracked onward journeys from the homepage.
Analysed top search queries to identify user intent.
Reviewed metrics for the top performing 25 pages.
Examined digital tools to track user sources and destinations.
Key findings:
Journey loops, where small groups of content keep linking to each other, were present in the top onward journeys. This made it difficult to identify patterns because I was analysing data at quite a granular level.
However when looking at the content within its information architectural position to see where they lead, it was too hard to identify meaningful journeys as there were over 100 pages, so there was too much detail.
To extract meaningful insights, I would think of alternative ways of viewing content groups.
Definition of content sub-categories and content types (see images above):
The majority of the Drinkaware website content sits under the “Facts” and “Advice” sections.
I needed a layer of definition between content pages and their parent page. Especially for larger groups, e.g. parent page “General health effects” had 15 content pages. These became sub-categories.
Extra nuance was also required when talking about the different types of fact pages and advice pages. These became content types.
Methodology
Mapping User Journeys:
I assigned each content page from the facts and advice section of the website to a sub-category.
Using Google Analytics to review each page within a sub-category, I combined data to provide me with the top 3 next pages for each category.
I then linked the sub-category for the top 3 pages and carried on linking and forming a journey until I reached either the Unit and Calorie Calculator digital tool (which I considered an interim point) or the digital AUDIT tool.
Using this method I could see which sub-categories linked together.
A journey showing which content users utilise to move forward and the loops within this
Working out the journey. This shows how I identified the pages that moved forwards, also the pages that looped and crossed with other journeys.
A key to the different page types.