Dyson — Navigation Enhancements
Optimising navigation UI to reduce drop off rates.
The primary objective for this project was to improve the overall navigation ease of use therefore reducing drop-off rates and increasing revenue. During initial usability testing of concepts, participants described the navigation as easy to use (90%), straightforward (80%), time-saving (60%) and effortless (50%).
Post testing, I was tasked to upgrade the navigation UI and design for the following considerations and scenarios:
- Featured technology is a new customised category, content in it could be defined by market merchandisers.
- The system should be able to accommodate any new future categories (NPD).
- Ensuring the current navigation structure was met for testing in different markets e.g., the inclusion of Connected Home.
- Ensuring the layout works when there are more than 6 items per category.
- Refining the ‘Shop all’ button (and align with UX team on the direction for where this should sit going forwards).
Post the completion and sign-off of the hi-fidelity designs, an asset pack was handed over to the Adobe Target testing team including:
- InVision specs (all breakpoints).
- Desktop and mobile Axure prototypes (demonstrating interactions upon click and hover states). Gestures were also demonstrated via the mobile prototype e.g. push screen left when navigating down a tier.
- Imagery (rendered for web).
- Copy matrix (including translations where required).
Testing took place in January 2021 over 4 weeks in markets .com (USA) and .de (Germany):
- +19% (+10k) shoppers visited featured technology pages
- No significant increase in purchases of featured products
- +40% desktop visits
- +10% mobile visits
Due to high performance results on desktop, the decision was made for the asset heavy UI to be re-tested on tablet and mobile viewports including:
- Featured technology
- Tier 3 navigation e.g., Vacuum cleaners (Fig 2.3)
The solution cont.
Hi-fidelity tier 3 design iteration (tablet + mobile)
The result cont.
Awaiting results from Adobe Target Testing team.