Logistics
Smart routing for courier companies to optimize routes, save time, and maximize resources. Streamline your deliveries and boost efficiency with our cutting-edge logistics technology
Role:
UX Research, Testing, Final UIs
Date:
2019
Testing Assumptions
Field Study
Transforming logistics with NUNAV Courier
NUNAV Courier is a professional multistop tour optimizer designed for the logistics sector. It ensures users always have an ideal tour, accommodating several hundred waypoints while factoring in not only distance and time but also variables like prioritization, weights, sizes, capacities, dangerous goods, and current traffic situations.
My main goal in developing NUNAV Courier was to enhance driver engagement and increase adherence to suggested routes. This approach aimed to boost efficiency for drivers and eliminate waste for businesses. During the development process, we incrementally added features to the system before completely decommissioning the old legacy infrastructure.
Crafting a Detailed User Flow to Elevate App Interaction
The initial step involved thoroughly understanding the current product, laying the groundwork for enhancing user experience. To better visualize and comprehend the entire journey users take through the app, a detailed user flow was crafted. This user flow map highlighted key interactions and pathways, providing clear insights into the user experience and identifying areas for improvement.
Field Study
A second important step was interview drivers and participate in their real common workday. Getting closer to the user context was possible to see how they actually behave and use the app. During the study, some basics questions were conducted but, in fact, observing then gave much more useful insights. They were not used to describe their activities and usually, the memory of the experience is quite far from the experience itself.
User Journey
As an outcome was possible to design a user journey and see where was the main pain points and opportunities. The main problem was how to maintain the user on the route proposed by the app. Otherwise, all the optimation process made previously could be lost. Rules of optimization and algorithms are of course not transparent to them, so they easily tend to try a different route or sequence when they are unsure about the system.
Designing Personas
After the designing of personas was even more clear the reason behind why they simply don’t follow routes. Drivers normally drive in the same area every day, so they get used to route and streets, if the system goes against this knowledge is hard to convince them to follow.
But on the other hand, in this sector, there is a high staff turnover, which means that it constantly has new drivers (and new users). So for those that aren’t familiar with the local area, the app is extremely important, and they couldn’t work better without. For that group of users follow the route is the most natural way to go through the day.
Assumptions
After the reseach stage, I could come up with few hypothesis of the reasons why drivers aren't not following the sugeested route.
1 Rules & algorithms aren't clear to drivers, so it difficult to gain their trust.
2 Drivers load the parcel on the truck with a completely different logic, so they tend to follow the same one to delivery
3 Experienced drivers already know the area, so they are skepitcal to follow the route.
Solutions
The main approach is to proactively display useful information and bring more system transparency, in order to build a trustful feeling with the drivers - even for experienced professionals. This was made with the following changes:
✅ Overview with an arc direction, instead of a straight line
✅ Checkpoints with fixed numbering
✅ Color and icons reinforcing the status of each checkpoint
✅ A specific icon showing what type of parcel it is
On the way, drivers can have an overview of the next checkpoint and all that is nearby. Also, colors and icons help them to identify in a glance special attributes, such as delivery with appointment, priority, and suspended. All delivered items remain appearing in order to give a sense of progress during the workday.
Mesuaring Results
In order to measure the impact of the new experience few users (drivers) was randonling picked to see how much the engagement was improved.
The higher concentration of deliveries in the central area, on the graph indicates little difference between estimated time and actual delivery time. This suggests that drivers are closer to the suggested routes and thus more engaged and confident with the system.
What's Next?
Based on opportunities of the user journey and considering the context of persona new improvements were mapped for next iterations.
A progress bar that display how many packages were already delivered could help to keep them motivated during the day.
Adding the actual brand of the sender in the delivery details card: it makes faster to find the package on the truck, once each brand has its own colors and standards. In the same direction, adding a specif package icon might help them to easily find them and not be surprised by the sizes and quantity, showing them either is a bag, a package or just a letter. Each icon also communicates when it is delivery or a pickup package.
