Puffy Delivery Driver
Puffy Delivery is an application where our in-house drivers deliver cannabis to the customer's destination. The problem is when the drivers don't have an efficient way to map out their customer's destination for delivery. Currently, the drivers get handed a list of destinations and they manually go on Google Maps to type the destination. This decreases efficiency and could delay the next customer's order. The goal was to increase the efficiency of internal drivers by choosing the best destination route for them so they don't need to chose.
“Helping increase the efficiency of internal drivers, our app will solve driver’s problem of auto-mapping best route for drivers.”
→ Company: Mr.NiceGuy owns multiple cannabis dispensaries and Puffy Delivery, a cannabis delivery service. The service delivers your choice of cannabis to your desired location.
→ Role: UX/UI Designer
→ Communications with: Developers, QA, Project manager, Stakeholders, Delivery drivers, In-house employees
→ Tools: Pen & paper, Sketch, Overflow, Marvel
→ Product overview: Puffy Delivery Driver is an internal application dedicated to helping drivers maintain an easier experience and increase work efficiency when doing deliveries.
→ Problem overview: We have in-house delivery drivers that drop off cannabis to our customers. The problem occurs when the drivers don’t have an efficient way to map out their customer’s destination for delivery.
→ Goal: In order to increase the efficiency of internal drivers, our app will solve the driver’s problem of auto-mapping the customer’s destination by giving them an application with set destination.
With the cannabis industry being legal in 14 states, it has continued to grow and expand.
Our company saw an inefficient way of delivering cannabis to its customers. Most of our customer’s complaints were long waiting times of receiving their product, long waiting time when paying for their product, and slow customer service experience. Our drivers say it’s hard to navigate to their customer’s places, the paying application sometimes crashes, etc. Now it’s time for my team and I to further investigate the core of the problem.
We needed to determine the problem from our internal drivers so that they could efficiently deliver products. We interviewed drivers and dispatchers and conducted field studies to get more information on their day-to-day tasks. Some of my questions to the drivers/dispatchers were:
→ Tell me about a time when you were frustrated because you couldn’t finish your tasks
→ Tell me about a time when you were frustrated because the applications you were using weren’t working
→ What are the total applications you use on your day-to-day tasks?
→ Why is the messaging app so cluttered with messages?
→ How often are products delivered on time?
→ Can you take breaks en route?
I try to keep the questions open-ended so I can discover any pain points. Some of the main things I gathered from my field studies and interviews were:
→ The majority of the drivers use Google maps to map the destinations, but they would need to type in the address every time they need to go to a new destination, which can be too time-consuming entering the customer’s information and double-checking to make sure it’s the correct address.
→ Drivers get handed a list of destinations they need to go to and they normally just select from the top down because the destinations are all scattered and not filtered as ‘best route’
→ While en route, their messaging system would get cluttered with messages from dispatchers, and sometimes drivers don’t see the message because it’s cluttered. One example was when a dispatcher sent a message to the driver saying the customer wanted to delay the order, or change directions, but by that time, the driver was already en route and didn’t see the message because the driver was driving.
→ Once the driver has arrived at the destination, the payment application can take forever to load and constantly crash, so the wait time can average 10 minutes just to make a payment, this will then waste the customer’s time and delay other deliveries.
Before moving further, I also created a user flow to understand what the current process is like for our drivers to make deliveries so I can get a clearer picture of their process.
After research of interviews, I created a user journey to discover any pain points and gaps within their flow. I focused on the red sticky notes, which were defined as ‘unhappy’ moments in their journey.
I then created a matrix of 4 W’s, explaining, who, what, where, and why the problem is occurring. Once decided, I focused on one core problem that drivers were mostly concerned about and how it was affecting the customer’s experience.
Our drivers have the problem of not knowing which is the best route to deliver next when they’re going to deliver to their next destination. Our solution should deliver a way to automatically route all the destinations to drivers.
Now it’s time to turn the main problem of ” Our drivers have the problem of not knowing which is the best route to deliver next when they’re going to deliver to their next destination. Our solution should deliver a way to automatically route all the destinations to drivers.” into a solution. But how do we do that? How might we help find the best route for drivers? How might we help increase driver’s efficiency on delivery?
We brainstormed some ideas and matched them into the How, Now, Wow matrix. We chose the ‘Wow’ matrix as a possible solution because it was feasible to do and definitely something that could help drivers.
Onwards to wireframing! We started designing wireframes and prototyping them out. Our initial wireframes started off with set routes for the drivers. The drivers don’t have to think about which destination to go to next or think about whether the address they entered was correct. For example, think of an itinerary, you would want the best route destination routed in one nice flow instead of going in circles because time would be wasted. So how does it work? Dispatchers receive the orders from customers, dispatchers then add the list of the destinations onto their software that they were already using, the information will be sent into the driver’s app that the dispatchers are assigned to. The driver will log in to their app and the routes will already be set for them. Drivers just click a simple button “Start delivery” and the navigation will be started. Drivers won’t need to type any addresses, check for spelling, or determine which destination is best to go to, etc.
We have received positive feedback from our drivers and how easy it was to use. Going back to the original problem: Our drivers have the problem of not knowing which is the best route to deliver next when they’re going to deliver to their next destination. Our solution should deliver a way to automatically route all the destinations to drivers. We helped solve this problem by creating an internal application that automatically routes the destinations for the drivers so they don’t need to think about which destination would be best for them. Or having the frustration of making sure they typed the right address or spelling errors.
Field studies were the key learning in this project for me. I was able to visually see their day-to-day tasks and from those data, I was able to successfully find their problem and solve it.