User Research isn’t Just about Users: A Reflection on Shadowing Shoppers.

As a new user researcher at HappyFresh, my supervisor suggested I follow HappyFresh shoppers for a day. Here at HappyFresh, a lot of what we do depends heavily on operations behind the scenes. These include ensuring high-quality product selections, and on-time deliveries to our users. As a new joiner in the product team, I aimed to understand our users through our shoppers and understand the logistics behind our product by observing first hand how our operations team work. I went with the intention to justify user’s pain points. Little was I aware of what I was about to see.

My preparation

Upon preparing for my field observation, I started envisioning what type of things I wanted to look at. From looking at past research, I discovered that it wasn’t rare that users are in some cases unsatisfied about our shoppers and drivers. So with that perspective, I found myself building some hypotheses to test out if user complaints were true. I wrote myself a checklist of possible reasons behind user pain points.

To test them, I would first build rapport with the shoppers. This includes getting to know their background, level of experience, and motivation for shopping. This would help me find reason behind their behaviour during my observation. Then, I’d start observing their daily tasks and pain points, and their interaction with customers, from receiving an order to completing one.

What really happened

On a weekday morning, I went to one of our busiest supermarkets. From a quick observation, even early in the morning the supermarket was already quite busy. I could see a HappyFresh shopper pushing her full shopping cart to the supermarket exit. I made my way to HappyFresh’s post and introduced myself to the shoppers and drivers. After some small talk, I asked one of the shoppers if I could tag along with her.

The first shopper I followed was a very articulate and passionate woman. She dedicatedly walked me through her routine, frustrations when confronted with common problems, and how she deals with them. The second shopper was very quick in her tasks, and helped me understand her thought process by thinking out loud.

From this short interaction with them, one of the things I noticed almost immediately did not actually check off anything on my list, but deeply impacted how I approached future research. I first observed that shoppers did not interact with the app as intended. Something as simple as having to divide attention between the app and shopping slowed down their shopping flow, which in turn geared shoppers to interact with the app less and less. In some cases they relied on screenshots of customer orders when internet connection is bad. Other times they preferred to ask information of items from supermarket staff rather than the app. Being in a busy supermarket, shoppers also try to speed up the process as much as possible. They often rushed clicking through the shopping procedures of the app to make sure they finish their order on time.

What I learned

After half a day of observation and quick, casual interviews, I realised that I’ve been approaching the situation from a limited (and pretty biased) point of view. There were many factors that I never thought of when making my checklist. Many faults which users often attributed to the shopper was in fact beyond shopper’s control. Despite these challenges, HappyFresh is of course very fortunate to have clever shoppers that wittingly find solutions to unforeseen situations.

From this experience, I realized that shopper’s interaction with the app matter just as much as our customer’s. They may face issues with our app that at some point also impact customer experience. In short, shoppers are just as much a user as our customers. This may be old news to some, but new user researchers such as myself, really benefit from field observations, such as shadowing shoppers, to come to such an understanding. Such studies help new researchers gain in-depth understanding of how their product functions in real life, from all sides of the product. In my case, I realised that an update that may ease use for customers may turn out to have a burdensome impact for our shoppers. With that breadth of understanding, we are better able to empathise with all sides and always add them to the equation when implementing user findings.