Lean Ethnography
Products that engage users and monetize create a strong emotional connection for their users. Many traditional user researchers believe it must take months of research to discover key emotional drivers. We have found though that we can draw on the framework of lean processes and rapid contextual research to engage in what we call Lean Ethnography.
When designing a new product for delivery service drivers in a compressed timeframe, we engaged with these drivers by ordering six pick-ups and deliveries from their delivery service over two days. We observed the drivers, and asked questions about their tasks, what they love, and what they dislike. We rapidly gained an understanding of their context of use, their current challenges, their goals—both explicit and implicit—and what connects them emotionally to their current process. In doing so, we were able to create the vignette, or visual story, highlighting a new mobile solution that they loved!
In the following vignettes, we highlight the recommended solution, as well as some of the key emotional motivators for these delivery drivers.
Douglas, a package delivery driver, prides himself on having mastered “the art of stacking.” He stacks higher, moves faster, and moves more each trip than most of his peers, all while keeping packages in good condition and staying on schedule.
What’s more, Douglas uses everything he learns about his route, and his customers, to provide even better service without ever thinking about it.
What if we could capture all of Douglas’ tacit knowledge and then add technology to it?
The framework developed had two key design drivers: contextual knowledge and efficiency. The less the driver has to look at the device, the better. Time used in navigating and interacting with the device is inefficient time. The driver needs to focus on the road, on the customer and on looking and understanding his whereabouts. The interface automatically adjusts to show what is relevant to Douglas in each step of delivery. Optimizing for driving, carry and delivery. The route and delivery queue shifts automatically to the conditions on road and driver’s location. The driver is not burdened with unnecessary data and the most important thing is always highlighted.
