Field Research & Insights
Client: Ula | 2023 | Research
For context, Ula is a tech forward ecommerce company that provides solutions to assist small retail stores in Indonesia, to manage their working capital & inventory more effectively.
Project Goal
In order to operate well in the retailer market of Indonesia, it is important for us to understand how the community works, from the smallest link of retail store owner to bigger concepts like store dynamics, a deeper understanding of these factors allow us to improve product offerings and marketing strategies that will cater to them.
Research Interviews
Our team consisted of 9 researchers and designers who visited a total of 210 stores in Indonesia as part of our research study. During these store visits, we conducted interviews with warung owners and collected valuable data related to their daily sales, storage capacity, inventory management processes, operational hours, and top selling SKUs. This quantitative data formed a key part of our datasets, which were analyzed to gain insights into the operational and business aspects of warungs in Indonesia.
By combining both qualitative and quantitative data, we were able to build a comprehensive understanding of the warung ecosystem and identify patterns, traits and characteristics of these warungs.
Identifying persona traits and values
Through the insights gathered from our interviews with retailers, we began to identify commonalities in their behavior and practices. Our team then worked to group these traits together and understand the values that led them to belong to their corresponding groups.
After extensive analysis, we were able to identify five major traits that were common among the retailers we interviewed. Each trait was associated with a set of specific values that informed the way these retailers approached their business operations.
Generating Personas
Utilizing the available datasets, we were able to accurately assess the performance of our personas and derive correlations between numerous variables which influenced their income, including but not limited to store location, age, operational hours, and inventory. The personas we developed featured comprehensive information on their store health, procurement process, and operational practices.
Additionally, we created a data visualization that condenses all these data points into a single snapshot, providing an at-a-glance overview of the results for everyone.
Reflections
Through this research project we were able to see two emerging categories that defined a store owner, they could either be a leader who actively participates in his/her own ways to improve his business, or a follower, who is mostly passive, laid back and mostly unmotivated to improve his business. It also reflected in data collected that showed differences in overall income generated by these two categories.Next steps included, gaining more insights and forming better value propositions for these leader category, and how Ula can be a part of their success story, by fuelling their motivated mindset and help them achieve their goals.