Is Field Data Still Necessary in an AI-Driven World? In today’s practical, interconnected, and AI-driven world, is direct field data collection still necessary?
With the convenience of accessing information at our fingertips—consulting AI like GPT or obtaining secondary data through various platforms—one might question the need for on-the-ground research. However, despite these technological advancements, field data collection remains essential. It offers a comprehensive understanding that secondary data often lacks—data which can be skewed by research design or limited by the scope of previous analysis.
Real Case: Helping a Client Bridge the Gap
Recently, we supported a client in conducting field research to gain deeper insights into their customers. By collecting first-hand feedback and observing real customer behaviour, we uncovered service gaps that secondary data had failed to reveal.
These insights empowered the client to craft targeted improvement strategies, leading to greater customer satisfaction and tangible business growth. For example, while the client initially believed that business development hinged on brand awareness, incentives, and other marketing strategies, our field data told a different story: the real priority was building a strong ecosystem.
This meant that incentives needed to go beyond just end-users—they had to support the broader network of stakeholders to ensure a holistic and sustainable approach to growth.
Ultimately, the critical question is,
“Is it worth spending millions of rupiah on research?”
The answer is a resounding yes—if your goal is to build sustainable business processes.
As a research agency, we understand that data alone doesn’t guarantee success, but good data dramatically improves your chances. Having accurate, reliable insights is like having a map for your journey—you know where to turn, when to pause, and how best to reach your destination
