Bosch Circular Saw Case Study Revisited

An AI-Powered JTBD Research Experiment

The Jobs-to-be-Done (JTBD) research method has evolved significantly over the past 20 years. Traditionally, qualitative interviews were the primary tool for understanding the job, the map, and the metrics. However, this approach often led to inconsistent results due to the variability in the interview process, the evolution of rules and framing, and the influence of individual biases.

Today, we're leveraging artificial intelligence (AI) to streamline and improve the JTBD research process. Specifically, we're using ChatGPT (and other tools) to generate job maps and success metrics. While this AI approach isn't perfect, it offers a more systematic and consistent method for conducting JTBD research.

To illustrate this, let's consider a case study involving a Bosch circular saw job. Using ChatGPT, I generated job maps and success statements for four different scenarios of cutting wood in a straight line using a circular saw. The AI was able to produce detailed and varied results for each scenario, demonstrating its potential in automating the qualitative phase of JTBD research.

AI has revolutionized the JTBD research process, making it faster, more accurate, and less biased. For those interested in conducting JTBD research projects using this new approach, my team and I offer services to help you navigate this process.

I invite you to check out a database containing my complete outputs on the job of cutting a piece of wood in a straight line using a circular saw - you’ll find links in the video description. I'd appreciate your feedback on which version you think is best. The question we're left with is: "Did AI do a better job than the professionals?"

Don’t forget to check out the link 👇 below 👇 to gain direct access (one click) to a database of my complete outputs on the job of cutting a piece of wood in a straight line (using a circular saw). Let me know which version you think is best!