A leading global tech company wanted to understand the perception of products in the generative AI space—both image and text generation. They needed a comparison of their platform with five competitors, focusing on which aspects of the user experience triggered peak and pit emotional moments.
We built a dataset of 200,000 data points from online discussions about the six platforms. Using advanced clustering models and human expertise, we mapped the overall landscape. We then honed in on the most critical Use Cases and Features clusters. By applying our filtration algorithms, which focused on emotional recognition, past tense usage, and 1st person speech, we isolated approximately 9,000 peak and pit memory data points. This process allowed us to identify the specific use cases and features that were driving high emotional engagement in the generative AI space, along with the exact set of emotions being triggered.
Our client gained a clear understanding of their positioning against competitors. Insights were provided to: Marketing: Knowledge of the most favoured use cases and their associated emotions helped shape a Major TV campaign. Engineering: Feedback on key features influenced a shift from a single platform offering to a more integrated operating system-level proposition.
