In analyzing consumer insights for laundry products, the distinction between laundry diary data and panelist-level data is crucial for understanding user experience and detergent efficacy. Laundry diary data offers real-time insights into actual consumer behaviors and preferences, reflecting genuine usage patterns. In contrast, panelist-level data, derived from consumers’ experiences over a few weeks, can be influenced by post-rationalization, where perceptions may shift due to expectations or marketing, potentially distorting product performance evaluations. This highlights the need for relying on laundry diary data for a more accurate assessment of product effectiveness.

To present these insights, we utilize JMP software for advanced statistical analysis and data visualization. Key functionalities include combining data tables for a comprehensive overview, using data cleaning tools to maintain integrity, and applying Partial Least Squares (PLS) modeling to explore variable relationships. Additionally, modeling scenarios and Monte Carlo analysis are employed to simulate consumer behaviors and predict outcomes under uncertainty. By prioritizing laundry diary data and utilizing these analytical tools, we aim to enhance product development and marketing strategies, ultimately improving consumer satisfaction and brand loyalty.