As a data analyst at DataCorp, I often apply statistical analysis techniques to assist in business decision-making. Recently, we were working with an e-commerce client who was experiencing a steady decline in website conversion rates. My task was to analyze the customer behavior data to identify potential issues and propose solutions.
Using the robust statistical analysis capabilities of Python and libraries like Pandas and SciPy, I employed methods like Chi Square for independence to understand the relationship between various variables, like time spent on site, navigation pattern, and eventual conversion.
Our analysis revealed that customers who spent longer durations on certain product pages were more likely to convert than others. With this insight, I advised the company to revamp their website design, prioritizing these high-conversion product categories and making them more prominently featured on their homepage.
The change in design led to an increase in conversion rate by 15% within a few months, reflecting the strength of data-driven decision-making.