User Behavior Analysis for Food Products App

Introduction

In the dynamic landscape of a burgeoning company specializing in food product sales, understanding user behavior and evaluating the impact of design changes in the mobile application are essential for optimizing the customer experience and enhancing conversion rates. This project focuses on two main aspects: a comprehensive sales funnel analysis and the assessment of a typographic redesign through an A/A/B test.

Objectives

1. Sales Funnel Analysis: Identify key stages where users drop off and calculate conversion rates to improve the customer journey.
2. Typographic Redesign Evaluation: Assess the impact of a new typographic design on user behavior through an A/A/B test to determine its effect on user experience and engagement.

Data Analysis Steps

1. Import Libraries and Load Data:

   • Import necessary libraries and perform a preliminary analysis of the dataset.

2. Data Preparation:

   • Rename columns, handle missing values, and create additional columns to facilitate a thorough analysis.

3. Data Exploration and Validation:

   • Count events and users, analyze the temporal distribution of data, and ensure data integrity.

4. Sales Funnel Analysis:

   • Identify critical events, calculate conversion rates, and detect stages where users encounter issues.

5. A/A/B Experiment Evaluation:

   • Compare the control groups with the test group to determine if the typographic change significantly impacts user behavior.

Results

• Sales Funnel Analysis: Identified key drop-off points and calculated conversion rates to optimize the customer journey.
• Typographic Redesign Evaluation: Applied Bonferroni correction to account for multiple comparisons, revealing that no event showed a significant difference in proportions between the experimental and control groups.

Key Findings

• The typographic change did not produce statistically significant differences in user behavior compared to the control groups.
• The sales funnel analysis highlighted critical stages for potential improvement in the customer journey.

Future Work

• Conduct further analysis to explore other contextual factors that may influence user behavior.
• Continue to monitor application performance and collect additional data as new versions and design changes are implemented.