Project 1: Create a Pain Point Chart

I created a Pain Point Chart using AI tools, identifying customer frustrations within 30 minutes. This involved analyzing data to uncover deeper insights and engaging with peers by providing thoughtful, insight-driven feedback on their charts, setting the stage for a comprehensive customer journey

Project 3: Conduct A Survey To Gather Consumer Insights

I conducted a comprehensive consumer insights survey, where I analyzed the research question with AI, designed the survey, and crafted targeted outreach messages. I set up a Google Form and utilized ManyChat to streamline survey administration and track responses efficiently.

Step 2. Conduct Quantitative Data Analysis

I performed quantitative data analysis, focusing on understanding percentages and central tendencies. I analyzed Likert scale responses, calculated average rankings and correlations, and segmented data to derive meaningful insights.

Step 4. Visualize Data

I visualized data using Google Sheets to represent both qualitative and quantitative analysis results, effectively showcasing insights from my research and enhancing understanding of the findings.

Project 2: Create a Customer Journey Map

I developed a Customer Journey Map utilizing the AIDA framework, effectively translating surface-level complaints into a narrative that captured user thoughts, feelings, and actions at each stage of their journey. This mapping provided clarity on customer experiences and pain points.

Step 1. Access the Survey Responses

I accessed and reviewed survey responses, gaining insights from the auto-generated analysis provided by Google Forms. This step allowed me to familiarize myself with data interpretation methods.

Step 3. Conduct Qualitative Data Analysis

I conducted qualitative data analysis by interpreting open-ended survey responses. This involved identifying key themes and narrative insights, allowing me to draw meaningful conclusions from consumer feedback.