Best ChatGPT prompts for Market Research Analysts and Marketing Specialists

Using a dataset of customer demographic and transactional information, build a logistic regression model in Python to predict the likelihood of customer churn based on variables such as age, income, purchase frequency, and average order value. Assume the dataset is stored in a Snowflake database and provide the necessary SQL queries to extract the required data. Then, use the model to identify the top 3 factors contributing to customer churn and provide recommendations for marketing strategies to mitigate churn.

Design a data quality audit framework for an ETL pipeline that loads customer data from a CRM system into a data warehouse. The framework should include checks for data completeness, accuracy, and consistency, as well as data profiling and data validation rules. Provide a sample Python script to implement the audit framework and generate a report highlighting any data quality issues and recommendations for improvement.

Using a transactional dataset of customer purchases, perform market basket analysis using association rule mining to identify patterns and relationships between products. Implement the analysis in R and provide the necessary code to generate a set of association rules with minimum support and confidence thresholds. Then, interpret the results and provide insights on how to use the findings to inform product bundling and cross-selling strategies.

Create a Tableau dashboard to visualize sales and customer data, including metrics such as sales revenue, customer count, and average order value. Design the dashboard to include filters for date range, product category, and customer segment, as well as interactive visualizations to enable drill-down analysis. Provide a sample dataset and a step-by-step guide on how to build the dashboard, including any necessary calculations and data preparations.