Prompts for Data Analysis

A reminder about data analysis.

Generative AI can analyze data for themes, sentiment, and more. But it doesn’t perform consistently across all data sets. It is better with text data over numerical data. It fails consistently on addition and math. So don’t rely on basic generative AI models for math.

  • Analyze the sales data for the past quarter to identify top-performing products, overall sales trends, and significant anomalies. Provide insights on seasonality, geographical performance, and customer segments contributing to sales variations:

    [insert data containing product names, quantities sold, revenue generated, sales dates, geographical data, customer segment data].n text goes here

  • Perform a customer segmentation analysis using the latest customer data. Group customers based on demographics, purchasing behavior, and engagement levels. Provide insights on each segment's value, growth potential, and targeted marketing strategies:

    [insert data containing demographic information (age, gender, location), purchase history (products, frequency, spending), engagement metrics (website visits, email opens, social media interactions)]

  • Analyze website traffic data for the past month to identify key metrics such as total visits, unique visitors, average session duration, and bounce rate. Provide insights on traffic sources, user behavior patterns, and recommendations for improving site engagement:

    [insert data containing total visits, unique visitors, session duration, bounce rate, traffic sources, user behavior data]

  • Analyze these survey results to summarize key findings, identify common themes in customer feedback, and highlight areas for improvement:

    [insert data containing survey results, customer feedback, common themes, customer demographics].

  • Conduct a social media engagement analysis for the past quarter, analyzing engagement metrics such as likes, shares, comments, and follower growth. Provide insights on content performance, audience engagement, and recommendations for increasing social media presence:

    [insert data containing social media engagement metrics, content types, posting frequency, audience demographics

  • Review cost details for the recently completed project to identify significant variances between actual and budgeted costs, and provide insights into primary cost drivers: [insert data containing actual costs, budgeted costs, significant variances, project scope, resource allocation]

  • Analyze customer churn data for the past year to identify patterns and trends in customer attrition, and provide insights into factors contributing to churn. Offer strategies to reduce churn:

    [insert data containing customer churn data, patterns and trends in attrition, factors contributing to churn, customer demographics, subscription details]

  • Conduct a product performance analysis for the past quarter, evaluating key metrics such as sales volume, revenue, profit margins, and customer reviews. Provide insights on product strengths, weaknesses, and opportunities for improvement:

    [insert data containing sales volume, revenue, profit margins, customer reviews, product details, market trends].

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Generic Data Analysis Prompt Template

Below is a generic prompt for any data analysis task. Personalize this template to get better results. Brackets { } indicate areas to fill in details and provide the necessary data.

Analyze the data set provided. The data set includes information on {brief description of the data, e.g., sales transactions, customer feedback, survey responses, etc.}.

1. Objective: Provide a summary of the key insights and themes found within the data set.

2. Specific Areas of Interest:

- Identify any significant trends or patterns in {specific aspect, e.g., sales over time, customer satisfaction ratings, survey responses by demographic, etc.}.

- Highlight any anomalies or outliers in {specific aspect, e.g., monthly sales, customer feedback, etc.}.

- Determine the most common themes or topics in {specific aspect, e.g., customer comments, survey responses, etc.}.

3. Desired Output

- A summary of the main findings

- Insights on how these findings could impact {relevant business area, e.g., marketing strategy, product development, customer service, etc.}.

- Recommendations for actions based on the insights gained from the analysis.

{UPLOAD OR COPY/PASTE DATA SET HERE}