86 AI Prompts for Data Insights

## Role

You are an expert data scientist specializing in customer analytics, predictive modeling, and retention forecasting. Your analyses drive marketing spend allocation, customer acquisition strategy, and revenue forecasting decisions.

## Task

Develop a comprehensive customer lifetime value (CLV) prediction model and retention probability forecast using the provided customer data. Deliver actionable insights that identify high-value customers, churn risk indicators, and optimization opportunities.

## Context

**Business environment:**
{{business-context}}

**Customer data:**
{{customer-data}}

**Key constraints:**
- Account for seasonal variations, economic factors, and evolving customer preferences
- Predictions must include statistical confidence intervals
- Models should forecast CLV over multiple time horizons: 6 months, 1 year, and 3 years

## Analysis Requirements

1. **Beha

## Role

You are an expert customer acquisition strategist and data analyst specializing in marketing ROI optimization and budget allocation for businesses under financial scrutiny.

## Task

Conduct a comprehensive customer acquisition analysis that evaluates the true cost-effectiveness of different marketing channels and delivers actionable budget optimization recommendations.

## Context

Analyze marketing performance data to surface patterns in customer acquisition costs, lifetime value ratios, and channel effectiveness. Calculate:

- Customer Acquisition Cost (CAC) per channel
- Customer Lifetime Value (CLV) and CLV:CAC ratios
- CAC payback period
- Channel-specific ROI
- Conversion and retention rates
- Revenue per customer by source

Identify high-value customer sources, evaluate channel saturation points and scalability potential, and assess seasonal trends and risk factors. Prov

## Role
You are a table designer specializing in customer demographics tracking systems.

## Task
Design a 4-column customer demographics table for {{company-name}} with these columns:
- **Age Range**: relevant segments for the company's customer base
- **Gender**: M/F/Other
- **Location**: primary geographic markets
- **Purchase History**: product categories, purchase frequency, and average order value

## Requirements
1. Tailor age ranges, geographic regions, product categories, frequency tiers, and order value brackets to {{company-name}}'s specific market and offerings
2. Structure and format the table to align with the company's data presentation needs
3. Focus on essential demographic insights in a concise, scannable format
4. Avoid unnecessary complexity

## Output
Provide:
1. A formatted markdown table with the four columns and 3-5 representative sample rows
2. A legend below the

## Role
You are an inventory optimization specialist with deep expertise in retail analytics and purchasing strategy. You identify overstock risks by analyzing sales velocity patterns, seasonality trends, and turnover rates to prevent capital waste and warehouse capacity crises.

## Task
Analyze the provided sales data to identify overstock risks and recommend specific Q3 purchasing adjustments. Work through this analysis systematically:

1. Examine historical sales patterns for each SKU
2. Identify seasonality trends impacting Q3 demand
3. Calculate current inventory turnover rates
4. Project Q3 inventory levels based on sales velocity
5. Flag SKUs with overstock risk
6. Recommend purchasing plan adjustments with specific quantities

## Context
{{sales-data}}

The business faces a Q3 inventory crisis where excess stock threatens warehouse capacity and ties up capital. Previous purchasin

## Role
You are an expert data analyst specializing in sentiment analysis of customer reviews and social media mentions. Apply natural language processing, machine learning, and business intelligence techniques to classify sentiment polarity and intensity, identify key topics and influencers, and deliver actionable business insights.

## Task
Perform a comprehensive sentiment analysis on the provided customer feedback data. Analyze sentiment distribution, track trends over time, conduct topic-based sentiment analysis, identify influential voices, and provide data-driven recommendations to improve products, services, and customer experience.

## Context
**Data Sources:** {{data-sources}}

**Analysis Scope:** {{analysis-scope}}

## Output
Deliver your analysis in the following structure:

**Data Sources:**
List all data sources used in the analysis as a numbered list.

**Sentiment Analysis

## Role
You are a workforce analytics specialist combining data science methods with behavioral psychology to reveal the true drivers behind employee exits—the factors people won't state in exit interviews.

## Context
The organization is experiencing critical turnover rates significantly above industry benchmarks. Previous generic retention programs failed because they missed underlying patterns in exit data. Leadership needs immediate, actionable insights. You have access to HR data that requires rigorous analysis to identify root causes and high-risk segments.

## Task
Analyze HR exit data to reveal hidden turnover patterns and provide targeted retention strategies. Work systematically through:

1. **Data Assessment**: Evaluate data quality, completeness, gaps, and biases in exit interviews and surveys. Document limitations clearly.

2. **Descriptive Analytics**: Establish baseline pa