Prompt lesson · 21 prompts
Market Research prompts for Chief Strategy Officers (CCOs)
21 ready-to-use prompts from our AI for Chief Strategy Officers (CCOs) course. Copy one, fill in the {{placeholders}}, and paste it into ChatGPT, Claude, Gemini or any other AI.
Turn Data Into An Executive Chart
Use this when you need to turn a dataset into a clear chart plus a short insight summary for a leadership audience.
Role — You are a data visualization specialist who turns raw figures into a clear, decision-ready chart with a short insight summary.
Context you provide
- {{chart_type}} — the visualization needed: bar, line, pie, scatter, etc.
- {{data}} — the actual data to plot (paste numbers/table, or describe the dataset precisely)
- {{dimensions}} — what's on each axis or category, e.g. time period, product, region
- {{purpose}} — what decision or insight this chart should support (optional)
Instructions
- Ask for any missing inputs before starting, especially the underlying {{data}}.
- Build a {{chart_type}} using {{data}}, labeling {{dimensions}} clearly.
- Write 2-3 sentences summarizing the key pattern the chart shows: trend, spike, outlier, or comparison.
- If {{purpose}} is given, tie the summary directly to the decision it should inform.
- Note any data gap or assumption that affects how the chart should be read.
Output format — The chart, rendered if the platform supports it, otherwise a clearly labeled data table plus chart description, followed by a short 'What this shows' summary. Executive-ready, no unnecessary detail.
Guardrails — Only plot the {{data}} provided — do not invent or extrapolate data points. Label axes and units accurately. Flag if the requested {{chart_type}} isn't well suited to the data and suggest a better fit.
Example — chart_type: "line graph"; data: "monthly website traffic for the past 12 months"; dimensions: "month on the x-axis, unique visitors on the y-axis"; purpose: "identify the impact of the March campaign".
Open this prompt Creating · Beginner
Build A Predictive Model From Data
Use this when you need a plain-language predictive model to inform a strategic decision, built from your own historical data.
Role — You are a strategic data analyst who builds interpretable predictive models from historical data to support high-stakes decisions.
Context you provide
- {{historical_data}} — the past data available, e.g. customer behavior, financial history, campaign results
- {{prediction_target}} — what you want to predict, e.g. purchase likelihood, default risk, response rate, demand
- {{prediction_horizon}} — the timeframe or scope of the prediction
- {{key_variables}} — factors believed to influence the outcome, if known (optional)
Instructions
- Ask for any missing inputs before starting, especially {{historical_data}}.
- Identify which factors in {{historical_data}}, including {{key_variables}} if given, most plausibly influence {{prediction_target}}.
- Describe a modeling approach appropriate to the data and {{prediction_target}}, e.g. regression, classification, time-series, explaining the reasoning in plain language.
- Estimate the prediction for {{prediction_horizon}}, with a confidence range if possible.
- List the top assumptions and what would most improve model accuracy.
Output format — A short 'Approach' explanation, the prediction/estimate with a confidence range, and an 'Assumptions & limitations' list. Analytical but accessible to non-data-scientists.
Guardrails — Do not fabricate data or claim to have run a model you cannot actually execute — describe the method and ask for the data or a tool to run it in. State every assumption explicitly. Flag when sample size or data quality limits confidence.
Example — historical_data: "3 years of customer purchase and demographic data"; prediction_target: "likelihood of repeat purchase within 30 days"; prediction_horizon: "next month"; key_variables: "recency, frequency, average order value".
Open this prompt Analysis · Advanced
Analyze Time Series Trends And Forecast
Use this when you need to spot trends, seasonality and anomalies in historical data and turn them into a near-term forecast.
Open this prompt Analysis · Intermediate
Guide A Customer Cluster Analysis
Use this when you want to group customer data into meaningful segments to inform strategy.
Open this prompt Analysis · Advanced
Analyze Customer Sentiment Themes
Use this when you have customer feedback and need the sentiment and driving themes pulled out clearly.
Open this prompt Analysis · Intermediate
Brand Sentiment Analysis
Use this when you need to analyze customer feedback and social media to understand brand sentiment and inform strategy.
Open this prompt Analysis · Intermediate
Detect and Explain Data Anomalies
Use this when you need to scan a business dataset for anomalies and explain their likely cause and impact.
Open this prompt Analysis · Advanced
Feature Selection Guidance
Use this when you need to identify the most relevant features for a data analysis or modeling project to improve efficiency and effectiveness.
Open this prompt Analysis · Intermediate
Data Segmentation Strategy
Use this when you need to divide your data into meaningful subsets to uncover insights and tailor strategies.
Open this prompt Analysis · Intermediate
Correlation Analysis
Use this when you need to determine the relationship between two variables in your dataset to inform decision-making.
Open this prompt Analysis · Intermediate
Perform Data-Driven Forecasting
Use this when you have historical data and need to predict future values (sales, demand, churn, revenue) and understand the factors driving those trends.
Open this prompt Analysis · Advanced
Interpret Data Analysis Results for Strategy
Use this when you need to derive actionable insights and strategic recommendations from data analysis results.
Open this prompt Analysis · Intermediate
Customer Segmentation Analysis
Use this when you need to segment your customer base using data analysis to tailor marketing strategies to different profiles.
Open this prompt Analysis · Intermediate
Predictive Analytics for Customer Behavior
Use this when you need to forecast customer behavior to improve targeting, retention, and marketing strategies.
Open this prompt Analysis · Advanced
Market Trend Analysis
Use this when you need to monitor and analyze market trends to identify opportunities and stay competitive.
Open this prompt Analysis · Intermediate
Pricing Optimization Strategy
Use this when you need to analyze pricing strategies and determine optimal pricing based on market conditions and demand.
Open this prompt Analysis · Intermediate
Customer Lifetime Value Analysis
Use this when you need to calculate customer lifetime value to inform retention strategies and marketing investments.
Open this prompt Analysis · Intermediate
Sales Forecasting Analysis
Use this when you need to analyze historical sales data to predict future volumes and support resource planning.
Open this prompt Analysis · Intermediate
Fraud Detection Strategy
Use this when you need to develop or enhance fraud detection capabilities using data analysis and machine learning.
Open this prompt Analysis · Advanced
Supply Chain Optimization
Use this when you need to analyze supply chain data to optimize inventory, reduce costs, and improve efficiency.
Open this prompt Analysis · Advanced
Personalized Marketing Campaign Design
Use this when you need to leverage customer data to create personalized marketing campaigns that boost engagement.
Open this prompt Creating · Intermediate