Automatically analyzes data to provide key insights and patterns using machine learning.
Allows users to ask data questions in plain English for easy interaction.
Generates scheduled reports and dashboards based on data updates.
Creates charts, graphs, and visual summaries from analyzed data.
Uses historical data to forecast trends and outcomes with AI models.
Works with major spreadsheet platforms and external data sources.
Enables team sharing, editing, and commenting on analytics projects.
Track and optimize sales metrics, identify top performers, and forecast revenue using AI-driven insights.
Measure ROI, analyze customer engagement, and adjust strategies based on predictive analytics.
Predict revenue, expenses, and cash flow trends to support budgeting and financial planning.
Optimize stock levels and reduce waste by forecasting demand with machine learning models.
Identify and target customer groups based on behavior and preferences for personalized marketing.
Analyze processes to identify bottlenecks, reduce costs, and improve productivity.
Evaluate potential risks in business operations using data-driven probability models.
Use customer feedback and market data to guide feature enhancements and new product launches.
Analyze employee performance, retention rates, and recruitment effectiveness to optimize HR strategies.
Improve logistics and distribution by predicting delays and optimizing routes with AI insights.
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