Plus, get a dedicated onboarding session with Rasgo Chief Data Scientist, Andrew Engel.
Ramp up quickly for your next data science project. Each Model Accelerator gives context of the business challenge, guides target variable identification, and recommends data sources for high-value features for a specific use case.
Prioritize sales activity by predicting which new leads are most likely to close.
Determine what action to take with a customer to improve satisfaction and increase revenue.
Increase conversions by identifing new users ready to buy and customers ready to upgrade.
Forecast sales based on marketing and sales activity, product plans, and market factors.
Segment customers to customize sales, marketing, and product by customer attributes.
Predict the conversion rate for a given keyword based on the MSA, the recent weather, google trends data and demographics data.
Determine which marketing campaigns drive a customer to purchase.
Maximize marketing ROI by determining the marketing programs driving revenue.
Optimize prices and predict sales volume based on demand, competition, and market factors.
Reduce churn by predicting which customers are likely to churn and why.
Predict future demand for services, such as sessions or downloads.
Leverage historical customer purchase and product usage to recommend new products.
Optimize inventory management by predicting future demand of physical goods.
Optimize levels throughout supply chain to maximize profits and minimize stockout events.
Prevent fraudulent online transactions while maintaining good customer experience.
Assign physical resources by prioritizing competing requests in order to maximize revenue.
Identify and prevent fraudulent acounts from being created before they cause damage.
Reduce machine downtime by predicting failures and scheduling preventative maintenance.
Reduce employee attrition by identifying which employees are most likley to leave.
Establish part time staffing plans that serve customers while minimizing cost.
Improve employee search results and recommend content to improve productivity.
Predict the future value of a given asset.
Find the total cost to serve an individual customer to optimize profitability.
Estimate a customer's lifetime value to segment and prioritize high value customers.
Estimate customer satisfaction levels based on customer activity and sparse survey data.
Classify support requests to streamline responses and improve customer satisfaction.
