RETAIL: UNCOVER EMOTIONS AND IDEAS IN CUSTOMER FEEDBACK
Discover how to perform sentiment analysis on product reviews to characterize positive and negative buyer experiences. Leverage topic modeling to reveal common feedback themes and understand the voice of your customer at scale.
HUMAN RESOURCES: PREDICT EMPLOYEE TURNOVER
Use Assisted Modeling to walk through creating a model that predicts which employees are most at risk of resigning based on past data. Assess your model’s predictive performance with drag-and-drop model evaluation assets, including a confusion matrix and a prediction report.
MARKETING: PREDICT CAMPAIGN RESPONSE OF NEW CUSTOMERS
Use Assisted Modeling to walk through creating a model that predicts which customers are most likely to respond to a marketing promotion based on past data. Then apply your predictive model to a new list of new customers to discover which are the best targets for future marketing efforts.
OFFICE OF FINANCE: AUTOMATICALLY FLAG INVOICES FOR REVIEW
Use Assisted Modeling to walk through creating a model that predicts which future invoices will likely have errors based on past data. Then use Image to Text to read in a collection of scanned invoices and discover which get flagged by your model for high risk of errors.
RECRUITING: AUTOMATICALLY RANK RESUMES FOR FURTHER EVALUATION
Use Assisted Modeling to create a model predicting success likelihood based on past data. Then use Image to Text to read in candidate resumes and spatial tools to enrich your data set with location information. Finally, discover how your model ranks these resumes by likelihood of high performance.