Cut time to build models from 6 months to less than a week
- Doubled customer propensity to buy rate
- Realized additional revenue by being better able to target offers
- Created propensity models that helped companies identify the right customers and prospects that have a high likelihood to purchase a particular product or service
- Create models and use custom recipes that generate features/variables that provide a probabilistic estimation of whether customers will perform any of such actions or not i.e. a propensity score.
Use propensity scores to estimate value each customer brings in real-time. Make data available to Relationship Managers of the Bank (RMOs) who can further slice and dice the data and consume the information intuitively.
H2O AI Apps, built with SDK for Data Scientists, can perform:
Supervised Machine Learning
Automatic feature engineering, model tuning and optimization, scoring pipeline generation
Accurate time series capabilities
Automatically generated visualizations and data plots
Nonlinear algorithmic modeling
Results viewed on Dashboards in a tabular format, grouped by different features (city, areacode, spending limit, etc) or for a single user; view target groups and selected features such as textual insights explaining the prediction, the propensity score for each user (mean or median) if a target group is selected.