Predictive alerts are powered by Natero’s state-of-the-art machine learning technology, which builds predictive models and algorithms that apply to SaaS vendors' unique scenarios and types of data, to proactively alert them to customers at-risk; as well as those that represent sales opportunities.
We do this, in general, by looking at vast amounts of historical customer data such as product usage, billing and support data. Then we construct machine learning models that are customized for your business; and evaluate a variety of algorithms to determine which would be the most accurate for your specific account.
We train our models using some of your historical data, and then test it on another set of data. These models analyze hundreds or thousands of factors to determine which are the most relevant indicators of churn, expansion, conversion, etc. We continuously update predictive models as data comes in, automatically improving in accuracy and adjusting for changes in customer behavior - with no effort required by you.
Currently, we will only turn this capability on for Natero users when enough historic data has been collected and consumed. As more data comes in, Natero’s machine learning models automatically become more accurate in their ability to predict customer actions.
Learn more about the difference between rule-based alerts and predictive alerts.
Learn how Natero builds predictive models.