Predictive Alert Reasons

Natero's advanced machine learning models look across many factors to decide if an account is likely to churn, expand or convert. When a predictive alert triggers, it'll come with a list of reasons the model believes are most relevant to the situation predicted.

Below is the description of some common measures you are likely to see in your predictive alerts. 

Age Time since the "join_date" of the account.
Feature Usage
Counts how many times each specific feature event was logged for each account, per week.
Module Usage  Tracks time spent in each tracked module, per week.

Session Time 

Total time spent in all tracked modules, per week.

Days Active 

Counts how many days the account recorded activity per week, from 0 to 7. 
Interactions  Counts messages/notes. 
Open Support Tickets  Counts how many support tickets are still open, per week. 
Distinct Features Counts how many distinct features (tracked by Natero) were used in a given week by each account.

We also look at the relations hip between these measures across different weeks, in particular:

Momentum of... Compares a weekly metric, such as total usage of a specific feature or total session time, against historical weeks.  Typically compares the most recent week against 2 or 3 weeks ago. 
Current Time Since... An activity index that is higher the more recently an account has done something, such as using a specific feature, or having a Salesforce interaction logged. 
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