Identify the cohorts of users most likely to be responsive
Extensible ML pipeline that allows easy ingest of growth related data sets, feature engineering, model selection and ensembling.
Causal inference processing framework for explainability of correlated activities. Shows how parameters impact predictions.
Users can be classified into being ideal for high, medium or low touch mitigation activity to match your go-to-market strategy.
Designed to ingest user responses to mitigation campaign activity and continoulsy learn. The system improves the quality of prediction results without manual intervention.
The six data sets that impact growth
Data about the customer both demographic and firmographic
As the user engages with the application user interaction data becomes much more relevant
User payment transaction data
We receive data from numerous data vendors and are constantly evaluating new sources to improve coverage.
Any marketing that has been done to the users and customer support tickets that have been raised.
Customer interaction data from mitigation campaigns
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