For a B2B SaaS company, we unified CRM, billing, and marketing data, then layered on revenue forecasting and at-risk-account detection, all surfaced in Power BI.
Illustrative preview · not live data
The challenge
CRM, billing, and marketing data were scattered across systems. Churn was handled reactively, and forecasts were guesswork.
The approach
We built an Azure Data Factory and Synapse hub, added PyTorch revenue forecasting, gradient-boosting and CNN churn models, an LSTM customer-health index, and K-Means segmentation for targeted campaigns.
The result
Forecast accuracy up 14%, monthly churn down 12% at 85% precision, email CTR up 25%, and data-prep time cut roughly 75%.
Built with
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