Predictive Analytics – know tomorrow what you decide today

Demand forecasts, churn prediction, conversion scores – we develop predictive models that are integrated directly into your eCommerce processes and decision logic.

From forecast to decision

Predictive analytics is only valuable when forecasts feed into real decisions. We develop models always with an eye on downstream use: how is the forecast integrated into the workflow?

Technically we rely on Snowflake as the data foundation and ML Ops pipelines for production operations. Integration into eCommerce platforms and CRM systems is part of the delivery scope.

  • Demand forecasts reduce excess stock and prevent stockoutsDemand forecasting
  • Identify at-risk groups early for proactive retention campaignsChurn prediction
  • Real-time scoring for dynamic incentivization of purchase-ready visitorsConversion scoring
  • Dynamic pricing based on demand, competition, and inventoryPrice optimization

Long-term partnerships with leading brands

ABUS
AIDA Cruises
Cyberport
Fegime
HARTING
Heel
HSE
HUK Autoservice
Kardex Remstar
Lavazza
Lekker Energie
Möbel Boss
Müller
NKD
porta Möbel
Segmüller
SOKA-BAU
Witt Gruppe
ABUS
AIDA Cruises
Cyberport
Fegime
HARTING
Heel
HSE
HUK Autoservice
Kardex Remstar
Lavazza
Lekker Energie
Möbel Boss
Müller
NKD
porta Möbel
Segmüller
SOKA-BAU
Witt Gruppe

Frequently Asked Questions

Demand forecasting typically requires 1–2 years of historical sales data. Churn models need sufficient customer behavior data with known churn events. The rarer the event, the more data is required.

Only if it is regularly retrained with new data. We implement ML Ops pipelines for automatic retraining and monitoring that detects model drift early.

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Forecasts That Improve Decisions – Measurably.

Talk to us about your analytics requirements.

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We look forward to your enquiry.

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