TechnologyCustomer Service

How IONOS Uses Snowflake AI to Retain 30% of At-Risk Customers

IONOS SE, the German web hosting company serving 6.6 million customers, built a unified data foundation on Snowflake to eliminate customer data silos across all brands. AI and machine learning power automated analysis of 15,000 daily call transcripts, ML-driven upsell recommendations, and proactive churn detection — retaining 30% of customers at the point they call to cancel.

Outcomes

150+Data sources consolidated
15,000Daily call transcripts analyzed
30%Customers retained at cancellation point
Up to 2xUpsell conversion rate uplift
50%+Automated churn risk analysis accuracy

Tools & Technologies

1S
Snowflake
Cloud data warehouse by Snowflake for storing, querying, and sharing structured and semi-structured data.

AI Categories

Challenge

IONOS operated customer data across disconnected silos spanning multiple brands and departments, preventing unified visibility into customer behavior, limiting transcript analysis to 1% of call volume, and leaving churn risk and upsell opportunities largely undetected across 6.6 million customers.

Solution

IONOS migrated to Snowflake’s AI Data Cloud, consolidating 150+ data sources with Snowpipe Streaming for real-time ingestion and Dynamic Tables for pipeline automation, then used Snowflake Notebooks to feed 15,000 daily call transcripts into AI models — enabling automated churn detection, ML-powered upsell recommendations, and proactive customer retention at scale.

Full Story

IONOS SE operates one of Europe’s largest web hosting platforms, serving over 6.6 million customers with domains, hosting, website tools, and cloud services across multiple brands. For years, customer data was siloed: care, sales, finance, and product teams each maintained separate data systems with no shared view of a customer’s full journey. Service agents had limited context when fielding calls, marketing teams couldn’t target effectively, and churn often went undetected until it was too late.

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Source

SNOWFLAKE
May 2026
Original case study

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