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>Manuel Eugster
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About The Speaker

Manuel Eugster

Extracting business value from half a billion daily user events - Avira is receiving half a billion user events per day, ranging from product usage events to campaign reactions to purchase and refund events. This stream of data is the foundation for various in-house data products like product health dashboards showing retention and stickiness of our products, and an experimentation framework for rapid AB testing. The fundamental question behind such behavioral data products is always "How is the customer using our product?". Generated insights enable our product owners and campaign managers to take actions that ultimately drive product and business growth. In this talk, we present a framework developed and used at Avira for behavioral analysis. The framework establishes an event data methodology providing methods to mine and explore event data. We will show different use cases, e.g., attribution models based on Markov models helping to find out relevant touch points leading to a conversion; and flow analysis to explore significant differences between user paths through a product. The framework is implemented as a Python package and will soon be open-sourced.

Extracting business value from half a billion daily user events

Extracting business value from half a billion daily user events
Avira is receiving half a billion user events per day, ranging from product usage events to campaign reactions to purchase and refund events. This stream of data is the foundation for various in-house data products like product health dashboards showing retention and stickiness of our products, and an experimentation framework for rapid AB testing.
The fundamental question behind such behavioral data products is always “How is the customer using our product?”. Generated insights enable our product owners and campaign managers to take actions that ultimately drive product and business growth. In this talk, we present a framework developed and used at Avira for behavioral analysis. The framework establishes an event data methodology providing methods to mine and explore event data. We will show different use cases, e.g., attribution models based on Markov models helping to find out relevant touch points leading to a conversion; and flow analysis to explore significant differences between user paths through a product.
The framework is implemented as a Python package and will soon be open-sourced.

 

Manuel is a data scientist by heart on the mission of turning data into actions. Currently he leads the Data Analytics & Insights unit at Avira. There he and his team develop data analytics solutions that transform massive amounts of (real-time) data from various sources into knowledge about customers and products. Prior to Avira, he was a scientific researcher at the Probabilistic Machine Learning group at HIIT, Aalto University in Finland and the Department of Statistics at LMU Munich. He holds a PhD in Statistics from LMU Munich, a MSc in Computational Intelligence and a BSc in Software and Information Engineering from TU Vienna.