Learning from Zillow’s AI inflicted loss of $10 Billion

What happened? In the earnings call on November 3rd, Zillow’s CEO Rich Barton announced to shut down Zillow’s iBuying operations, its home-flipping business, to cut losses of over $400 million in the third quarter of 2021. This announcement will cut 25% of Zillow’s workforce, immediately caused Zillow’s share price to drop by 25% and inflicted […]

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The Analytical Journey for successful AI Transformation

Although AI technology has been available for a couple of years now, 85% of companies still struggle in scaling their efforts (Accenture, 2018) and 70% fall short in providing business value with AI (BCG, 2019). That is especially the case, when AI use cases need to be implemented in processes of an organization that require […]

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My breakthrough project in AI Transformation

During my time as Director of Data Science for one of the leading innovations and marketing consultancies in Germany, I was the responsible team lead for Data Science & Analytics projects.  Although I’ve completed numerous innovations projects with significant business impact, I had a steep learning curve to get there. I want to write about […]

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Budget Allocation With AI

The call for accountability in marketing has been growing over recent years to justify total investments in the area. Furthermore, to allocate budgets across different marketing channels, managers have been trying to better understand their contribution to sales. To model the impact of marketing on sales, time-series approaches have been proven to be successful. However, […]

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From GLM to GBM (Part 2)

In Part 1, we proposed better revenue and managing regulatory requirements with machine learning (ML). We made the first part of the argument by showing how gradient boosting machines (GBMs), a type of ML, can match exactly, then exceed, both the technical merits and the business value of popular generalized linear models (GLMs) using a […]

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From GLM to GBM (Part 1)

Insurance and credit lending are highly regulated industries that have relied heavily on mathematical modeling for decades. In order to provide explainable results for their models, data scientists and statisticians in both industries relied heavily on generalized linear models (GLMs). However, this post argues that it’s now time for a transition to a more contemporary […]

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