Storytelling can be the difference between your data making a true contribution or remaining unheard. Because in order to move your stakeholders to act, they need to thoroughly understand why your data matters, and often on an emotional as well as a rational level. And for that, there is no more...

This chapter introduces the KontoSensor , a digital service offered by Deutsche Bank since September 2018, as an example of data processing using predictive analytics. We present the motivation behind this digital service, the use cases and methods currently implemented, the way they have been...

With the rise of artificial intelligence and machine learning, competitive data science platforms like Kaggle are gaining momentum. From a host's perspective, the platforms offer access to a large crowd of data scientists who can solve their data science problems efficiently and...

In today's economy, experiences are a distinct offering that have become the core selling point for some of the world's most successful companies. From banking and transportation, to home exercise and healthcare, companies have differentiated themselves by designing distinct experiences...

In light of the data economy, data protection law is a key legal element for being able to leverage data-driven innovation and is often regarded as a limitation for businesses and service design. Contrasting this traditional view, this chapter argues why designing with privacy in mind is a...

Text mining, natural language processing, and natural language understanding continually help businesses and organizations extract valuable insights from unstructured data. As the business environment changes, companies must integrate data from many sources to remain competitive. Text is yet...

Across disciplines, researchers and practitioners employ decision tree ensembles such as random forests and XGBoost with great success. What explains their popularity? This chapter showcases how marketing scholars and decision-makers can harness the power of decision tree ensembles for academic...

Neural networks, which provide the basis for deep learning, are a class of machine learning methods that are being applied to a diverse array of fields in business, health, technology, and research. In this chapter, we survey some of the key features of deep neural networks and aspects of their...

Machine learning and artificial intelligence (AI) have arisen as the availability of larger data sources, statistical methods, and computing power have rapidly and simultaneously evolved. The transformation is leading to a revolution that will affect virtually every industry. Businesses that are...