Data Analytics in Marketing, Entrepreneurship, and Innovation

Marketing, entrepreneurship, and innovation each involve decisions under uncertainty. Data Analytics in Marketing, Entrepreneurship, and Innovation brings these areas together in a collection of chapters on how analytical methods can help investigate markets, assess choices, and develop business opportunities.

Edited by Mounir Kehal and Shahira El Alfy, this book ranges across business and predictive analytics, customer behavior, hospitality, product development, and innovation. Its interdisciplinary approach makes the connections between data, business questions, and practical applications the central thread.

Analytics across business and markets

The collection considers business analytics alongside predictive techniques and tools. In its marketing-focused chapters, it turns to marketing and customer analytics: using data to examine preferences, assess trends, and inform decisions about campaigns and markets.

From customer choices to new products

Discrete choice analysis appears as an approach to decision-making, while other chapters consider new product development and entrepreneurship analytics. Together, these subjects show how analytics can contribute at different stages—from interpreting choices to evaluating opportunities and shaping business strategy.

Innovation in more than one setting

Innovation analytics, technopreneurship, and the distinction between disruptive and incremental innovation broaden the discussion beyond marketing alone. The book also includes applications in hospitality and predictive learning analytics in higher education, illustrating the range of settings represented in the collection.

For readers working with data-informed decisions

Researchers, practitioners, and students interested in business analytics, marketing, entrepreneurship, or innovation will find a cross-disciplinary set of perspectives here. Rather than presenting one narrow method, the chapters bring together different analytical topics and applications for readers seeking a wider view of data use in business and related fields.