In recent years, behavioral approaches, social media listening, and other new techniques and technologies-digital techniques, augmented intelligence, machine learning, and advanced biometrics, among others-have been foregrounded in innovation research. A focus on the evolving fields of data science and neuroscience is a driving force for both researchers and the people they study. These digital and mobile technologies have enabled researchers to augment listening, observing and categorizing methods, and to adapt new techniques in attempting to better understand consumers. On the other hand, digitized mobile societies, spurred by faster and cheaper internet access, emphasize an interconnectedness that drastically alters human behaviors and creates borderless influences. Even so, the tenets and approaches to insightful deep learning for consumers and other actors, from discovery through to the launch of successful products, remains an intrinsic part of assessing the market. Product Innovation Toolbox brings together key thought leaders and seasoned consumer researchers from corporate R&D, academia, and marketing research companies to share their experiences, advanced consumer research tools and practical tips for successful and sustainable product innovation. By offering these leading-edge tools and insights, the book ensures consumer-centric innovation by linking strategy and a designed approach. The new edition focuses on the integration and connection of all data - both structured and unstructured - for deep learning and activation, rather than a differentiated qualitative-quantitative approach, reflecting the shifting relationships involved in the latest developments in the field.