Customer foresight is a new field of applied research. It aims to understand future consumer preferences and wishes with regard to tomorrow's products and services. It does so by combining customer research and foresight research elements. Customer foresight can be conceived as an interaction with projected future markets through selected customers by understanding their wishes and attitudes, ideas and visions as well as their perception of signals and drivers of change. Even though the concept cannot predict the future, it enables companies to prepare for different future scenarios and thus improves strategy and decision-making processes. Definition and classification As the future combines both continuity and change, not everything one knows today will disappear tomorrow. Some things will change significantly while others will not. But even today, research reveals that numerous inventions fail due to a lack of customer centricity. Consequently, anticipating future customer needs and behaviors constitutes a challenge when developing future product portfolios. This is especially relevant for industries with long planning cycles because these industries have to develop value propositions today for the customers of tomorrow. However, this involves dealing with many unknowns e.g. future everyday life or future consumption patterns. This is why, customer foresight starts with analyzing the consumer needs, values and motivations of today. Methods in the field of customer research that can be applied at this stage are e.g. qualitative and quantitative surveys, behavioral observation and experience, ethnographic research, cultural analysis or value and motivation research. On the basis of these consumer insights, transformations and change dynamics are projected into the future. As a result, a space of possibility is defined. In order to then understand future realities, customer and foresight research are combined. Foresight tools to apply can for example be scenario planning, trend research and science fiction. However, also quantitative methods such as time series analysis can be used. Their application allows for understanding dynamics of change and projecting the envisioned developments into the future. The following graphic visualizes and classifies the approach in the sweet spot of customer and foresight research. At the intersection of customer and foresight research, it is then crucial to understand the interaction of customers with drivers of change or future realities. As customer foresight relies a lot on insight generation through interactions, a systematic selection of study participants is of great importance. Through interacting with Trend Receivers or other study participants, insights are generated which are