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Description: Choice-based conjoint (CBC) analysis is one of the most widely applied market research techniques. This study focuses on two principles that seek to enhance CBC: incentive alignment and adaptive choice-based conjoint (ACBC) analysis. Individually, these principles have proven to increase the forecasting accuracy of CBC, however there is a lack of research considering both principles simultaneously. Drawing on two lab and two online experiments, the present study fills this gap, and tests whether combining both principles yields superior results. On the one hand, the findings reveal that incentive-aligned CBC and hypothetical ACBC predict comparatively well. On the other hand, ACBC proposes a more efficient cost-per-information ratio in studies with a high sample size. Moreover, the newly introduced incentive-aligned ACBC achieves the best predictions. Based on our studies, we help market researchers to decide whether to apply incentive alignment, ACBC, or both, depending on the context of a specific application.