Due to the advent of internet-based microlabour marketplaces, crowdsourcing (CS) has risen as a prominent way to match workers and employers. However, the successfulness of these crowdsourcing campaigns on the market depends upon what factors and their combinations are used by crowdsourcing platforms to stimulate user engagement. Therefore, this study investigates what factors of CS campaign profiles (gamification, transparency, and experience) and level of monetary compensation predict crowdsourcee participation and consequent campaign success. This study analyzes data from a popular Chinese crowdsourcing platform “Xiao Yuer” of 101 crowdsourcing tasks (including successful and unsuccessful crowdsourcing campaigns) by using Structural Equation Modelling (SEM) and fuzzy set Qualitative Comparative Analysis (fsQCA). The results of the SEM analysis show that gamification is positively associated with the popularity of the campaign and further successfulness of the campaign. Furthermore, the results of the more exploratory analysis (fsQCA) reveal that four combinations of the factors sufficiently explain crowdsourcing success.