Optimizing gamification: unveiling customer preferences through neural network and conjoint analysis

Purpose Within the banking industry, gamification is a strategic response to customer hedonic and interaction-oriented preferences. However, many gamification programs fail due to improper game mechanism selection and not considering customer expectations. To increase the effectiveness of gamification programs, this study has been conducted to optimize their design by aligning them with customers' preferences and elements of interest. Design/methodology/approach This research is designed in the form of three consecutive studies. In the first study, the elements of gamification programs have been identified through a systematic review. In the second phase, the sensitivity analysis of a multilayer perceptron neural network has been used to determine the importance of these elements. In the third study, 22 test profiles were evaluated based on the full profile model of conjoint analysis. Findings The results highlight that goals (importance 0.146), rewards (0.139) and customization (0.098) significantly influence banking customers. Conjoint analysis indicates a strong preference for investment-focused gamified financial programs (partial utility 3.379), continuous feedback (0.565), storyline exploration (0.399) and absence of time pressure (0.383). Practical implications This article contains suggestions for increasing the effectiveness of gamification programs and determines what customers want from a gamification program and what factors in these programs are attractive to them. Originality/value Previous research has rarely addressed customer expectations and preferences in the design of gamification programs. The results of this study can increase the success rate of gamification and provide the possibility of saving the costs allocated to the programs.