DATA DRIVEN PATRON ENGAGEMENT IN ART INSTITUTIONS - Bakshi, Sameer; Dev, Sudhanshu; Narayana, Ananta; Thakur, Rahul; B. Anupama (ShodhKosh: Journal of Visual and Performing Arts, 2025)
The institutions of art find themselves in that situation more and more, trying to maintain the attention of the visitors because of shifting expectations of the audience, the disruptive influence of digital technologies, and the lack of understanding of the heterogeneous behavior of the patrons. Conventional methods of engagement are based on intuit, stationary surveys or post-experience surveys and they have little abilities in forseeing inclinations, customizing experiences, or institutional decision-making. This paper aims to discuss the issue of a lack of evidence-based, methods of cognition and control of the work with patrons in real and virtual art environments. The main goal is to come up with a structured framework utilizing data to model visitor behavior, preferences and pattern of interaction in order to facilitate adaptive engagement approaches in art institutions. The given methodology combines multi-source data, such as ticketing data, time-spent in exhibitions, digital interactions history, social media indicators, and demographic features. Clustering, predictive analytics, and recommendation models are machine learning methods that are used to create segments, predict attendance patterns, curatorial, educational, and marketing interventions. They have explainable analytics to guarantee transparency and institutional interpretability of insights. The results of empirical studies indicate that data-based engagement strategies have a significant positive effect on visitor retention, frequency of participation, and satisfaction rates relative to conventional ones. Customized content delivery and direct outreach boosts the recurrent visitation and predictive models enhance proactive programming in tune with the demand of the audience. The framework also aids in planning strategies as it helps to show what sections are under-engaged and measure the effect of exhibitions and events on a near time basis. Comprehensively, the paper shows that evidence-based patron-facing allows art organizations to move beyond their reactive management and adopt the more adaptive, audience-focused ecosystems to increase the cultural accessibility, institutional sustainability and creation of long-term value to the population.