Cultural ecosystem services (CES) based on nature experiences substantially contribute to public health and human well-being. However, CES’s supply-demand methodology remains scarcely explored on the coastal beach, and the demand relating to public preferences has not been sufficiently unveiled in spatial assessment. Here, we selected recreation services as a lens of CES and applied the knowledge of multi-source big data to better reflect public preferences. Point of Interests (POIs) refer to particularly valuable or interesting places. We proposed to integrate POIs and social media data (Weibo check-in) to quantify the demand for beach recreation services (BRS). We also used socio-ecological indicators to quantify the BRS’s supply. The supply-demand balance of BRS was further identified by quadrant analysis and coupling coordination degree. Our methodology was applied to a typical coastal zone, Shenzhen Dapeng New District, in the Greater Bay Area of China. Over 80% of the beaches in the study area exhibited an imbalanced or barely balanced supply-demand of recreation services. We found that POIs density had a significant influence on a balanced supply-demand of BRS. Multi-source big data (POIs and Weibo check-in) provided an efficient, low-cost, and across-scale approach for public preference mapping than traditional questionnaire surveys. The proposed CES’s supply-demand framework can identify coastal beaches with imbalanced recreation and support sustainable coastal management. Coastal beach management prioritizes not only waste prevention and sufficient safety signs but also proper infrastructure development that contribute sustainably to the human well-being of nature experiences.