Assessing the Efficacy of In-the-Moment Surveys Triggered by Geolocation Data: A Comparative Study of Beach Visitors
Year: 2025
Type: article
Abstract: Memory errors can undermine survey data quality, leading to discrepancies between reported and actual events. Surveying individuals at the moment they experience an event—or shortly thereafter—could enhance data quality. Advances in technology now enable real-time event detection and the immediate delivery of surveys to individuals as events occur. However, the practical feasibility and benefits of in-the-moment surveys compared to conventional retrospective surveys remain largely unexplored. This paper investigates the use of in-the-moment surveys triggered by geolocation data in an opt-in online panel. During July/August 2024, panelists visiting any of the 2,480 mainland beaches in Spain received survey invitations one hour after their arrival. The results were compared to a conventional survey conducted at the end of the same period, asking participants to retrospectively report their last beach visit. Findings indicate comparable participation and post-participation evaluations between methods. However, in-the-moment responses do not produce significant benefits in reducing explicit non-recall (“don’t know” answers), except for challenging questions that are difficult to reconstruct, and only among those responding while still at the beach (on-site participants); other data quality aspects did not improve. Nonetheless, this method allowed for the collection of specific information (e.g. photos) more conveniently gathered on-site. Significant disparities in substantive results were observed between methods, largely, but not solely, driven by differences in the events captured (e.g. timeframe and duration of beach visits). When compared with external sources, in-the-moment surveys demonstrated greater credibility.
Author: Carlos Ochoa
Institution: Universitat Pompeu Fabra
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,969
OpenAlex ID: W4416377605