Interview completed: the application of survival analysis to detect factors influencing response rates in online surveys

Ákos Münnich, Mátyás Kocsis, Mark C. Mainwaring, István Fónagy and Jenő Nagy ()
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Ákos Münnich: University of Debrecen
Mátyás Kocsis: DataExpert Services Ltd
Mark C. Mainwaring: Bangor University
István Fónagy: DataExpert Services Ltd
Jenő Nagy: DataExpert Services Ltd

Journal of Marketing Analytics, 2025, vol. 13, issue 1, No 14, 202-217

Abstract: Abstract Marketing interviews are widely used to acquire information on the behaviour, satisfaction, and/or needs of customers. Although online surveys are broadly available, one of the major challenges is to collect high-quality data, which is fundamental for marketing. Since online surveys are mostly unsupervised, the possibility of providing false answers is high, and large numbers of participants do not finish interviews, yet our understanding of the reasons behind this pattern remains unclear. Here, we examined the possible factors influencing response rates and aimed to investigate the impact of technical and demographic information on the probability of interview completion rates of multiple surveys. We applied survival analysis and proportional hazards models to statistically evaluate the associations between the probability of survey completion and the technical and demographic information of the respondents. More complex surveys had lower completion probabilities, although survey completion was increased when respondents used desktop computers and not mobile devices, and when surveys were translated to their native language. Meanwhile, age and gender did not influence completion rates, but the pool of respondents invited to complete the survey did affect completion rates. These findings can be used to improve online surveys to achieve higher completion rates and collect more accurate data.

Keywords: Online survey; Completion probability; Response rate; Hazard ratio; Optimisation; Cox’s regression; Technical conditions; Time-dependent processes (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1057/s41270-023-00282-y

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