Message personalization and real-time adaptation as next innovations in sport sponsorship management?

Christoph Breuer

Felix Boronczyk

Christopher Rumpf

Message personalization and real-time adaptation as next innovations in sport sponsorship management? How run-of-play and team affiliation affect viewer response


  • Technical innovations in sport marketing allow for personalized sponsor messages.
  • Targeting viewers based on run-of-play can increase sponsor message efficiency.
  • Biometric data are collected in real time and analyzed using multilevel models.
  • Heart rate and eye-tracking data capture viewer response to sponsor messages.
  • Viewer arousal and attention vary with the run-of-play and their team affiliation.

The digitization of sports content and technological innovations in sports media offer disruptive new ways to adapt sponsor messages to real-time events during live broadcasts. To date, sponsorship management mostly ignores the run-of-play and viewers’ team affiliation. This paper seeks to demonstrate how a dynamic management approach can contribute to greater sponsor message efficiency. For this purpose, real-time data were collected during live broadcasts of the 2018 soccer World Cup. Arousal was captured using changes in heart rate, attention to sponsor brands was measured via eye tracking, and in-play betting odds were continuously obtained from a sports betting website. Mixed models predict viewer arousal and sponsor brand attention from biometric and betting data. Evidence is provided for how run-of-play and viewer characteristics affect sponsor message communication outcomes. The applicability of the models for distinctive sponsor exposure tactics is demonstrated, and the theoretical and managerial implications are outlined.

Data synchronization and analysis were conducted using the iMotions screen-based eye tracking module. All visible sponsor messages on the perimeter boards were detected and marked as so-called areas of interest. By matching the participant’s fixations (fixation filter = 100 ms) with these areas of interest in each time frame, the algorithm was able to determine the duration of gaze hits on the sponsor brand (so-called ‘glance duration’) as a measure of visual attention (Duchowski, 2007).

This publication uses ECG and Eye Tracking which is fully integrated into iMotions Lab

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