Searching for the "Holy Grail" of sponsorship-linked marketing: A generalizable sponsorship ROI model

Paper: arXiv 2305.09473

Authors: Jonathan A. Jensen

Abstract

Marketers routinely allocate a significant portion of their budget to sponsorship. However, isolating the return on investment from such efforts has remained a challenge. Thus, a dataset of more than 5,800 sponsorships is analyzed using survival analysis approaches that utilizes the sponsor’s renewal of the sponsorship as a proxy for positive ROI. In addition to its contribution to the sponsorship-linked marketing literature, the resulting model can be utilized by managers to generate predicted values relative to the sponsor’s probability of renewal and the ultimate duration of time the sponsor will remain with the property, representing a novel managerial contribution.

Complexity vs Empirical Score

• Math Complexity: 3.5/10
• Empirical Rigor: 6.5/10
• Quadrant: Street Traders — practical and empirical, lighter on theory

Why this score: The paper relies on applied statistical methods (survival analysis) rather than deep mathematical theory, making the math complexity relatively low. However, it demonstrates solid empirical rigor through a large dataset of over 5,800 sponsorships to model ROI via renewal probability.

Research Flowchart

  flowchart TD
    A[Goal: Measure Sponsorship ROI & Predict Renewal] --> B[Data Collection: 5,800+ Sponsorships]
    B --> C[Methodology: Survival Analysis Modeling]
    C --> D[Computational Process: Use Renewal as Positive ROI Proxy]
    D --> E[Key Outcome 1: Predict Sponsor Renewal Probability]
    D --> F[Key Outcome 2: Forecast Sponsorship Duration]