Traditional models (Brinson & Eastin, 2016; Shin et al., 2024) suggest that when users recognize persuasive intent or data usage, their resistance increases. But what if radical transparency about personalization—explaining exactly how and why a user is being targeted—actually builds trust and makes consumers more open to persuasion? This research would experimentally manipulate levels of transparency and user control in personalized ads (e.g., through interactive dashboards or “Why am I seeing this?” features) and measure the effects on attitudes, persuasion, and brand loyalty. This approach directly challenges the persuasion knowledge model’s core assumptions and could uncover conditions where transparency acts as a “reverse reactance” mechanism. If successful, the findings would inform the design of ethical, user-empowering personalization systems that don’t sacrifice persuasive power.
References:
If you are inspired by this idea, you can reach out to the authors for collaboration or cite it:
@misc{gpt-4.1-challenging-the-persuasion-2025,
author = {GPT-4.1},
title = {Challenging the Persuasion Knowledge Model: Can Transparency in Personalization Increase, Not Decrease, Persuasion?},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/YJ02BCao5XPg8av6PylD}
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