Data Privacy and Ethics in Digital Marketing: A Risk Analysis Using Logistic Regression Models - Mohammad, Suleiman Ibrahim Shelash; Alenazi, Sultan Alaswad; Al Oraini, Badrea; Khraiwish, Ahmad; Vasudevan, Asokan; Jing, Khoo Wuan (International Review of Management and Marketing, 2026)
This research looks at the success of digital campaigns considering imposed regulations of data privacy, driven by the main factors, compliance with the legislation about privacy, use of personal data, trust of consumers, and perceived risk. Based on a sample marketing campaign dataset, this research applies logistic regression models, risk analysis, and sensitivity analysis to 250 marketing campaigns featuring how adherence to privacy regulations such as GDPR and CCPA influences the outcomes of campaigns. The final result shows that compliance with all privacy regulations is the key factor in minimizing risks and ensuring the enhancement of campaign performance. It means campaigns that adhere to privacy laws have a higher chance of success, whereas all other campaigns that do not comply carry a high risk of failure. Further, personalized data use was seen as a very important factor in making the campaign successful and underpinned the use of customized marketing strategies that needed to be fitted within the regulations. However, consumer trust and perceived risk were not seen to have a statistically significant effect as direct influencers on the outcome of the campaign hence, the effect must be indirect or context-specific also. A limitation with this study is that it could not look into sectoral variation since the data did not depict industries. This research emphasizes that personalized marketing strategies balance well with the strict adherence to the privacy regulations for ideal results. With data-privacy concerns still evolving, integrating compliance into the strategies will surely help the digital marketer not only avoid legal risks but also build trust among consumers for long-term success.