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Data Privacy and Ethics in Digital Marketing: A Risk Analysis Using Logistic Regression Models
Mohammad, Suleiman Alenazi, Sultan Al Oraini, Badrea Vasudevan, Asokan Jing, Khoo
Mohammad, Suleiman
Alenazi, Sultan
Al Oraini, Badrea
Vasudevan, Asokan
Jing, Khoo
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2026-02-01
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IRMM.pdf
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Abstract
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.
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