UDTR Global Rights of Nature Radar

Integrating Secure Data Governance and Scalable Analytics for Intelligent Marketing

Identification

Public canonical key

doi:10.58482/ijersem.v2i3.48

Authors

R G Kumar · M. Pujitha · F Hussain Abbas · K Durga Hemanth Kumar · N K Mohanamithran

Reported year

2026

Reported language

en

Source type

article

First detected

2026-11-09T19:04:47.704224+00:00

Last metadata observation

2026-11-09T19:04:47.704224+00:00

Last HTTP verification

Not checked

Documentary abstract — original language

An intelligent and secure data-driven framework for online marketing that integrates data governance, scalable analytics, and AI-based decision support to enhance campaign performance.The proposed system begins with structured data collection and ingestion from multiple digital advertising sources, followed by strict GDPR-compliant data governance and privacy enforcement to ensure secure and ethical data handling.A comprehensive data preprocessing and quality assurance module removes inconsistencies, cleans outliers, and prepares high-quality data for analysis.The analytical core employs machine learning models, specifically Random Forest and Gradient Boosting, to predict campaign performance and optimize marketing strategies.Experimental results show that the Gradient Boosting model achieved a high prediction accuracy of 98.99%, outperforming traditional models.The system analyzed 4,454 marketing campaigns, of which 3,186 campaigns (71.5%) were successful, demonstrating strong predictive reliability.Financial analysis revealed a total advertising spend of $24.8 million, generating 1,049,598 conversions with an average ROI of 171.83%, highlighting the effectiveness of the proposed optimization strategy.Engagement analysis further indicated an average click-through rate (CTR) of 0.0797 and an average session duration of 311 seconds, reflecting strong user interaction and content relevance.The framework also integrates real-time dashboards for campaign monitoring and a feedback loop for continuous optimization, enabling dynamic budget reallocation, performance tracking, and data-driven decision-making.Overall, the proposed system successfully combines secure data governance, scalable AI analytics, and intelligent feedback mechanisms to deliver a robust, efficient, and privacy-aware marketing solution, making it highly suitable for modern digital advertising environment.

Identifiers

OPENALEX

W7153276926

DOI

10.58482/ijersem.v2i3.48

Documentary context

Documentary family

Scholarship

Source-reported types

article

Natural entities mentioned

Forest

Entity mentions are not evidence of legal recognition. Jurisdiction studied is separate from author affiliation country.

Sources

OpenAlex · Record 1 · Record 2

• DOI · https://doi.org/10.58482/ijersem.v2i3.48
• OpenAlex · https://openalex.org/W7153276926

Documented bibliographic relations

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• Deleuze and Big Data: How Facebook's Use of Big Data Analytics Shifts Legal Personhood, Privacy and Commercial Expression · CITES
• openalex:w3111394666 · CITES
• openalex:w3152412535 · CITES
• openalex:w3162208250 · CITES
• openalex:w3203136744 · CITES
• openalex:w3216380353 · CITES
• openalex:w4205924232 · CITES
• openalex:w7134937939 · CITES

0 incoming references within the detected corpus

Documentary status

Relevance pending

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