IJSMT Journal

International Journal of Science, Strategic Management and Technology

An International, Peer-Reviewed, Open Access Scholarly Journal Indexed in recognized academic databases · DOI via Crossref The journal adheres to established scholarly publishing, peer-review, and research ethics guidelines set by the UGC

ISSN: 3108-1762 (Online)
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AD CAMPAIGN TRACKER

AUTHORS:
Yoheswari S
Sandhosini T S
Saai Ruba N B
Mentor
Affiliation
Department of Computer Science, K.L.N. College of Engineering, Anna University, Madurai, India
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract

The Ad Campaign Tracker and Campaign Health Monitoring System processes massive volumes of real-time digital advertising data impressions, clicks, conversions, costs and performance signals to deliver actionable insights while tackling two major industry problems: widespread ad fraud and low-quality / non- genuine user engagement. It continuously tracks core KPIs such as Click-Through Rate (CTR), Cost Per Mille (CPM), Cost Per Acquisition (CPA) and Return on Ad Spend (ROAS), runs a real-time fraud detection engine to flag suspicious behavioral patterns, and applies an attention-aware scoring model that evaluates true user interest and engagement quality far beyond simple click counts. These three dimensions performance, fraud cleanliness, and genuine attention depth are intelligently combined into a single unified campaign health score, automatically classifying every campaign as Healthy, Watchlist or Risk. A modern web-based dashboard provides live visualization of all key metrics, health scores, fraud alerts, trends and cross-campaign comparisons, giving advertisers instant visibility across hundreds or thousands of campaigns so they can react quickly to issues, eliminate large amounts of wasted ad spend, significantly improve advertising efficiency and ROI, and ultimately support cleaner, more responsible and sustainable digital advertising practices.

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S, Y., S, S. T. & B, S. R. N. (2026). Ad Campaign Tracker. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.019

S, Yoheswari, et al.. "Ad Campaign Tracker." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.019.

S, Yoheswari,Sandhosini S, and Saai B. "Ad Campaign Tracker." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.019.

References
1.Richardson, Matthew, Ewa Dominowska, and Robert “Predicting Clicks: Estimating the Click-Through Rate for New Ads.” Proceedings of the 16th International World Wide Web Conference (2007): 521–530.

2.He, Xinran, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, Stuart Bowers, and Joaquin Quiñonero

3.“Practical Lessons from Predicting Clicks on Ads at Facebook.” Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2014): 1–10.

4.McMahan, Brendan, Gary Holt, David Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lance Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, Sharat Chikkerur, and Dan Liu. “Ad Click Prediction: A View from the Trenches.” Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2013): 1222–1230.

5..Zhang, Weinan, Tianming Du, and Jun “Deep Learning over Multi-Field Categorical Data for Response Prediction.” European Conference on Information Retrieval (2016): 45–57.

6.Chaffey, Dave, and Fiona Ellis-Chadwick. Digital Marketing: Strategy, Implementation and Practice. 7th ed. Pearson Education Limited, 2019.
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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