Citation:

Bhageerath Bogi, 2024. "Leveraging A/B Testing and Synthetic Control Methods for Effective Model Evaluation in Retail Analytics", ESP Journal of Engineering & Technology Advancements  4(4): 140-148.

Abstract:

In the following report, the author examines the application of A/B Testing and Synthetic Control methods for model evaluation in the domain of retail analytics. One of the most popular experimental methods is called A/B testing, and it is used in retail to determine the success of particular marketing campaigns and both the location and the style of products within the store as well as website layouts. But it may be confined in specific situations, including cases with more than two treatment groups and non-observable kinds of variables. While other methods ignore the data from control units or only use them for comparison, Syn-Control, an enhanced causal inference technique provides an answer to this problem by creating a weighted sum of control units to estimate the counterfactual value. This paper outlines the theoretical frameworks, strengths and weaknesses of both methods and provides a synthesis of each in the retail context.

References:

[1] Abdul-Yekeen, A.M., Kolawole, M.A., Iyanda, B. and Abdul-Yekeen, H.A., 2024. Leveraging Predictive Analytics to Optimize SME Marketing Strategies in the US. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online), 3(3), pp.73-102.

[2] Barajas, J., Zidar, T. and Bay, M., 2020. Advertising Incrementality Measurement using Controlled Geo-Experiments: The Universal App Campaign Case Study. ACM: Washington, DC, USA.

[3] Benjamin, L.B., Amajuoyi, P. and Adeusi, K.B., 2024. Leveraging data analytics for informed product development from conception to launch. GSC Advanced Research and Reviews, 19(2), pp.230-248.

[4] Berman, R. and Israeli, A., 2022. The value of descriptive analytics: Evidence from online retailers. Marketing Science, 41(6), pp.1074-1096.

[5] Boppiniti, S.T., 2022. Exploring the Synergy of AI, ML, and Data Analytics in Enhancing Customer Experience and Personalization. International Machine learning journal and Computer Engineering, 5(5).

[6] Farias, V., Li, A. and Peng, T., 2021. Learning treatment effects in panels with general intervention patterns. Advances in Neural Information Processing Systems, 34, pp.14001-14013.

[7] Kalusivalingam, A.K., Sharma, A., Patel, N. and Singh, V., 2020. Leveraging Deep Reinforcement Learning and Real-Time Stream Processing for Enhanced Retail Analytics. International Journal of AI and ML, 1(2).

[8] Kalusivalingam, A.K., Sharma, A., Patel, N. and Singh, V., 2022. Optimizing E-Commerce Revenue: Leveraging Reinforcement Learning and Neural Networks for AI-Powered Dynamic Pricing. International Journal of AI and ML, 3(9).

[9] Koning, R., Hasan, S. and Chatterji, A., 2022. Experimentation and start-up performance: Evidence from A/B testing. Management Science, 68(9), pp.6434-6453.

[10] Lopez, S. and Arjunan, G., 2023. Optimizing marketing ROI with predictive analytics: Harnessing big data and AI for data-driven decision making. Journal of Artificial Intelligence Research, 3(2), pp.9-36.

[11] Tierney, G., Hellmayr, C., Barkimer, G., Li, K. and West, M., 2023. Multivariate Bayesian dynamic modeling for causal prediction. arXiv preprint arXiv:2302.03200.

[12] York, P. and Bamberger, M., 2024. The applications of big data to strengthen evaluation. In Artificial intelligence and evaluation (pp. 37-55). Routledge.

[13] Kola, H. G. (2024). Optimizing ETL Processes for Big Data Applications. International Journal of Engineering and Management Research, 14(5), 148-161.

[14] SQL in Data Engineering: Techniques for Large Datasets. (2023). International Journal of Open Publication and Exploration, ISSN: 3006-2853, 11(2), 36-51. https://ijope.com/index.php/home/article/view/165

[15] Data Integration Strategies in Cloud-Based ETL Systems. (2023). International Journal of Transcontinental Discoveries, ISSN: 3006-628X, 10(1), 48-

[16] 62. https://internationaljournals.org/index.php/ijtd/article/view/116

[17] Harish Goud Kola. (2024). Real-Time Data Engineering in the Financial Sector. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(3), 382–396. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/143

[18] Harish Goud Kola. (2022). Best Practices for Data Transformation in Healthcare ETL. Edu Journal of International Affairs and Research, ISSN: 2583-9993, 1(1), 57–73. Retrieved from https://edupublications.com/index.php/ejiar/article/view/106

[19] Bussa, S. (2023). Enhancing BI tools for improved data visualization and insights. International Journal of Computer Science and Mobile Computing, 12(2), 70–92. https://doi.org/10.47760/ijcsmc.2023.v12i02.005

[20] Sai Krishna Shiramshetty. (2024). Enhancing SQL Performance for Real-Time Business Intelligence Applications. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(3), 282–297. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/138

[21] Sai Krishna Shiramshetty, "Big Data Analytics in Civil Engineering : Use Cases and Techniques", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 3, Issue 1, pp.39-46, January-February.2019 URL : https://ijsrce.com/IJSRCE19318

[22] Sai Krishna Shiramshetty, " Data Integration Techniques for Cross-Platform Analytics, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 4, pp.593-599, July-August-2020. Available at doi : https://doi.org/10.32628/CSEIT2064139

[23] Shiramshetty, S. K. (2021). SQL BI Optimization Strategies in Finance and Banking. Integrated Journal for Research in Arts and Humanities, 1(1), 106–116. https://doi.org/10.55544/ijrah.1.1.15

[24] Sai Krishna Shiramshetty. (2022). Predictive Analytics Using SQL for Operations Management. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 11(2), 433–448. Retrieved from https://eduzonejournal.com/index.php/eiprmj/article/view/693

[25] Sai Krishna Shiramshetty. (2024). Comparative Study of BI Tools for Real-Time Analytics. International Journal of Research and Review Techniques, 3(3), 1–13. Retrieved from https://ijrrt.com/index.php/ijrrt/article/view/210

[26] Sai Krishna Shiramshetty "Leveraging BI Development for Decision-Making in Large Enterprises" Iconic Research And Engineering Journals Volume 8 Issue 5 2024 Page 548-560

[27] Shiramshetty, S. K. (2023). Advanced SQL Query Techniques for Data Analysis in Healthcare. Journal for Research in Iconic Research And Engineering JournalsApplied Sciences and Biotechnology, 2(4), 248–258. https://doi.org/10.55544/jrasb.2.4.33

[28] Sai Krishna Shiramshetty "Integrating SQL with Machine Learning for Predictive Insights" Iconic Research And Engineering Journals Volume 1 Issue 10 2018 Page 287-292

[29] Shiramshetty, S. K. (2023). Advanced SQL Query Techniques for Data Analysis in Healthcare. Journal for Research in Applied Sciences and Biotechnology, 2(4), 248–258. https://doi.org/10.55544/jrasb.2.4.33

[30] Shiramshetty, S. K. (2023). Advanced SQL Query Techniques for Data Analysis in Healthcare. Journal for Research in Applied Sciences and Biotechnology, 2(4), 248–258. https://doi.org/10.55544/jrasb.2.4.33

[31] Mouna Mothey. (2022). Automation in Quality Assurance: Tools and Techniques for Modern IT. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 11(1), 346–364. Retrieved from https://eduzonejournal.com/index.php/eiprmj/article/view/694

[32] Mothey, M. (2022). Leveraging Digital Science for Improved QA Methodologies. Stallion Journal for Multidisciplinary Associated Research Studies, 1(6), 35–53. https://doi.org/10.55544/sjmars.1.6.7

[33] Mothey, M. (2023). Artificial Intelligence in Automated Testing Environments. Stallion Journal for Multidisciplinary Associated Research Studies, 2(4), 41–54. https://doi.org/10.55544/sjmars.2.4.5

[34] Mouna Mothey. (2024). Test Automation Frameworks for Data-Driven Applications. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(3), 361–381. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/142

[35] Bagam, N., Shiramshetty, S. K., Mothey, M., Annam, S. N., & Bussa, S. (2024). Machine Learning Applications in Telecom and Banking. Integrated Journal for Research in Arts and Humanities, 4(6), 57–69. https://doi.org/10.55544/ijrah.4.6.8

[36] Annam, S. (2023). Data security protocols in telecommunication systems. International Journal for Innovative Engineering and Management Research, 8(10), 88–106. https://www.ijiemr.org/downloads/paper/Volume-8/data-security-protocols-in-telecommunication-systems

[37] Annam, S. N. (2023). Enhancing IT support for enterprise-scale applications. International Journal of Enhanced Research in Science, Technology & Engineering, 12(3), 205. https://www.erpublications.com/uploaded_files/download/sri-nikhil-annam_urfNc.pdf

[38] Santhosh Bussa, "Advancements in Automated ETL Testing for Financial Applications", IJRAR - International Journal of Research and Analytical Reviews (IJRAR), E-ISSN 2348-1269, P- ISSN 2349-5138, Volume.7, Issue 4, Page No pp.426-443, November 2020, Available at : http://www.ijrar.org/IJRAR2AA1744.pdf

[39] Bussa, S. (2023). Artificial Intelligence in Quality Assurance for Software Systems. Stallion Journal for Multidisciplinary Associated Research Studies, 2(2), 15–26. https://doi.org/10.55544/sjmars.2.2.2.

[40] Bussa, S. (2021). Challenges and solutions in optimizing data pipelines. International Journal for Innovative Engineering and Management Research, 10(12), 325–341. https://sjmars.com/index.php/sjmars/article/view/116

[41] Bussa, S. (2022). Machine Learning in Predictive Quality Assurance. Stallion Journal for Multidisciplinary Associated Research Studies, 1(6), 54–66. https://doi.org/10.55544/sjmars.1.6.8

[42] Bussa, S. (2022). Emerging trends in QA testing for AI-driven software. International Journal of All Research Education and Scientific Methods (IJARESM, 10(11), 1712. Retrieved from http://www.ijaresm.com

[43] Santhosh Bussa. (2024). Evolution of Data Engineering in Modern Software Development. Journal of Sustainable Solutions, 1(4), 116–130. https://doi.org/10.36676/j.sust.sol.v1.i4.43

[44] Santhosh Bussa. (2024). Big Data Analytics in Financial Systems Testing. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(3), 506–521. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/150

[45] Bussa, S. (2019). AI-driven test automation frameworks. International Journal for Innovative Engineering and Management Research, 8(10), 68–87. Retrieved from https://www.ijiemr.org/public/uploads/paper/427801732865437.pdf

[46] Santhosh Bussa. (2023). Role of Data Science in Improving Software Reliability and Performance. Edu Journal of International Affairs and Research, ISSN: 2583-9993, 2(4), 95–111. Retrieved from https://edupublications.com/index.php/ejiar/article/view/111

[47] Sri Nikhil Annam, " IT Leadership Strategies for High-Performance Teams, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 1, pp.302-317, January-February-2021. Available at doi : https://doi.org/10.32628/CSEIT228127

[48] Annam, S. N. (2024). Comparative Analysis of IT Management Tools in Healthcare. Stallion Journal for Multidisciplinary Associated Research Studies, 3(5), 72–86. https://doi.org/10.55544/sjmars.3.5.9.

[49] Annam, N. (2024). AI-Driven Solutions for IT Resource Management. International Journal of Engineering and Management Research, 14(6), 15–30. https://doi.org/10.31033/ijemr.14.6.15-30

[50] Annam, S. N. (2022). Optimizing IT Infrastructure for Business Continuity. Stallion Journal for Multidisciplinary Associated Research Studies, 1(5), 31–42. https://doi.org/10.55544/sjmars.1.5.7

[51] Sri Nikhil Annam , " Managing IT Operations in a Remote Work Environment, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 5, pp.353-368, September-October-2022. https://ijsrcseit.com/paper/CSEIT23902179.pdf

[52] Naveen Bagam. (2024). Data Integration Across Platforms: A Comprehensive Analysis of Techniques, Challenges, and Future Directions. International Journal of Intelligent Systems and Applications in Engineering, 12(23s), 902–919. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7062

[53] Naveen Bagam, Sai Krishna Shiramshetty, Mouna Mothey, Harish Goud Kola, Sri Nikhil Annam, & Santhosh Bussa. (2024). Advancements in Quality Assurance and Testing in Data Analytics. Journal of Computational Analysis and Applications (JoCAAA), 33(08), 860–878. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/1487

[54] Bagam, N., Shiramshetty, S. K., Mothey, M., Kola, H. G., Annam, S. N., & Bussa, S. (2024). Optimizing SQL for BI in diverse engineering fields. International Journal of Communication Networks and Information Security, 16(5). https://ijcnis.org/

[55] Bagam, N., Shiramshetty, S. K., Mothey, M., Annam, S. N., & Bussa, S. (2024). Machine Learning Applications in Telecom and Banking. Integrated Journal for Research in Arts and Humanities, 4(6), 57–69. https://doi.org/10.55544/ijrah.4.6.8

[56] Bagam, N., Shiramshetty, S. K., Mothey, M., Kola, H. G., Annam, S. N., & Bussa, S. (2024). Collaborative approaches in data engineering and analytics. International Journal of Communication Networks and Information Security, 16(5). https://ijcnis.org/

[57] Kola, H. G. (2024). Optimizing ETL Processes for Big Data Applications. International Journal of Engineering and Management Research, 14(5), 99–112. https://doi.org/10.5281/zenodo.14184235

[58] SQL in Data Engineering: Techniques for Large Datasets. (2023). International Journal of Open Publication and Exploration, ISSN: 3006-2853, 11(2), 36-51. https://ijope.com/index.php/home/article/view/165

[59] Data Integration Strategies in Cloud-Based ETL Systems. (2023). International Journal of Transcontinental Discoveries, ISSN: 3006-628X, 10(1), 48-62. https://internationaljournals.org/index.php/ijtd/article/view/116

[60] Harish Goud Kola. (2024). Real-Time Data Engineering in the Financial Sector. International Journal of Multidisciplinary Innovation and Research Methodology, ISSN: 2960-2068, 3(3), 382–396. Retrieved from https://ijmirm.com/index.php/ijmirm/article/view/143

[61] Harish Goud Kola. (2022). Best Practices for Data Transformation in Healthcare ETL. Edu Journal of International Affairs and Research, ISSN: 2583-9993, 1(1), 57–73. Retrieved from https://edupublications.com/index.php/ejiar/article/view/106

[62] Kola, H. G. (2018). Data warehousing solutions for scalable ETL pipelines. International Journal of Scientific Research in Science, Engineering and Technology, 4(8), 762. https://doi.org/10.1.1.123.4567

[63] Harish Goud Kola, " Building Robust ETL Systems for Data Analytics in Telecom , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 3, pp.694-700, May-June-2019. Available at doi : https://doi.org/10.32628/CSEIT1952292

[64] Kola, H. G. (2022). Data security in ETL processes for financial applications. International Journal of Enhanced Research in Science, Technology & Engineering, 11(9), 55. https://ijsrcseit.com/CSEIT1952292

[65] Annam, S. N. (2020). Innovation in IT project management for banking systems. International Journal of Enhanced Research in Science, Technology & Engineering, 9(10), 19. https://www.erpublications.com/uploaded_files/download/sri-nikhil-annam_gBNPz.pdf

[66] Annam, S. N. (2018). Emerging trends in IT management for large corporations. International Journal of Scientific Research in Science, Engineering and Technology, 4(8), 770. https://ijsrset.com/paper/12213.pdf

Keywords:

: A/B Testing, Synthetic Control, Retail Analytics, Model Evaluation, Causal Inference, Experimental Design, Retail Decision-Making