Evaluating the Impact of Cold Email Outreach Channel Using a Fuzzy Decision-Making Framework

Raiha Imran; Khadija Basharat; Kifayat Ullah

Authors

Raiha Imran Department of Mathematics, Riphah International University, Lahore, Pakistan Author https://orcid.org/0009-0002-8678-504X
Khadija Basharat Department of Mathematics, Riphah International University, Lahore, Pakistan Author https://orcid.org/0009-0003-0979-7335
Kifayat Ullah 1) Department of Mathematics, Riphah International University, Lahore, Pakistan; 2) Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Tamil Nadu, India Author https://orcid.org/0000-0002-1438-6413

Keywords:

Cold email outreach, Digital Marketing Optimization, Circular q-rung Orthopair fuzzy sets, MAIRCA model, MCDM, Decision making framework

Abstract

Cold emailing is the most popular technique for B2B lead generation, but it is hard to select the best option due to uncertainty, subjective judgment, and the dynamic behaviour of users. Conventional analytical models usually do not recognize qualitative aspects such as personalization, timing sensitivity, and user perception and hence provide inconsistent decision-making. To overcome this shortcoming, this paper presents a new decision-making model that incorporates circular q-rung orthopair fuzzy sets (Cq-RoFS) combined with the MAIRCA approach. The proposed method is useful in modelling uncertainty, hesitation, and linguistic ambiguity, as well as offering a deviation-based comparative analysis of options. A study is carried out in a SaaS setting where five cold email strategies are assessed using four benefit criteria. The judgments of the experts, in the form of linguistic expressions, are converted into Cq-RoFS values and processed within the suggested framework. The findings show that the hybrid semi-automated approach has the lowest degree of deviation, which means that it is the most efficient one, followed by AI-adaptive and bulk automated strategies. The sensitivity analysis of parameter q at different values also proves that the model is stable and robust, and no rank reversal has been noted. The research paper reveals the necessity of a balance between personalization and automation in cold email campaigns and shows that the proposed framework is superior in its ability to manage complex and uncertain decision-making conditions. The Cq-RoFS MAIRCA model enhances the evolution of fuzzy multi-criteria decision-making and provides a useful, dependable, and comprehensible instrument to streamline digital marketing initiatives.

Downloads

Download data is not yet available.

References

Zhou, M., Abhishek, V., Kennedy, E. H., Srinivasan, K., & Sinha, R. (2025). Linking Clicks to Bricks: Understanding the Effects of Email Advertising on Multichannel Sales. Information Systems Research, 36, 225–238. https://doi.org/10.1287/isre.2020.0557

Heinzel, M., Weaver, C., & Briggs, R. (2025). Incentivizing Responses in International Organization Elite Surveys: Evidence from the World Bank. Journal of Experimental Political Science, 12, 17–26. https://doi.org/10.1017/XPS.2023.39

Pereira, M. M., Giger, N., Perez, M. D., & Axelsson, K. (2025). Encouraging Politicians to Act on Climate: A Field Experiment with Local Officials in Six Countries. American J Political Sci, 69, 148–163. https://doi.org/10.1111/ajps.12841

Mastykina, A. (2025). Best Practices for Scaling Cold Outreach Processes in Global Fundraising. ULBEC, 02, 01–06. https://doi.org/10.70315/uloap.ulbec.2025.0203001

Gornall, W., & Strebulaev, I. A. (2025). Gender, Race, and Entrepreneurship: A Randomized Field Experiment on Venture Capitalists and Angels. Management Science, 71, 5308–5327. https://doi.org/10.1287/mnsc.2024.4990

Pinar, A. (2025). An Integrated Sentiment Analysis and Q-Rung Orthopair Fuzzy MCDM Model for Supplier Selection in E-Commerce: A Comprehensive Approach. Electron Commer Res, 25, 1311–1342. https://doi.org/10.1007/s10660-023-09768-4

Subrata, S. A. (2025). Email Ethics for Authors: From the World of Publication Process. Inn. Health. and Soc, 5, 63–69. https://doi.org/10.31603/ihs.14027

Wahab, F. K., & Akintade, E. A. (2025). Exploring the Impact of E-Marketing Strategies on Overtourism: Assessing the Prospects and Challenges in the Hospitality and Tourism Industries. Solutions for Managing Overtourism in Popular Destinations, 23–36. https://doi.org/10.4018/979-8-3693-8347-6.ch002

Bouke, M. A., Alramli, O. I., & Abdullah, A. (2025). XAIRF-WFP: A Novel XAI-Based Random Forest Classifier for Advanced Email Spam Detection. Int. J. Inf. Secur., 24, 5. https://doi.org/10.1007/s10207-024-00920-1

Gohil, D., Parmar, F., Prajapati, D., Poriya, Y., & Iyer, S. (2025). Ai-Powered Cold Email Automation for Staffing Solutions: Enhancing Personalization and Efficiency Through Open-Source Large Language Models. In Proceedings of the 2025 Third International Conference on Networks, Multimedia and Information Technology (NMITCON) (pp. 01–07). IEEE.

Miettilä, S. (2025). Should B2B Companies Utilize Automated Cold Emails for Lead Generation? Assessing the Potential of Automated Cold Emails for B2B Lead Generation. http://www.theseus.fi/handle/10024/884007

Brachten, M. (2025). Impact of AI Personalization on Email Clicks and Conversions: Insights from a Real-World AI-Personalized Phishing Simulation (Master Thesis).

Bawah, K. (2025). Bridging the Equity Gap: How AI-Powered Digital Marketing Can Transform Public Health in Underserved Communities.

Chinnaraju, A. (2025). Explainable AI (XAI) for Trustworthy and Transparent Decision-Making: A Theoretical Framework for AI Interpretability. World Journal of Advanced Engineering Technology and Sciences, 14, 170–207.

Miettilä, S. (2025). Should B2B Companies Utilize Automated Cold Emails for Lead Generation?: Assessing the Potential of Automated Cold Emails for B2B Lead Generation.

Bouke, M. A., Alramli, O. I., & Abdullah, A. (2025). XAIRF-WFP: A Novel XAI-Based Random Forest Classifier for Advanced Email Spam Detection. Int. J. Inf. Secur., 24, 5. https://doi.org/10.1007/s10207-024-00920-1

Kleinert, S., & Hildebrand, M. (2025). Venture Capitalists' Decision-Making in Hot and Cold Markets: The Effect of Signals and Cheap Talk. Entrepreneurship Theory and Practice, 49, 571–598. https://doi.org/10.1177/10422587241268311

Gornall, W., & Strebulaev, I. A. (2025). Gender, Race, and Entrepreneurship: A Randomized Field Experiment on Venture Capitalists and Angels. Management Science, 71, 5308–5327. https://doi.org/10.1287/mnsc.2024.4990

Bleda, M., & Pinkse, J. (2025). Leaving the Cold Behind: The Role of Emotions and Cognitive Biases in Business Adaptation to Climate Change. Business & Society, 64, 9–44. https://doi.org/10.1177/00076503231219692

Zadeh, L. A. (1965). Fuzzy Sets. Information and Control, 8, 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X

Atanassov, K. (1986). Intuitionistic Fuzzy Sets. Fuzzy Sets and Systems, 20, 87–96. https://doi.org/10.1016/S0165-0114(86)80034-3

Yager, R. R. (2013). Pythagorean Fuzzy Subsets. In Proceedings of the 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS) (pp. 57–61). IEEE. https://doi.org/10.1109/IFSA-NAFIPS.2013.6608375

Yager, R. R. (2016). Generalized Orthopair Fuzzy Sets. IEEE Transactions on Fuzzy Systems, 25, 1222–1230. https://doi.org/10.1109/TFUZZ.2016.2604005

Imran, R., Ullah, K., Ali, Z., Shang, Y., & Senapati, T. (n.d.). Exploring Risk Management in Smart Banking Systems through the Circular Intuitionistic Fuzzy Bonferroni Means Aggregation Operator. https://doi.org/10.7717/peerj-cs.3791

Imran, R., Ullah, K., Ali, Z., Pamucar, D., & Simic, V. (2026). Uncertainty-Driven Assessment of Floating Photovoltaic Hydropower Wind Hybrid Energy Systems Using a Circular Neutrosophic Approach. Engineering Applications of Artificial Intelligence, 174, 114474. https://doi.org/10.1016/j.engappai.2026.114474

Imran, R., Amin, M., Ullah, K., Pamucar, D., Ali, Z., Saidani, O., & Simic, V. (2025). A Data-Driven Approach to Tackling Academic Stress-Coping and Mental Health Issues in College Students Using Spherical Fuzzy MARCOS Methodology. Applied Soft Computing, 113925. https://doi.org/10.1016/j.asoc.2025.113925

Imran, R., Ullah, K., Ali, Z., & Akram, M. (2024). A Multi-Criteria Group Decision-Making Approach For Robot Selection Using Interval-Valued Intuitionistic Fuzzy Information And Aczel-Alsina Bonferroni Means. Spectrum of Decision Making and Applications, 1, 1–31. https://doi.org/10.31181/sdmap1120241

Atanassov, K. T. (2020). Circular Intuitionistic Fuzzy Sets. Journal of Intelligent & Fuzzy Systems, 39, 5981–5986.

Bozyigit, M. C., Olgun, M., & Ünver, M. (2023). Circular Pythagorean Fuzzy Sets and Applications to Multi-Criteria Decision Making. Informatica, 34, 713–742. https://doi.org/10.15388/23-INFOR529

Wolfe, R., & Mitra, T. (2024). The Impact and Opportunities of Generative AI in Fact-Checking. In Proceedings of the The 2024 ACM Conference on Fairness, Accountability, and Transparency (pp. 1531–1543). ACM.

Verma, C., Vijayalakshmi, P., Chaturvedi, N., Umesh, U., Rai, A., & Ahmad, A. Y. B. (2025). Artificial Intelligence in Marketing Management: Enhancing Customer Engagement and Personalization. In Proceedings of the 2025 International Conference on Pervasive Computational Technologies (ICPCT) (pp. 397–401). IEEE. https://doi.org/10.1109/ICPCT64145.2025.10940626

Angappan, S., Nataraj, A., Krishnan, L. N., & Palanisamy, A. (2025). Development of an Internet of Things Based Smart Cold Storage with Inventory Monitoring System. International Journal of Electrical & Computer Engineering (2088-8708), 15. http://doi.org/10.11591/ijece.v15i1.pp89-98

Miettilä, S. (2025). Should B2B Companies Utilize Automated Cold Emails for Lead Generation?: Assessing the Potential of Automated Cold Emails for B2B Lead Generation.

Bouke, M. A., Alramli, O. I., & Abdullah, A. (2025). XAIRF-WFP: A Novel XAI-Based Random Forest Classifier for Advanced Email Spam Detection. International Journal of Information Security, 24, 5. https://doi.org/10.1007/s10207-024-00920-1

Ali, Z., & Yang, M.-S. (2024). On Circular Q-Rung Orthopair Fuzzy Sets with Dombi Aggregation Operators and Application to Symmetry Analysis in Artificial Intelligence. Symmetry, 16, 260. https://doi.org/10.3390/sym16030260

Emam, W., Amin, M., Imran, R., Nazeer, M. S., Ullah, K., & Ali, Z. (2025). TOPSIS Driven Complex Picture Fuzzy Approach for Speech Matching and Sports Training Feature Recognition. Scientific Reports, 15, 34136. https://doi.org/10.1038/s41598-025-03572-w