Quantitative Analysis of Marketing Strategy Effective Marketing Management Approach

Erislan Erislan

Authors

Erislan Erislan Universitas Sahid Jakarta, Indonesia

Keywords:

Quantitative Approach, Marketing Management, Effectiveness, Challenges, Consumer Behavior

Abstract

In managing marketing strategies, a deep understanding of consumer behavior, market trends and competitive advantages is the main key to achieving success. The importance of effective marketing management is further strengthened by a quantitative approach. This research explores the significance of using a quantitative approach in marketing management and investigates its impact on effectiveness and the challenges it faces. This research uses quantitative methods to evaluate the contribution of statistical approaches and quantitative data analysis in improving the effectiveness of marketing management. Quantitative methods include regression analysis to assess the relationship between the use of a quantitative approach in marketing decision making and company sales growth, as well as ANOVA and correlation analysis to compare the success of marketing strategies. Research findings reveal that quantitative analysis provides valuable insights for designing more effective marketing campaigns and making informed decisions. However, some challenges such as data complexity and resistance to change were observed. Nevertheless, investments in information technology and employee training are proposed as solutions to overcome these obstacles. This research highlights the important role of quantitative approaches in improving marketing management practices.

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References

Aaker, D. A. (1996). Building Strong Brands. New York: Free Press.

Ahmad, A. Y. B., Gongada, T. N., Shrivastava, G., Gabbi, R. S., Islam, S., & Nagaraju, K. (2023). E-commerce trend analysis and management for Industry 5.0 using user data analysis. International Journal of Intelligent Systems and Applications in Engineering, 11(11s), 135-150.

Akter, S., Bandara, R., Hani, U., Wamba, S. F., Foropon, C., & Papadopoulos, T. (2019). Analytics-based decision-making for service systems: A qualitative study and agenda for future research. International Journal of Information Management, 48, 85-95.

Amir, L. R., Tanti, I., Maharani, D. A., Wimardhani, Y. S., Julia, V., Sulijaya, B., & Puspitawati, R. (2020). Student perspective of classroom and distance learning during COVID-19 pandemic in the undergraduate dental study program Universitas Indonesia. BMC medical education, 20, 1-8.

Anderson, J. C., Narus, J. A., & van Rossum, W. (2018). Business Market Management: Understanding, Creating, and Delivering Value (4th ed.). London: Pearson.

Berger, J., Humphreys, A., Ludwig, S., Moe, W. W., Netzer, O., & Schweidel, D. A. (2020). Uniting the tribes: Using text for marketing insight. Journal of marketing, 84(1), 1-25.

Chen, H., & Popovich, K. (2003). “Understanding Customer Relationship Management (CRM): People, Process and Technology.” Business Process Management Journal, 9(5), 672-688.

Cravens, D. W., & Piercy, N. F. (2019). Strategic Marketing (11th ed.). New York: McGraw-Hill Education.

Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: management, analysis and future prospects. Journal of big data, 6(1), 1-25.

Davenport, T. H., & Harris, J. (2007). Competing on Analytics: The New Science of Winning. Boston: Harvard Business Press.

Erlangga, H. (2021). Effect of digital marketing and social media on purchase intention of Smes food products. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(3), 3672-3678.

Garousi, V., Felderer, M., & Mäntylä, M. V. (2019). Guidelines for including grey literature and conducting multivocal literature reviews in software engineering. Information and software technology, 106, 101-121.

Gupta, S., Justy, T., Kamboj, S., Kumar, A., & Kristoffersen, E. (2021). Big data and firm marketing performance: Findings from knowledge-based view. Technological Forecasting and Social Change, 171, 120986.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Boston: Cengage Learning.

Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks, 3, 119-132.

J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Boston: Cengage Learning.

Kane, G. (2019). The technology fallacy: people are the real key to digital transformation. Research-Technology Management, 62(6), 44-49.

Keller, K. L., & Lehmann, D. R. (2006). Brands and branding: Research findings and future priorities. Marketing Science, 25(6), 740-759.

Kiron, D., Prentice, P. K., & Ferguson, R. B. (2012). "The Analytics Mandate." MIT Sloan Management Review, 53(1), 1-24.

Kotler, P., & Armstrong, G. (2020). Principles of Marketing (18th ed.). London: Pearson Education.

Kumar, A., Shankar, R., & Aljohani, N. R. (2020). A big data driven framework for demand-driven forecasting with effects of marketing-mix variables. Industrial marketing management, 90, 493-507.

Lanzolla, G., Pesce, D., & Tucci, C. L. (2021). The digital transformation of search and recombination in the innovation function: Tensions and an integrative framework. Journal of Product Innovation Management, 38(1), 90-113.

McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution Harvard Business Review, 90(10), 60-68.

Rindfleisch, A., & Moorman, C. (2001). “The Acquisition and Utilization of Information in New Product Alliances: A Strength-of-Ties Perspective.” Journal of Marketing, 65(2), 1-18.

Salminen, J., Guan, K., Jung, S. G., Chowdhury, S. A., & Jansen, B. J. (2020, April). A literature review of quantitative persona creation. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (pp. 1-14).

Stanton, W. J., Etzel, M. J., & Walker, B. J. (2019). Fundamentals of marketing. New York: McGraw-Hill Education.

Stylos, N., & Zwiegelaar, J. (2019). Big data as a game changer: how does it shape business intelligence within a tourism and hospitality industry context? (pp. 163-181). Springer Singapore.