The objective of this paper was to explore a better pricing strategy by predicting contribution margin (CM) to drive wins at higher prices. This paper focused on the services industry, where macroeconomic factors play a key decisive role in arriving at contribution margin to win more deals in this competitive market. The paper incorporated prior research findings to develop a multidimensional and multifaceted framework depicting the methodology of formulating customer value for value-based pricing. The empirical portion of this paper contained a case study based on masked industry data from an industrial manufacturing company dealing with products and services. We discussed and highlighted the criticality of identifying and capturing the right features while creating the right pricing strategy using multiple linear regression and decision tree techniques. Applying the predictive analytics approach helped us estimate the contribution margin with a higher winning probability during contract negotiation. This paper would aid organizations to develop and implement an enterprise-wide strategic pricing discipline designed to bolster the value and impact of their products and service pricing.

1. Armstrong, G., Adam, S., Denize, S., & Kotler, P. (2014). Principles of marketing. Pearson Australia.
2. Baykara, B. (2015). Impact of evaluation methods on decision tree accuracy (Msc Thesis). School of Information Sciences, University of Tampere, Finland. https://core.ac.uk/download/pdf/250137461.pdf
3. Björk, H., & Forsberg, L. (2015). How to succeed with value-based pricing. KTH Industrial Engineering and Management Industrial Management, Stockholm, Sweden.
4. Bodea, T., & Ferguson, M. (2012). Pricing segmentation and analytics (1st edition). Business Expert Press Marketing Strategy Collection.
5. Brownlee, J. (2020). How to calculate feature importance with python. Machine Learning Mastery. https://machinelearningmastery.com/calculate-feature-importance-with-python/
6. Chan, K., Jubas, J., Kordes, B., & Sueling, M. (2014). Understanding your options : An overview of proven pricing strategies and how they work. McKinsey & Company.
7. Chan, M. (2017, December5). Discount pricing strategy explained. https://www.unleashedsoftware.com/blog/discount-pricing-strategy-explained
8. Claessens, M. (2018, June 27). Economic value estimation - How to estimate economic value ? Marketing Insider. https://marketing-insider.eu/economic-value-estimation/
9. Daly, J. L. (2002). Pricing for profitability. Wiley.
10. Jain, S., & Kamble, S. C. (2021). An analytical study of buyers' behaviour towards automatic fuel pricing and price smoothing in India. Prabandhan : Indian Journal of Management, 14(2), 40–59. https://doi.org/10.17010/pijom/2021/v14i2/157692
11. Kantardzic, M. (2011). Data mining : Concepts, models, methods, and algorithms. John Wiley & Sons.
12. Kotler, P., & Keller, K. (2014). Marketing management (15th edition). Prentice Hall.
13. Kuhn, M. & Johnson, K. (2019). Feature engineering and selection : A practical approach for predictive models.n Taylor & Francis Group. https://bookdown.org/max/FES/creating-dummy-variables-for-unordered-categories.html
14. Liberto, D. (2021). Bundling. https://www.investopedia.com/terms/b/bundling.asp
15. Monson, M. (2009). Valuation using hedonic pricing models. Cornell Real Estate Review, 7, 62–73.
16. Montgomery, D.C., Peck, E.A., & Vining, G.G. (2012). Introduction to linear regression analysis (5th edition). John Wiley & Sons.
17. Nagle, T., Hogan, J., & Zale, J. (2011). The strategy and tactics of pricing : A guide to growing more profitably (5th edition). Pearson.
18. Panigrahi S. K., Azizan, N. A., & Al - Shamsi, I. R. (2021). Product innovation, customer satisfaction, and brand loyalty of using smartphones among university students : PLS–SEM approach. Indian Journal of Marketing, 51(1), 8–25. https://doi.org/10.17010/ijom/2021/v51/i1/156931
19. Panigrahi, S. K., Azizan, N. A., & Khan, M. W. (2018). Investigating the empirical relationship between service quality, trust, satisfaction, and intention of customers purchasing life insurance products. Indian Journal of Marketing, 48(1), 28–46. https://doi.org/10.17010/ijom/2018/v48/i1/120734
20. Pwc. (2016). Driving retail growth by leveraging analytics. https://www.pwc.in/assets/pdfs/publications/2016/profitable-growth-for-retail-businesses-online.pdf
21. Senaviratna, N. A., & Cooray, T. M. (2019). Diagnosing multicollinearity of logistic regression model. Asian Journal of Probability and Statistics, 5(2), 1–9. https://doi.org/10.9734/ajpas/2019/v5i230132 Simon, H., & Fassnacht, M. (2018). Price management. Springer International Publishing.
22. Spann, M., Fischer, M., & Tellis, G. (2015). Skimming or penetration ? Strategic dynamic pricing for new products. Marketing Science, 34(2), 235–249. https://doi.org/10.1287/mksc.2014.0891
23. Survey King. (2021a.). A guide to the Van Westendorp price sensitivity meter. https://www.surveyking.com/help/vanwestendorpanalysis
24. Survey King.(2021b.). An interactive conjoint survey tutorial with sample data. https://www.surveyking.com/help/conjoint-analysis-explained
25. Tangirala, S. (2020). Evaluating the Impact of GINI Index and information gain on classification using decision tree classifier algorithm. International Journal of Advanced Computer Science and Applications, 11(2), 612–619. https://doi.org/10.14569/IJACSA.2020.0110277
26. Tatyana, N. - P. (2011). Value-based pricing : A success factor in the competitive struggle. Marketing, 42(4), 227–236. https://doi.org/10.5937/markt1104227N
27. Tay, R. (2017). Correlation, variance inflation and multicollinearity in regression model. Journal of Eastern Asia Transportation Society, 12, 2006–2015. https://doi.org/10.11175/easts.12.2006
28. Tofan, C.A. (2015). Decision tree method applied in cost-based decisions in an enterprise. Procedia Economics and Finance, 32, 1088–1092.
29. Wroblewski, J., & Loss, S. E. (2018). Understanding value-based pricing : Conceptualising customer value in a B2B industrial context. School of Economics and Management, Lund University. http://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=8949083&fileOId=8949087