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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM64931

Predicting the Revenue of Zomato Using Least Squares Regression Based on Marketing Expenditure

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64931

Volume:

10 |

6 |

Jun 2026

Pages:

1-4

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM64931

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PST

Prof. Sonam Tiple

MBA

Tirpude Institute of Management Education Nagpur

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ARS

Aish Raj Singh

MBA

Tirpude Institute of Management Education Nagpur

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Abstract

This study develops a predictive model to estimate Zomato Ltd.'s fiscal revenue for FY2025 using the least squares regression algorithm with marketing/ad & promotion expenditure and time as independent variables. Based on fiscal data from FY2020 to FY2024, the regression model produced an R² of 0.936, suggesting high explanatory power. Using the derived equation and projecting marketing expenditures of ₹1972 crore for FY2025, the model forecasts revenue for FY2025. The paper presents methodology, a literature review focusing on predictive analytics in marketing and finance, detailed data analysis, and implications for strategic decision-making. Limitations and future research directions are discussed.

KEYWORDS

Predictive analytics least squares regression marketing expenditure revenue forecasting Zomato financial modeling.

Cite This Article

Prof. Sonam Tiple, Aish Raj Singh, "Predicting the Revenue of Zomato Using Least Squares Regression Based on Marketing Expenditure," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-4, Jun 2026. https://doi.org/10.55041/IJSREM64931

Full Article/Conclusion

This paper applied an OLS regression model to forecast Zomato's FY2025 revenue using historical fiscal data and projected marketing spend. The model's high R² indicates strong explanatory power within the sample; the point forecast under a ₹1972 crore marketing budget is approximately ₹16,235.96 crore.

References

[1] D. N. Gujarati, Basic Econometrics, 5th ed. McGraw-Hill, 2009. [2] D. C. Montgomery and E. A. Peck, Introduction to Linear Regression Analysis, 4th ed. Wiley, 2021. [3] P. K. Kannan and H. Li, “Digital marketing: A framework, review and research agenda,” Intern. J. Res. Mark., vol. 34, no. 1, pp. 22–45, 2017. [4] P. S. Farris et al., Marketing Metrics: The Manager's Guide to Measuring Marketing Performance, 4th ed. Pearson, 2020. [5] S. J. Bronnenberg and K. M. Xia, “Advertising and social network effects,” Marketing Science, vol. 39, no. 4, pp. 606–624, 2020. [6] J. Chen and Z. Zhang, “Combining econometric and machine learning methods for forecasting,” J. Forecasting, vol. 39, no. 2, pp. 235–251, 2020. [7] R. Damodaran, Investment Valuation: Tools and Techniques for Determining the Value of Any Asset, 3rd ed. Wiley, 2012. [8] A. Gupta and B. Singh, “Customer acquisition cost in food delivery platforms,” J. Digital Bus., vol. 5, no. 2, pp. 45–59, 2021. [9] L. Zhao et al., “Diminishing returns to advertising in app-based services,” Marketing Letters, vol. 31, pp. 101–118, 2020. [10] G. Box, G. M. Jenkins, and G. C. Reinsel, Time Series Analysis: Forecasting and Control, 5th ed. Wiley, 2015. [11] Zomato Ltd., Annual Reports FY2020–FY2024 (data provided by user).

Editorial & Review Transparency

Publication Date

6/13/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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