519.866 Mathematical modeling of an advertising campaign

Chibisova A. V. (Bauman Moscow State Technical University), Shinakov D. S. (Bauman Moscow State Technical University)

ADVERTISING CAMPAIGN, ADVERTISING BUDGET, PARETO BOUNDARY, TARGETED ADVERTISING, OPTIMAL ADVERTISING STRATEGIES, MATHEMATICAL MODELING IN MARKETING


doi: 10.18698/2309-3684-2022-3-8497


This article proposes a method for optimizing the dynamic budget allocation policy for an advertising campaign placed through an advertising tool built into the search engine. This method takes into account the unique features of social media marketing, provides an optimal budget allocation policy over time for one advertising campaign and minimizes the duration of the campaign, taking into account the specific budget and the desired level of coverage of each marketing segment. The model includes a general "efficiency function" that determines the relationship between the cost of an advertising bid at a given time and the number of new users shown at that time. This goal is achieved by implementing an algorithm for optimal solution of the problem of dynamic distribution of the advertising budget under certain boundary conditions, as well as by analyzing data on advertising campaign for June 2018. In the course of the study, an algorithm for optimal solution of the problem of dynamic distribution of the advertising budget under appropriate boundary conditions was implemented, examples of specific cases of the efficiency function were given and some models of real advertising campaigns of the enterprise were analyzed. Then, the data registered by the advertising agency of a particular enterprise was analyzed in relation to an advertising campaign registeredusing a built-in search engine tool for calculating bids and audience coverage for 30 days.


Magomadov E.M., Murtazalieva A.H. The use of economic and mathematical models in the digital transformation of economic relations. Economic and Law Issues, 2020, no. 141, pp. 43–47.
Pinson K.Yu., Osobennosti targetirovannoj reklamy v social'nyh setyah [Features of targeted advertising in social networks]. Innovative technologies of scientific development: A collection of articles of the International Scientific and Practical Conference. Part 2, Kazan, 2017, pp. 40-43.
Semiglazov A.M., Semiglazov V.A., Ivanov K.I. Mathematical modeling an advertising campaign. Proceedings of TUSUR University, 2010, no. 2–1 (22), pp. 342–349.
Dimitrienko Yu.I., Dimitnenko O.Yu. Nonrigid cluster model for analysis of dynamic data in economics. Information technologies, 2010, no. 9, pp. 43–50.
Dimitrienko Y.I., Dimitrienko O.Y. A model of multidimensional deformable continuum for forecasting the dynamics of large scale array of individual data. Mathematical Modeling and Computational Methods, 2016, no. 1, pp. 105–122.
Livshin D.A., Voronova L.I. Matematicheskoe modelirovanie v marketinge pri postroenii reklamnyh kampanij [Mathematical modeling in marketing when building advertising campaigns]. Sovremennye naukoemkie tekhnologii [Modern High-tech Technologies], 2014, no. 5–2, pp. 207–209.
Podinovsky V.V., Nogin V.D. Pareto-optimal'nye resheniya mnogokriterial'nyh zadach [Pareto-optimal solutions of multicriteria problems]. Moscow, Nauka Publ., 1982, 256 p.
Luzon Y., Pinchover R., Khmelnitsky E. Dynamic budget allocation for social media advertising campaigns: optimization and learning. European Journal of Operational Research, 2022, vol. 299, iss. 1, pp. 223–234.
Panteleev A.V. Bortakovsky A.S., Letova T.A. Optimal'noe upravlenie v primerah i zadachah [Optimal control in examples and tasks]. Moscow, MAI Publ., 1996, 212 p.
Micchi G., Khah S.S., Turner J. A new optimization layer for real-time bidding advertising campaigns. Intelligent Data Analysis, 2020, vol. 24, iss. 1, pp. 199–224.
Han J., Moraga C. The influence of the sigmoid function parameters on the speed of backpropagation learning. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1995, vol. 930, pp. 195–201.


Чибисова А.В., Шинаков Д.С. Математическое моделирование рекламной кампании. Математическое моделирование и численные методы, 2022, № 3, с. 84–97.



Download article

Количество скачиваний: 193