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Methodological foundations for the development of fi nancial models for monetization of startups

https://doi.org/10.29030/2309-2076-2023-16-2-63-75

Abstract

At the idea stage, any startup thinks about how it will earn, who the client is and what he will pay the startup for. The speed of the project development directly depends on how fast the startup starts earning. From the moment of the business idea, it is necessary to choose a suitable financial and economic model. There are more than 50 startup monetization models on the market, each model has its pros and cons, and when choosing it, it is necessary to take into account industry specifics. The monetization model needs to be tested as early as possible, each product has its own cost, if the product is free, then monetization is at the expense of something else.

In this article, the author has compiled a step-by-step plan for choosing the most stable financial model depending on the type of product and calculation indicators (using the example of e-commerce at the startup stage, entering a new market), and also considers the classical model of small business development based on digital solutions to attract customers.

From the point of view of practical significance, this article can be used in business acceleration programs of student startups, as well as the transfer of existing business to the online format. Small businesses can use the proposed tools for analyzing the company's activities and profit management.

About the Author

N. A. Shuvalova
Peoples' Friendship University of Russia
Russian Federation

Nataliya A. Shuvalova – Ph.D. in economic sciences, assistant

Moscow



References

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3. Zhigurina O. Five working schemes for monetization of startups. URL: https://vc.ru/flood/1325-pyat-rabochih-shem-monetizatsii-startapov. (In Russ.).

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Review

For citations:


Shuvalova N.A. Methodological foundations for the development of fi nancial models for monetization of startups. Economic Systems. 2023;16(2):63-75. (In Russ.) https://doi.org/10.29030/2309-2076-2023-16-2-63-75

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ISSN 2309-2076 (Print)