DEVELOPMENT OF A METHODOLOGY FOR COMPREHENSIVE MARKETING ANALYSIS AND PREDICTIVE RISK ASSESSMENT OF EDTECH STARTUPS IN THE DIGITAL ENVIRONMENT

  • D.V. Barankov Synergy University, Moscow, Russia
  • A.Yu. Anisimov Synergy University, Moscow, Russia
DOI: https://doi.org/10.34680/BENEFICIUM.2026.3(60).46-57

Abstract

The educational technology market increases startups' sensitivity to user acquisition costs, retention, dependence on digital platforms, personal data regulation, and changing demand. The research problem is the insufficient development of an applied method that links comprehensive marketing analysis with early detection of market, technological, and regulatory risks of EdTech startups. The purpose of the study is to develop a comprehensive marketing analysis method and, on this basis, build a predictive model for assessing and early detecting these risks in the digital environment, taking into account differences between the Russian, U.S., and European markets. The hypothesis is that the joint use of marketing, product, technological, and legal indicators within a single calculation procedure makes it possible to identify declining startup sustainability before it appears in financial results. The method combines PESTLE analysis, SWOT analysis, indicator normalization on a 1-5 scale, calculation of market, technological, and regulatory risk blocks, an integral risk index, the probability of significant risk, and a managerial response class. Empirical testing covers seven digital education companies: Skillbox, Skyeng, Uchi.ru / Tetrika, Yandex Practicum, Coursera, Udemy, and GoStudent. Direct scale and dynamics indicators are taken from open Smart Ranking and Skillbox Media data, public financial releases by Coursera and Udemy, and GoStudent disclosures. Non-disclosed marketing indicators are used as normalized proxy variables rather than reported company data. The results show that high risk is most often formed by costly user acquisition, weak retention, a narrow monetization model, and increased data requirements. The practical value of the model lies in early selection of managerial actions.

Keywords: comprehensive marketing analysis, machine learning, predictive analytics, risks, digital educational platform, digital environment, EdTech-startups

Funding: the research had no sponsorship (own resources).

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About the Authors

Dmitry V. Barankov – Graduate Student, Synergy University, Moscow, Russia. E-mail: Ychitel200291@mail.ru. SPIN RINTS 4325-6318. ORCID 0000-0001-8317-2577.

Alexander Yu. Anisimov – Cand. Sci. (Economics), Docent; Associate Professor, Synergy University, Moscow, Russia. E-mail: anisimov_au@mail.ru. SPIN RINTS 9732-9601. ORCID 0000-0002-8113-4523. ResearcherID Q-3824-2017. Scopus Author ID 57194047333.

For citation: Barankov D.V., Anisimov A.Yu. Development of a Methodology for Comprehensive Marketing Analysis and Predictive Risk Assessment of EdTech Startups in the Digital Environment // BENEFICIUM. 2026. Vol. 3(60). Pp. 46-57. (In Russ.). DOI: 10.34680/BENEFICIUM.2026.3(60).46-57

Published
2026-09-06
Issue
No 3 (2026)
Section
PLATFORM SOLUTIONS AND AI TECHNOLOGIES IN MODERN INDUSTRY MANAGEMENT