A system of indicators for evaluating the performance of e-commerce enterprises in the Russian market
Abstract
Abstract. As of mid-2026, the domestic e-commerce market has shifted its development paradigm. The extensive capture of audiences has given way to fierce competition for their retention. Because of this, traditional methods of financial analysis, which work successfully in classical offline retail, are rapidly losing their representativeness when auditing digital platforms. This dictates the relevance of a radical rethinking of management metrics. Meanwhile, a clear conceptual contradiction is observed today in scientific discourse and industry practice. In essence, the macroeconomic optimism of official statistics, reporting steady growth in trade turnover, sharply dissonates with the microeconomic reality. Many sellers are balancing on the brink of unprofitability. Their classical unit economics has proven defenseless against the rising cost of traffic and the volatility of commissions from large marketplaces. In this regard, the aim of this study is to develop and theoretically substantiate a system of indicators that comprehensively reflects the specifics of digital retail. In the course of the work, the author decomposed the architecture of an online business into four separate segments: financial, customer, operational, and technological. The proposed matrix integrates cohort analytics and predictive logistics parameters. The author's contribution is manifested in the synthesis of disparate functional indicators into a single dashboard. In addition, a new synthetic criterion has been introduced – the Infrastructure Independence Index (III). It is reasonable to assume that this marker helps to proactively identify the risks of an enterprise's mono-dependence on the algorithms of third-party platforms. As a result, a conclusion is made: the long-term viability of a trading platform today is determined not by the volumes of purchased inventory. It directly depends on the multiple excess of the customer lifetime value over the cost of their initial acquisition, the minimization of the return rate, and the degree of automation of routine warehousing processes.