Data metrics in modern digital marketing

The article defines the stages of digital marketing and highlights modern metrics for choosing data analysis tools. Currently, mobile Internet accounts for 80% of the total Internet traffic in the Russian Federation. The research emphasises the components of effective media planning, including return on investments, target audience, increasing brand awareness, and costs optimising. According to the statistics, there are different approaches to increasing sales of new trademarks (brands) via the mobile Internet. The research considers the issues of calculating the market share of a trading company, advertising voice among the voices of other brands, and calculating the advertising budget for promoted similar budgets of other companies. The paper proves the validity of the formula expressing the equilibrium in a market with several players. The social networks, messengers, digital television, and neural networks replace the traditional advertising channels. It provides the reduction of brand forgetting time. Moreover, the traditional advertising impact on the target audience is losing its effectiveness. The considered mathematical model of the advertising response redistribution shows the inverse dependence of the share of the advertising voice depending on the number of the promoted product in the company's product line. Other data metrics allow ones to increase sales profits in addition to the main advertising strategy of the enterprise through geographic information systems (coverage radius), customer comments, and reviews on marketplaces and digital cinemas. The use of big data technologies transforms the methodology of effective advertising. It applies the econometric laws providing a "target funnel" for product promotion and Nevertheless, it requires large budgets to maintain the promoted brands. Therefore, the marketing services of enterprises investigate market segmentation and assess the advertising budgets of competitors. It maximises the effectiveness of an advertising campaign following the entry of competing companies into the same market. Hence, the share of the regional or global market of the promoted product is proportional to the advertising budget relative to the total budget of the entire market. The funding for the promotion of a new brand for well-known purposes is an analytical dependence of Peckham. The individual share of the advertising vote (out of 100% of votes for new brands) analytically depends on the company's historical market share and the number of the new brand for the reporting period (1, 2, 3, etc. years). The individual share of the advertising voice is a dimensionless random variable depending on the relative frequency of the brand over the previous period. The integral calculus in advertising forecasting provides marketers with a powerful tool for analysing data and making informed decisions. Such models include the Bass and the Adstock models. Probability metrics are important tools for assessment of advertising campaigns effectiveness and making strategic decisions. They allow ones to consider the uncertainties and randomness characteristic of consumer behavior. Moreover, the game theory is a powerful tool for analysing and developing advertising strategies. It allows companies to consider the behavior of competitors, respond to changes in the market environment, and make informed decisions. The use of game theory helps to minimise risks and maximise the benefits of advertising campaigns, ensuring sustainable business development.