Features of Applying Statistical Analysis in Modern Marketing

Abstract

The article discusses the features of applying statistical analysis in marketing during digital transformation. After explaining the relevance of the study, the authors formulate the challenges of using statistical analysis in marketing, reveal the study goals, objectives, and tools, and provide an overview of the content of statistical analysis (at the company level). In modern Internet marketing, a large number of statistical indicators are used, such as CPC (cost per click), CTR (advertisement click-through rate), CPA (advertising cost), conversion rate, lead cost, and many others. However, according to the authors, the indicators used in most companies are not comprehensive enough. The paper notes that statistical analysis of the digital marketing domain uses several digital products, such as Google Analytics, Adobe Analytics, Mixpanel, Salesforce Analytics Cloud, and Looker. The more specific the information required for statistical analysis, the more the company strives to create its digital product for collecting, analyzing, and interpreting the most important data for marketing about hidden patterns in customer behavior, in their consumer journey, motives, and incentives for their choice. The uniqueness of the artificial intelligence algorithms used for this is ensured by the methods of classification, clustering, regression, and association analysis that are used in machine learning and statistical analysis for the automatic processing and analysis of large amounts of data. The article focuses on the specific results of improving marketing activities based on the development of statistical analysis amidst digital transformation arising from the introduction of digital technologies, and the development of digital products that ultimately give competitive advantages in a particular area of business.