FORMATION OF AN ADAPTIVE INTERNET MARKETING STRATEGY OF AN ENTERPRISE BASED ON DATA ANALYTICS

Abstract

The purpose of the article is to develop practical principles for building an adaptive internet marketing strategy for an enterprise focused on rapid response to changes in digital demand, fluctuations in the cost of advertising resources, and shifts in consumer behavior. The study concentrates on combining data analytics, flexible budgeting, personalized communications, and automated adjustment of marketing decisions. The methodology of the research is formed as a combination of applied analytical approaches. Comparative analysis was used to evaluate promotion channels by customer acquisition cost, conversion rate, and return on expenditures. The economic and statistical approach was applied to assess traffic structure, behavioral characteristics of the audience, and the effectiveness of advertising activities. The segmentation method was used to classify the customer base according to behavioral and transactional features. Scenario modeling made it possible to develop options for оперативe budget reallocation depending on changes in demand. The obtained results showed that the highest efficiency is generated not by channels with maximum reach, but by tools with higher traffic quality and more stable conversion rates. It was established that repeated communications with already acquired customers provide lower sales costs and higher return on expenditures. Critical points of user loss were identified at the stages of moving to the cart and completing the order, where technical and organizational barriers reduce the final result. A scenario budgeting model was proposed, which provides for rapid transfer of resources to directions with better economic return. The feasibility of using predictive segmentation for personalizing advertising messages and increasing purchase probability was substantiated. The practical significance of the results lies in the possibility of implementing a system of daily adaptive management of enterprise internet marketing without excessive budget growth. The originality of the study lies in combining three managerial blocks, namely diagnostics of customers’ digital behavior, scenario-based resource reallocation, and automatic adjustment of advertising campaigns in real time.