Tools for Optimizing the Budget of an Advertising Campaign in Digital Marketing
Tools for Optimizing the Budget of an Advertising Campaign in Digital Marketing
Anastasiia D. Shvets,I. Pyvavar,Tetiana Silichova
TLDR
The key findings of the study confirmed that targeting, content relevance, and ad frequency significantly affect consumer response and offers practical recommendations for businesses aimed at maximizing the return on investment in digital advertising.
Abstract
Advertising plays a pivotal role in shaping consumer behavior and driving economic growth. The study focuses on the impact of online advertising, including its personalized nature and ability to reach specific target audiences. The aim of the study is to analyze the factors that affect the efficiency of advertising, develop models for managing advertising campaigns and predicting potential results. The objective of the study is to analyze the factors that affect the efficiency of online advertising campaigns, to develop tools for predicting the results of advertising campaigns in order to determine the optimal marketing management strategies in the digital environment. The article uses various quantitative methods, including logistic regression and simulation modeling. As a result of the analysis of various tools, logistic regression with an adaptive gradient was recognized as the best, with the help of which the indicator for evaluating the efficiency of advertising – CTR (Click-Through Rate) was calculated. Based on the results of the built logistics model, a set of significant characteristics has been formed that have the greatest impact on the CTR indicator. It is determined that the most significant and efficient on the Internet will be banner advertising, which has its advantages: wide audience coverage, increased brand awareness, instant response. In addition to static assessment of advertising efficiency, the study builds a simulation model, on the basis of which the efficiency of investments under certain conditions and the cost of advertising is studied. A series of experiments with the model was carried out in order to search for the values of the parameters under which the best result of modeling the system is achieved, also to study the behavior of the model under given conditions. The key findings of the study confirmed that targeting, content relevance, and ad frequency significantly affect consumer response. The study also offers practical recommendations for businesses aimed at maximizing the return on investment in digital advertising.
