Exponential technological expansion creates opportunities for competitive advantage by applying new data-oriented approaches to digital marketing practices. Machine learning (ML) can predict future developments and support decision-making by extracting insights from large amounts of generated data. This functionality greatly impacts and streamlines the strategic decision-making process of organizations. The research gap analysis revealed that a little is known about marketers' attitude toward, and knowledge about, ML tools and their adoption and utilization to support strategic and operational management. The research presented here focuses on the selection and adoption of the ML-driven analytical tools by three distinct groups: marketing agencies, media companies, and advertisers. Qualitative and quantitative research was conducted on a sample of these organizations operating in Slovakia. The findings highlight: 1) the important role of intelligent analytical tools in the creation and deployment of marketing strategies; 2) the lack of knowledge about emerging technologies, such as ML and artificial intelligence (AI); 3) the potential application of the ML tools in marketing, and; 4) the low level of adoption and utilization of the ML-driven analytical tools in marketing management. A framework consisting of enablers and a process map was developed to help organizations identify the opportunities and successfully execute projects that are oriented toward the deployment and adoption of the analytical ML tools in digital marketing.INDEX TERMS Big data, data-driven analytical tools, digital marketing, machine learning (ML), marketing agencies, marketing analysis.

Digitalization, virtualization and transformation of everyday activities into the digital environment amplified by the globalized barrier-free world has led to the evolvement and enhancement of products and services. Media publishers have been forced to transform their traditional publication processes, with the content being published not only in print but also on their websites. Consumers of content were used to paying for printed versions, however, they are often not used to-and more importantly-not willing to pay for content consumed on the internet. Thus, the only monetization model for online content is dependent on displaying advertisements in their various forms. Digitalization and technologically advanced processes allow for the tracking of user behavior, for the development and mining of user information, and for the utilization of the data for enhancing user experience on websites. Even if the publisher is not able to create this data by himself, it is possible to obtain it from a third-party company. However, the mined data often also contains some form of personal information about users, leading to the need for change in the current concept of privacy. Displaying advertisements efficiently using this data offers an acceptable monetization model for content publishers on the one hand and an enhanced user experience for consumers thanks to better targeting on the other. Media publishers employ various approaches in terms of banner advertisements, with some of them disrupting consumers of the content and invading their privacy. Users have developed banner blindness and are protecting themselves by utilizing ad-blocking software solutions. These create great obstacles for displaying banner advertisements and thus, negatively affect revenue streams of content publishers.

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The viewers' response to television advertising has changed dramatically over the past years. Search visibility of advertisers has become of paramount importance to ensure that communication messages are followed up appropriately, and that the specific brand is considered in the customer decision-making process. This paper examines the effectiveness of communication campaigns that include TV advertisements. Specifically, it determines if, and to what extent, the advertisers of selected Australian TV advertising campaigns are visible in full-text searches on Google for a variety of relevant keywords. The visibility of advertisers is measured as the number of keyword searches that result in a high ranking on the search engine results page, average ranking, and site visibility. The results revealed notable differences in the visibility of advertisers in searches. Enhancing their visibility represents a challenge for companies striving to optimise the delivery of their communication message(s) across the entire spectrum of traditional and online media.

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