The aim of the study is to map the segmentation expectations of the marketers and then draw a unified conclusion regarding the segmentation and targeting options in the advertising system of the most popular online platforms in Hungary. When and in what way did the advertising platform meet or fail to meet segmentation expectations. The question was when and how the advertising platform meets or fails to meet segmentation expectations. According to the secondary data, the most used social media platforms and advertising systems were determined. Then, in the Google search engine filtered research was started for all targeting options, which are listed in Table No. 1. with different keywords and search terms in English and Hungarian. The filtering included an annual time interval from the publication date of each platform. Last, the websites were reviewed in the hit list from which a conclusion could be drawn about the relationship between the platform and the targeting option available at a given time. The examination took place on 21st April, 2022. It can be stated that all systems have very different results and segmentation focus. Google's advertising uses a unique colour system with keywords that does not exist on other platforms, and outperformed competition from social media platforms Facebook and LinkedIn in the 2nd year after TikTok's launch. The researchers' goal was to inform practitioners and theorists first about the applicable methods and second about the expected changes based on the knowledge of this data. The protection of personal data, which is becoming increasingly important in advertising systems, as well as the growing awareness of consumers and the user-friendly attitude of some manufacturers (Apple- IOS) are together leading to a re-evaluation of the systems. Already, the management of individual customer data is being revised and replaced, and new, similar target groups are being created instead. The profile used by machine learning for tagging will remain, but the ability to identify individual consumers will be lost. More data upgrades are expected in the future, which could lead to changes in segmentation capabilities. The number of sources used in research is high, but gaps can occur even with a systematic review. Advertising systems create and manage segmentation and targeting options without an officially published document, so changes in the system can only be determined using secondary data. Further continuous systematic research is needed in order to identify the changes. This summary has been prepared by the researchers with the utmost care and summarizes the segmentation habits, knowledge and evolution over time of theoretical and practical marketing. This paper contributes to identify and study the segmentation practice in digital marketing.
As digital marketing becomes increasingly important in both communications and sales, the right strategy can make companies more efficient. One possible method is to use Artificial Intelligence to develop a company's website in line with the requirements of Marketing 5.0. This paper examines the relationship between Artificial Intelligence and Search Engine Optimization. The question is whether the website can rank better, communicate in better quality and generate higher purchase intent than a marketing expert, a sales expert or even a consumer, based on predefined parameters.
n Hungary, 94% of businesses have Internet access and 63% have a website. Moreover, online retail sales will reach HUF 1,203 billion in 2021. In order for companies to achieve the largest possible market share, they can use various digital marketing strategies. They are distinguished according to different methods. One of the most commonly used in practice and in science is inbound (as search engine optimization) and outbound (as advertising). Google Ads, which emerged at the turn of the millennium and defined itself as the world’s first company to use machine learning technology, is a market leader. Their ad system was initially based on keywords, which have since been expanded to include more than 4,800 types of targeting criteria. These targeting options are available for a variety of ad formats. The digital solutions to the billboards of traditional marketing are banner ads, called Display on Google. These ads contain image, video, and text content and aim to interrupt the consumer’s activity and redirect them to the advertiser’s website. Since they are capable of increasing website traffic by up to 300%, this can be interpreted as an opportunity that is also considered favorable by businesses. It is also suitable for testing various content elements, as one of its main indicators, the click-through rate, expresses the relevance of the ad, as several researchers have noted. As the role of artificial intelligence grows, more and more companies are using it as a competitive advantage. Some of their algorithms are capable of generating text, images, videos, or other content. In this study, I leverage the power of display ads and conduct my research in the Google Ads system instead of conducting consumer surveys. I created two ads for the same target audience, with the same budget and settings. The text content for one ad was created by a marketer, the image content was created by a professional photographer, and the content elements for the other ad were provided by Artificial Intelligence. The objective of the article is to study the performance, efficiency, and impact of artificial intelligence-generated content on conversions under real market conditions. The study also includes content created by the players.
Digital solutions in marketing can help reach niche markets. Marketers have the greatest opportunity ever to address segments whose needs have not yet been met. Online segmentation techniques allow to better know their characteristics. The aim of this article is to investigate the segmentation and targeting possibilities of the Google Ads system, which helps to explore consumer patterns more deeply. Digital marketing solutions help marketers reach niche markets to maximise the effectiveness of their activities. The goal of this social constructivist research was to find an answer to the question of whether the segmentation and targeting options of the Google Ads advertising system can sufficiently ensure this. To this end, we examined the presence of the “target market category” label in 37 individuals using a face-to-face survey method. The occurrence of the labels and the actual interests often overlapped.
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