Digital marketing is the measure of attracting and retaining an audience through digital technology. Usually, its implementation is carried out with the help of mobile, television, and radio technologies. The central work area uses the Internet as the dominant communication mediator. Marketing operations are a vast branch of business that constantly requires upgrading current and the creation of new protocols for disseminating information about a company’s product. Artificial Intelligence (AI) is an effective tool to improve marketing, increase sales of current and new products, and retain customers.
AI is an operational tool that optimizes digital practices and promotes competitive advantage. The integration of AI is realized by analyzing open user data (product category preferences or purchase frequency) and advertising agents (Dumitriua & Popescua, 2020). It is most prevalent in analytics (Rabby, Chimhundu & Hassan, 2021). The ability to predict market dynamics can be helpful for marketing teams. AI can be used to predict trends among consumers, their buying behavior, and seasonal preferences (Murgai, 2018). It will tailor campaigns accordingly, ensuring they maximize reach and effectiveness. Predictive analytics can increase return on investment (ROI) and track productivity within teams.
Advanced analysis of user data is provided through granular personalization – assessing broad insights into preferences and behavior. Understanding customer queries is critical to the success of marketing campaigns because it allows one to promote personalized service and service. Every consumer will be happy to receive a personalized offer on top of the standard one, thereby increasing their satisfaction with the company. For example, product browsing history indicates what attracts a customer; in this case, AI will recommend products in that category with a promotional offer. If a company supplies entertaining content (YouTube or TikTok), then the feed will suggest to the user those materials with which the user positively interacts. User requests are analyzed for ad integration, quantity, and negative response rates (Rabby et al., 2021). Finding the optimal price offer can be successful when analyzing a consumer’s interests, purchase history, and all interactions with the site.
Effective marketing includes providing feedback and responding to customer inquiries as quickly as possible. AI tools include chatbots and online assistants that respond to customer inquiries based on frequently asked questions or problems (Haleema, Javaidb, Qadric, Singh & Sumane, 2022). Chatbots respond to the most straightforward queries by matching them with knowledge-based articles and content based on clarifying questions. The performance of this technology can be further improved by using historical data and questions from previous consumers to create more personalized dialogues (Ribeiro & Reis, 2020). This helps reduce the wait time for a service response and allows operators to focus on more complex tasks.
Instant customer support is essential for retention, even if they have had a negative experience. Round-the-clock service will attract consumers from different time zones (countries), thereby increasing reach and retention. Support can be synthesized by AI already after the consumer’s issue has been resolved, for example, by automatically sending out additional offers or providing codes to buy goods with discounts (Haleema et al., 2022). It shows the customers that they are valued and ready to gain trust again.
Special programs for analyzing social media content have been created to identify general information trends. Social networks are currently the most selling channel for content marketing. Besides revealing the preferences of network users, marketers solve the problem of placement of advertising and creating groups of influence. The use of social networks is an important segment of digital marketing, which provides the previously listed benefits of AI. In particular, this is best seen in personalized offers and ads. Users will see contextual advertising for a product that hits their newsfeed and interacts with (De Mauro, Sestino & Bacconi, 2022). One way or another, the reach will increase significantly, and a sufficient percentage of the audience will want to purchase the product and establish a lasting relationship with the seller.
The competencies of the modern marketer include soft skills (emotional intelligence, creativity), the ability to analyze data from AI and build strategy and create informative content. Data analysis is done with the same IT tools: cross-sectional analysis, statistical calculations, and correlation between reach and sales. Marketers must be able to correlate results with predicted data to find the best business solutions that will increase the effectiveness of the marketing strategy (Ribeiro & Reis, 2020). AI is becoming a handy tool in content creation: neural networks calculate which images and videos evoke a positive response from users and suggest these ideas to the content creator (De Mauro et al., 2022). Collaboration between different departments optimizes integration in marketing and achieves positive dynamics in sales and reach.
Thus, it is established that the effectiveness of AI in digital marketing is determined by analytical tools, personalization of offers, and online support. The analytical capabilities of AI allow evaluation the behavior of the general user population, correlating this data with expectations and changing strategies. Personalization is an advanced analysis of a particular customer’s attitude toward a company or product, creating customized offers for him or her. Chatbots provide users with round-the-clock support on common and relatively simple issues, and managers can solve complex problems. The use of social media is one area of AI integration that allows contextual advertising to be customized and AI-based content to attract audiences.
References
De Mauro, A., Sestino, A., & Bacconi, A. (2022). Machine learning and artificial intelligence use in marketing: A general taxonomy. Italian Journal of Marketing. Web.
Dumitriua, D., & Popescua, M. A.-M. (2020). Artificial intelligence solutions for digital marketing. Procedia Manufacturing, 46, 630-636. Web.
Haleema, A., Javaidb, M., Qadric, M. A., Singh, R. P., & Sumane, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks, 3, 119-132. Web.
Murgai, A. (2018). Transforming digital marketing with artificial intelligence. International Journal of Latest Technology in Engineering, Management & Applied Science, 7(4), 259-262. Web.
Rabby, F., Chimhundu, R. & Hassan, R. (2021). Artificial intelligence in digital marketing influences consumer behaviour: A review and theoretical foundation for future research. Academy of Marketing Studies Journal, 25(5), 1-7. Web.
Ribeiro, T., & Reis, J. (2020). Artificial intelligence applied to digital marketing. In Kacprzyk, J. (Eds.) Trends and innovations in information systems and technologies, (vol.1160, pp.158-169). New York City, USA: Springer.