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Рік заснування видання - 2011

APPLICATION OF ARTIFICIAL INTELLIGENCE IN MARKETING

15.02.2024 17:19

[1. Information systems and technologies]

Author: Dmytro Saus-Kachanov, undergraduate student, Department of information and measurement technologies, National Technical University of Ukraine "Ihor Sikorsky Kyiv Polytechnic Institute", Kyiv


Marketing is an essential part of any company’s business management and artificial intelligence has vast potential in marketing. AI adjusts the way of interaction between brands and users with each other. Hence, now marketers can focus more on the customer's needs, dependent on data previously collected, and target buying groups using personalised advertisements. As a result, companies can make better strategic decisions, set clear goals for the future, and allocate advertising budgets more accurately. All this makes shoppers feel more inclined to buy what is offered and makes their shopping experience more enjoyable. Machine Learning (ML) is a subset of AI, and it helps to analyse competitors, understand customers, identify emerging microtrends and predict own growth patterns. Moreover, ML interpret data without being directly programmed and improvement accuracy relies on the amount of data fed into the algorithm [1,3].

Many businesses of all sizes hinge on AI marketing tools to promote their brands, improve impacts and communicate better with customers. Networks are oftentimes a part of business plans, regardless of whether you are an individual or an organization, and they can take a company's marketing strategy to the next level. A multitude of AI types are finding their place in marketing strategies, such as:

a) Natural language processing (NLP): helps in analysing a huge number of product reviews, Tweets, Instagram and Facebook posts, e-mails between company and consumers, etc. [3]

b) Image recognition: helps to understand pictures, shared photos of daily life by consumers or, for example, advertisements by celebrities (in this case AI defines the person and the product). It can be used in security measures – cameras on markets, parking and warehouses. What is more, some companies use this technology to make portfolios of customers, which can contain such information as age category, gender, days and frequency of visiting, bought products and even emotions. All this data can be analysed to improve income and customer experiences [3].

c) Problem-solving and reasoning: AI in most cases used to get one exact purpose. Thus, before deploying a model, advertisers must identify one narrow problem to solve to gain a better ability to predict future events. An example is segmenting a company’s market based on varying psycho-graphics of their customers, in order to determine the most interested in product customers and what advantages they perceive in the product compared to its competitors. Personality profiles depict an individual in terms of the Big Five personality traits Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Al-based profiles then can inform future marketing decisions [1,3].

d) Machine learning: by detecting patterns in the data, AI systems can help consumers to choose options, which best fit their needs, even optimally than humans can. Moreover, a database of AI system can be scaled and this enables learning from “previous experience”. The more unstructured data is produced, the more can be used for learning, which leads to improving AI system performance. ML also can help predict customer lifetime value and conversion likelihood. Using personality analysis and sentiment analysis AI gleans information from unstructured data, and then produces content in the following way [2,3]:

– natural language generation (NLG): artificial intelligence can create automated emails by leveraging customer search history data. It also suggests which content will be most effective in creating emails. The subject line is one of the most important parts of writing an email, and it is difficult to generate the exact name that will attract the attention of the target audience or individual. In this case, artificial intelligence comes to the rescue, which is able to optimize the subject line as much as possible and encourage the audience to read the email. AI is also useful in determining the frequency and time of sending emails and even can help in making content for them [2,3].

– image generation: generating pictures and animated movies based on text descriptions. It provides an opportunity to get the required image quickly and cheaply [3]. 

– speech generation: providing meaningful voiceovers for advertisements. Also used for translating videos into different languages and in conjunction with image generation you can even make some videos, without leaving the computer [3].

– audience segmentation: AI helps efficiently divide up consumers by various factors, such as location, area of work, salary and behaviours, leading to better targeting and, as a result, more effective marketing campaigns [4].

– customer service chatbots: have great importance in marketing, because they respond promptly to requests and provide 24/7 support. Collected from them data can be used for further analysis of customer behaviour. Also, chatbots increase a company's sales by offering personalized shopping advice based on the customer's search history and past purchases [1,2,4].

– programmatic advertising: when a user searches for a product or service online, AI instantly remembers what he needs and offers similar things on other different platforms. In this way, customers become the target audience for brands and companies that offer services or products that he interested in. This helps companies show the most relevant ads to their target audience at the right time [1,4]. 

– search engine optimization (SEO): These AI tools suggest what type of content you should write to increase search traffic and rank better in search engines for specific keywords, and also ensure that your business appears accurately in search across multiple geographic regions [4].

– E-commerce: AI is helping to improve digital marketing capabilities and e-commerce programs by giving them a more nuanced understanding of customer’s needs and buying habits [4].      

Benefits [1,4]:

Faster, smarter decision-making: AI systems help in creating strategies and analysing data, based on which can recommend better actions. What is more, ML enables computers to learn automatically.

Improved return on investment (ROI) on marketing initiatives: AI tools can help marketers pinpoint executable insights from data, find the right investment in advertising channels and maximise ad effectiveness through behavioural targeting.

More accurate measurement of KPIs: the volume of data from digital campaigns is more than humans can keep up with, making it challenging to judge marketing effectiveness. AI-powered dashboards come to the rescue, enabling marketers to connect their success to specific actions and define what works best.

Enhanced customer relationship management (CRM) capabilities: AI technologies can be used to automate routine tasks, which helps in improving CRM programs by automating routine tasks. Hence, it reduces human interaction, eliminating the possibility of human error.

More meaningful insights from customer data: AI speeds up data processing and implementing predictive analytics, ensures accuracy and security, and allows the marketing team to focus on strategic goals.

Challenges [4]:

Training AI solutions: systems require significant training to deal with a new task, using a large amount of well-organised data, scientists who specialize in this kind of training and time. 

Ensuring the quality and accuracy of data: AI solutions are strong only if the quality of the data is accurate and representative. In another case, the decisions generated by AI will produce unreliable results.

Complying with privacy laws: loose use of personal data could have negative consequences for AI marketers. Companies face hefty fines and reputational damage when they misuse personal information.

Artificial intelligence is a very important technology for marketing today, and companies are making significant investments in it. ML and deep learning are two of the most well-known AI techniques. There are a variety of different systems used for collecting data, analysing it and giving feedback. AI can assist marketers by creating personalised brand experiences, making cultivating users' engagement, based on their behaviour and overall trends. AI makes possible personalising content, data collection, and analysis. Of course, most processes are now automated and data is processed much faster, but there are several drawbacks as well, hence people still need to control all these processes. Artificial intelligence helps people, but not replaces them.

References

1. Artificial intelligence (AI) applications for marketing: A literature-based study. / Abid Haleem and others. 2022, URL: https://www.sciencedirect.com/science/article/pii/S2666603022000136

2. Artificial intelligence (AI) in marketing. Group 107: webpage. URL: https://careers.group107.com/uk/blog/shtuchnij-intelekt-shi-v-marketingu/

3. Artificial Intelligence in Advertising: How Marketers Can Leverage Artificial Intelligence Along the Consumer Journey/ Jan Kietzmann, Jeannette Paschen, Emily Rae Treen. 2018, URL:  https://www.researchgate.net/publication/327500836_Artificial_Intelligence_in_Advertising_How_Marketers_Can_Leverage_Artificial_Intelligence_Along_the_Consumer_Journey

4. AI in marketing: How to leverage this powerful new technology for your next campaign. IBM: webpage. URL: https://www.ibm.com/blog/ai-in-marketing/



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