Внедрение решений искусственного интеллекта в торговой компании для привлечения клиентов – покупателей фармацевтической продукции (Implementation of artificial intelligence solutions in a trade company to attract customers – buyers of pharmaceutical products)
Аннотация
In today's competitive marketplace, trade companies, particularly those operating in the pharmaceutical sector, face the challenge of attracting and retaining customers. The utilization of AI technologies has gained significant attention as a means to enhance customer engagement and improve business outcomes. This thesis explores the relevance of implementing AI solutions in a trade company to address these challenges and capitalize on emerging opportunities.
The purpose of this master's thesis is to investigate the potential and to propose the strategy of AI solutions implementation in a trade company's operations to attract customers who purchase pharmaceutical products.
The object of the study is the information technologies in the trading activity.
The subject of the study is the strategy of effective implementation of AI solutions aimed at attracting customers of pharmaceutical products.
The research focuses on understanding how AI can optimize various aspects of the company's operations to enhance customer engagement and improve overall business performance.
The objectives of the study include identifying the most effective AI applications, analyzing their impact on customer behavior and satisfaction, and proposing a strategy and a plan for its successful implementation in practice.
This thesis contributes to the existing body of knowledge by examining the specific application of AI solutions in the context of attracting customers who purchase pharmaceutical products. It explores novel approaches and strategies to leverage AI technologies, such as machine learning, natural language processing, and personalized recommendations, to create innovative customer experiences and gain a competitive edge in the market.
The findings of this research have practical implications for trade companies operating in the pharmaceutical sector. By implementing AI solutions, companies can enhance customer engagement, improve the accuracy of demand forecasting, optimize inventory management, and provide personalized product recommendations. These outcomes have the potential to drive customer satisfaction, increase sales, and establish long-term customer loyalty.
The proposed strategy and corresponding measures aim to improve the economic efficiency of the trade company in several areas, including customer acquisition, retention, and sales growth. By leveraging AI solutions, the company can optimize marketing campaigns, reduce operational costs, and gain a competitive advantage. The research assesses the potential economic benefits and provides recommendations for effective implementation to ensure the economic efficiency of the proposed measures.
In summary, this master's thesis explores the implementation of AI solutions in a trade company to attract customers who purchase pharmaceutical products. It highlights the relevance, purpose, objectives, object, subject, scientific novelty, practical significance, and economic efficiency of the research, providing insights and recommendations for successful implementation in the pharmaceutical trade industry.
The purpose of this master's thesis is to investigate the potential and to propose the strategy of AI solutions implementation in a trade company's operations to attract customers who purchase pharmaceutical products.
The object of the study is the information technologies in the trading activity.
The subject of the study is the strategy of effective implementation of AI solutions aimed at attracting customers of pharmaceutical products.
The research focuses on understanding how AI can optimize various aspects of the company's operations to enhance customer engagement and improve overall business performance.
The objectives of the study include identifying the most effective AI applications, analyzing their impact on customer behavior and satisfaction, and proposing a strategy and a plan for its successful implementation in practice.
This thesis contributes to the existing body of knowledge by examining the specific application of AI solutions in the context of attracting customers who purchase pharmaceutical products. It explores novel approaches and strategies to leverage AI technologies, such as machine learning, natural language processing, and personalized recommendations, to create innovative customer experiences and gain a competitive edge in the market.
The findings of this research have practical implications for trade companies operating in the pharmaceutical sector. By implementing AI solutions, companies can enhance customer engagement, improve the accuracy of demand forecasting, optimize inventory management, and provide personalized product recommendations. These outcomes have the potential to drive customer satisfaction, increase sales, and establish long-term customer loyalty.
The proposed strategy and corresponding measures aim to improve the economic efficiency of the trade company in several areas, including customer acquisition, retention, and sales growth. By leveraging AI solutions, the company can optimize marketing campaigns, reduce operational costs, and gain a competitive advantage. The research assesses the potential economic benefits and provides recommendations for effective implementation to ensure the economic efficiency of the proposed measures.
In summary, this master's thesis explores the implementation of AI solutions in a trade company to attract customers who purchase pharmaceutical products. It highlights the relevance, purpose, objectives, object, subject, scientific novelty, practical significance, and economic efficiency of the research, providing insights and recommendations for successful implementation in the pharmaceutical trade industry.