Using AI for Effective Customer Experience Management : A Case Study of Vitec Roidu Oy
Kiryavaynen, Elena (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2025121034731
https://urn.fi/URN:NBN:fi:amk-2025121034731
Tiivistelmä
This thesis examines the growing role of Artificial Intelligence (AI) in organizational operations, improving the efficiency of data analysis and developing production processes at Vitec Roidu Oy (Roidu), a company specializing in customer feedback.
In the modern economy, the ability to collect and process large volumes of data has become a critical factor in strategic decision-making. Data analytics, particularly sentiment analysis, plays a key role in transforming practical outcomes that address various challenges, such as cultural differences and linguistic ambiguity, where AI models are capable of identifying context and emotions. Addressing these challenges is crucial for companies looking to improve customer service, increase brand loyalty and make strategically effective decisions.
The study aims to investigate how to expand the capabilities of AI in the work of an analyst, increase the potential for data development, enhance confidence in analytical data obtained through AI and provide new opportunities for effective data collection. Knowledge management is important.
The study case consists of a quality analysis at Roidu, including semi-structured interviews with employees engaged in AI development and data analytics. The research includes current situations, challenges, limitations and potential improvements. Furthermore, it reviews examples from other companies successfully using AI in analytics and shows possible adaptation options for the Roidu company.
The goal is to understand how AI can increase data mining potential, empower analysts, improve the reliability of analytical results and explore new opportunities for effective data collection.
In the modern economy, the ability to collect and process large volumes of data has become a critical factor in strategic decision-making. Data analytics, particularly sentiment analysis, plays a key role in transforming practical outcomes that address various challenges, such as cultural differences and linguistic ambiguity, where AI models are capable of identifying context and emotions. Addressing these challenges is crucial for companies looking to improve customer service, increase brand loyalty and make strategically effective decisions.
The study aims to investigate how to expand the capabilities of AI in the work of an analyst, increase the potential for data development, enhance confidence in analytical data obtained through AI and provide new opportunities for effective data collection. Knowledge management is important.
The study case consists of a quality analysis at Roidu, including semi-structured interviews with employees engaged in AI development and data analytics. The research includes current situations, challenges, limitations and potential improvements. Furthermore, it reviews examples from other companies successfully using AI in analytics and shows possible adaptation options for the Roidu company.
The goal is to understand how AI can increase data mining potential, empower analysts, improve the reliability of analytical results and explore new opportunities for effective data collection.