Chat Bot Powered Customer Engagement System
| dc.contributor.author | Atidu Ainebyoona | |
| dc.date.accessioned | 2025-11-03T06:45:09Z | |
| dc.date.available | 2025-11-03T06:45:09Z | |
| dc.date.issued | 2025-10-10 | |
| dc.description.abstract | The rapid growth of artificial intelligence (AI) has transformed how businesses interact with their customers. However, in many developing regions like Kabale Municipality in Uganda, traditional customer service methods still dominate. This study aimed to design and evaluate a Chat Bot Powered Customer Engagement System tailored to the needs of local businesses. The main objective was to improve customer satisfaction, automate sales processes, and enhance operational efficiency using AI technologies such as chatbots, natural language processing (NLP), and predictive analytics. A mixed-method research approach was used, combining quantitative data from 235 distributed questionnaires (179 returned) and qualitative insights from interviews and observations. The study revealed that existing customer engagement strategies are slow, generic, and prone to miscommunication. Most respondents agreed that AI systems could offer faster response times, better personalization, and improved service quality. A prototype AI system was developed and tested in selected businesses. Regression analysis showed that AI adoption accounted for 64% of improvements in business performance, confirming its effectiveness. Despite challenges such as limited technical knowledge, infrastructure gaps, and fear of job loss, the overall response to AI was positive. Interviewees expressed interest in using AI, especially if the system supports local languages and complements human staff. The study concludes that AI-powered engagement systems can greatly benefit businesses in Kabale if implemented thoughtfully. It recommends hybrid AI-human models, localized system customization, and ongoing training to ensure effective adoption and long-term impact. Keywords: Artificial Intelligence, Customer Engagement, Chatbots, Predictive Analytics, Uganda, Business Efficiency, NLP, Kabale Municipality | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12311/3047 | |
| dc.language.iso | en | |
| dc.publisher | Uganda Christian University | |
| dc.title | Chat Bot Powered Customer Engagement System | |
| dc.type | Thesis |