• Dr. Lukman Patel

Entrepreneurial businesses are facing new and unparalleled challenges when it comes to acquiring and retaining customers, as the acquisition cost has already increased by 40 percent since 2023, and traditional retention models do not seem to be effective enough any longer. This paper examines how artificial intelligence technologies can be used to transform customer relationship management in the entrepreneurial context with the help of predictive analytics, machine-learning algorithms, or personalization engines. Based on a mixed-methodology that includes quantitative research of 250 startups and qualitative research of successful AI implementations, the results show that AI-based acquisition strategies achieve rates of conversion 35 per cent greater and place the implementation at 28 per cent lower cost. Also, AI-based retention programmes show 45 per cent increase in customer lifetime value and 32 per cent decrease in churn. The study suggests an in-depth application framework to be used by entrepreneurs that would cope with technical, financial, and organisational issues and provide real-life guidelines to adopt AI. The findings highlight that effective implementation of AI requires a strategic alignment, sound data infrastructure, as well as human-AI interaction as opposed to complete automation. The results are relevant to the literature on entrepreneurship because they prove AI to be an essential facilitator of sustainable development of resource-limited businesses.

AI, customer acquisition, customer retention, entrepreneurship, machine learning, predictive analytics, personalization

"AI-ENABLED CUSTOMER ACQUISITION AND RETENTION IN ENTREPRENEURIAL VENTURES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.j671-j697, March-2025, Available :http://www.jetir.org/papers/JETIR2503985.pdf

"AI-ENABLED CUSTOMER ACQUISITION AND RETENTION IN ENTREPRENEURIAL VENTURES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppj671-j697, March-2025, Available at : http://www.jetir.org/papers/JETIR2503985.pdf