Advances in Consumer Research
Issue 3 : 147-153
Original Article
AI-Powered Consumer Analytics: Enhancing Marketing and Financial Decision-Making
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1
Designation: Associate Professor in Chemistry, Department: Applied Sciences, Institute: Institute of Engineering & Technology, Devi Ahilya University, District: Indore, City: Indore, State: MP
2
Designation: Assistant Professor, Department: Commerce and Management, Institute: Dayanand Sagar Business Academy District: Bangalore, City: Bangalore, State: Karnataka
3
Designation: Associate professor, Department: Department of Management studies, Institute: VFSTR Deemed to be university, District: Guntur, City: vadlamudi ( village), State: Andhra Pradesh
4
Designation: Associate Professor, Department: Centre for Management Studies, Institute: Gitarattan International Business School, District: New Delhi, City: Delhi, State: Delhi
5
Designation: Principal, Department:, Institute: SAVPM's Sancheti College of Arts, Commerce & Science, District: Pune City: Pune, State: Maharashtra
Abstract

The way that AI powers consumer analytics is transforming marketing and financial decisions for businesses, allowing them to provide personalization to their customers, predict behaviors, and allocate resources more efficiently. The objective of this study is to examine the application of artificial intelligence on consumer analytics and the markets in which artificial intelligence has caused impact especially in the fields of marketing and finance. The study also performs a survey of 350 such professionals across industries in order to understand how AI driven tools are helping in better customer segmentation, improving predictive modeling and serving personalised recommendations. AI analytics helps to achieve better marketing campaigns, higher levels of customer retention and better financial decision making, in particular, they are helpful where credit risk assessment and investment strategies are concerned. Despite that, there remain challenges around data privacy, algorithmic bias, and a lack of transparency in AI models. The study also suggests that XAI frameworks should be incorporated to minimize ethical issues, and both XAI and ethical issues would ensure seamless system integration for all AI consumer analytics potentials to be maximized. Further research is needed to determine the long term impacts of AI adoption on consumer trust, regulatory compliance as well as cross cultural differences in the usage of AI...

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Volume 2, Issue 3
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