Volume 02, Issue 05
Published on: May 2026
PERSUASIVE MARKETING INTELLIGENCE IN SUPERMARKET KIOSK AGENTS: EXTENDING AN INTELLIGENT RECEPTIONIST SYSTEM FOR CONTEXT-AWARE RECOMMENDATIONS
M. Harshini , R.R. Devapriya
D. Deepa
Artificial Intelligence and Data Science St.Joseph’s College Of Engineering Chennai, India
Article Status
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Peer Reviewed
Open Access
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Abstract
The number of customer contacts retail super- markets faces each day is massive, there are situations when customers inquire about the place and location of products, and active offers are promoted. Such restrictions may lead to poor navigation around the place, low consumer satisfac- tion and missed-sales opportunities. To address this gap, this paper proposes an AI-based conversational kiosk system that performs to comprehend the intentions of customers, and of- fering situationally-relevant advice, within the brick-and-mortar supermarket settings. The suggested system employs a locally developed conversational language model alongside the assistance of Ollama to process the queries of natural language without involving any external cloud-based solutions. The input of the customers is processed via Natural Language Processing (NLP) techniques and categorized under the action-oriented groups such as product location requests, offer requests or queries targeted at making recommendation. To increase sales intelligence, the system will include Apriori Association Rule Mining that will be used to identify the frequent patterns of products co-occurring in the structured information about the inventory. These asso- ciation guidelines allow the kiosk to make the suggestions of a complementary product of the product in real-time and in this sense can be considered as an upselling process in a controlled and transparent fashion. The architecture is implemented on the basis of two-part design (kiosk interface with customers and an administrative backup portal). The backend takes care of the updating of inventory, promotional offers, and layouts and maps with stores in order to maintain the responses of AI relatively close in accordance to the real-time store data. Such a separation will make sure that there is no hindrance in the decision-making process and operational visibility of staff members in supermarket is fulfilled. The practical application demonstrates that the combination of the conversational artificial intelligence and the logic of rules-based recommendations can be beneficial to the customer interaction without compromising on the system stability and affordability. The framework focuses on the feasibility of integrating the smart intent analysis and is the first step toward intelligent and scalable AI-supported supermarket processes and assistance in enhancing customer satisfaction.
How to Cite this Paper
Devapriya, M. H. ,. R. (2026). Persuasive Marketing Intelligence in Supermarket Kiosk Agents: Extending an Intelligent Receptionist System for Context-Aware Recommendations. International Journal of Creative and Open Research in Engineering and Management, <i>02</i>(05), 1-10. https://doi.org/10.55041/ijcope.v2i5.604
Devapriya, M.. "Persuasive Marketing Intelligence in Supermarket Kiosk Agents: Extending an Intelligent Receptionist System for Context-Aware Recommendations." International Journal of Creative and Open Research in Engineering and Management, vol. 02, no. 05, 2026, pp. 1-10. doi:https://doi.org/10.55041/ijcope.v2i5.604.
Devapriya, M.. "Persuasive Marketing Intelligence in Supermarket Kiosk Agents: Extending an Intelligent Receptionist System for Context-Aware Recommendations." International Journal of Creative and Open Research in Engineering and Management 02, no. 05 (2026): 1-10. https://doi.org/https://doi.org/10.55041/ijcope.v2i5.604.
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