The Role of Prescriptive Analytics on Product Availability Towards Improved Customer Loyalty in Quick Commerce
- Title
- The Role of Prescriptive Analytics on Product Availability Towards Improved Customer Loyalty in Quick Commerce
- Creator
- Muloor, Kiran Hemanthaj; Iyer, Lakshmi Shankar; Manu, K.S.; Saseekala, M.
- Description
- Quick commerce (Q-commerce) has transformed retail by enabling ultra-fast deliveries, requiring optimised product assortment and inventory management. While traditional e-commerce offers a broad product range and competitive pricing, its delivery limitations led to Q-commerces emergence, ensuring fulfilment within 30min to a few hours. This study applies prescriptive analytics, machine learning and optimisation algorithms to enhance decision-making in Q-commerce. Advanced forecasting models, such as LSTM networks, improved demand forecasting with a Mean Absolute Error (MAE) of 0.25 and Root Mean Square Error (RMSE) of 0.35, reducing inventory costs by 10%. Linear programming optimised product mix, increasing sales by 15%. LSTM demonstrated high accuracy in predicting demand patterns, ensuring the availability of high-demand products while minimising overstock. Market Basket Analysis (MBA) revealed significant product associations, streamlining fulfilment centre operations and enhancing cross-selling strategies. Market Basket Analysis (MBA) using the Apriori algorithm identified key product associations, reducing picking times by 20% and boosting order value by 12%, contributing to a 15% rise in overall sales. Personalised recommendation systems using collaborative and content-based filtering increased conversion rates by 20% and customer retention by 15%. Despite these advancements, challenges in computational feasibility and synthetic data applicability persist. Future research should focus on real-time analytics and adaptive inventory strategies to enhance scalability and efficiency. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.
- Source
- Lecture Notes in Networks and Systems;Volume;1613 LNNS;pp.513-526
- Date
- 01-01-2026
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Artificial intelligence; Consumer decisions; Fast delivery; Machine learning; Micro-fulfilment centres; Prescriptive analytics; Product assortment; Product quality; Purchase behaviour; Quick commerce
- Coverage
- Muloor K.H., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India, LTIMindtree Limited, Karnataka, Bengaluru, India; Iyer L.S., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India, School of Business and Management, Centre for AI, CHRIST University, Karnataka, Bengaluru, India; Manu K.S., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India; Saseekala M., School of Business and Management, CHRIST University, Karnataka, Bengaluru, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISSN: 23673370; ISBN: 978-981952874-5;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Muloor, Kiran Hemanthaj; Iyer, Lakshmi Shankar; Manu, K.S.; Saseekala, M., “The Role of Prescriptive Analytics on Product Availability Towards Improved Customer Loyalty in Quick Commerce,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25433.