EURO-Online login
- New to EURO? Create an account
- I forgot my username and/or my password.
- Help with cookies
(important for IE8 users)
2605. Enhancing Retail Strategies through Electronic Uniform Invoice Analysis: A Study on Consumer Behavior and Market Segmentation
Invited abstract in session WC-50: E-Commerce, stream Retail Operations.
Wednesday, 12:30-14:00Room: M2 (building: 101)
Authors (first author is the speaker)
| 1. | Ling-Jing Kao
|
| National Taipei University of Technology | |
| 2. | PEI-QI CHEN
|
| Business Management, National Taipei University of Technology | |
| 3. | Chih-Chou Chiu
|
| National Taipei University of Technology |
Abstract
As market competition escalates, retailers are compelled to understand consumer preferences more deeply to discern needs accurately. However, limited to internal databases, they lack access to cross-channel consumption data for a comprehensive understanding. This study utilizes electronic invoice records to analyze consumer behavior, predicting product choices in supermarkets. Employing the Self-Organizing Map (SOM) algorithm for consumer segmentation, it groups consumers with similar behavior, enhancing predictive accuracy. Using variables like expenditure and purchase frequency, it constructs Long Short-Term Memory (LSTM) models for channel forecasting. Empirical results show exceptional accuracy in product category prediction. This research aids effective segmentation, providing insights into consumer needs for inventory optimization. Cluster analysis facilitates targeted marketing, benefiting both retailers and consumers. Further validation and updates are vital for practical applications.
Keywords
- Marketing
- Analytics and Data Science
- Artificial Intelligence
Status: accepted
Back to the list of papers