Multimodal capture of consumer intent in retail

Authors:
Jhilmil Jain;Riddhiman Ghosh;Mohamed Dekhil
Affiliations:
Hewlett-Packard Laboratories, Palo Alto, CA, USA;Hewlett-Packard Laboratories, Palo Alto, CA, USA;Hewlett-Packard Laboratories, Palo Alto, CA, USA
Venue:
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Year:
2008

Citing 2
Cited 5

Why use memo for all?: restructuring mobile applications to support informal note taking

CHI '05 Extended Abstracts on Human Factors in Computing Systems
Why We Buy: The Science of Shopping

Why We Buy: The Science of Shopping

Color match: an imaging based mobile cosmetics advisory service

Proceedings of the 10th international conference on Human computer interaction with mobile devices and services
Imaging-based cosmetics advisory service

CHI '09 Extended Abstracts on Human Factors in Computing Systems
Discovering user profiles

Proceedings of the 18th international conference on World wide web
Snap and match: a case study of virtual color cosmetics consultation

CHI '10 Extended Abstracts on Human Factors in Computing Systems
weShop: using social data as context in the retail experience

Proceedings of the 2012 ACM Conference on Ubiquitous Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper we present a prototype for capturing retail related consumer intent using multiple devices and in multimodal input formats such as text, audio, and still images. The prototype was used in a longitudinal user study to analyze the process that consumers go through in order to make purchasing decisions. Based on these findings, we recommend desirable features for information management systems specifically designed for the retail environment.