Fuzzy Logic and Deep Learning for Brand Attention: A Consumer-Centric Approach to Product Packaging Design
Year: 2025
Type: article
Abstract: In the competitive world of today, brands cannot find an effective way of designing a package that attracts attention without considering the jungle that consumer preferences are. The problem with existing techniques is that they are incapable of adequately assessing subjective responses, and much to the dismay of designers, they are incapable of adjudicating between competing priorities, e.g. eye candy versus environmental friendliness. The three smart technologies compiled in our solution are Dempster-Shafer Fuzzy Sets to address the answers given, encouraging including the type “I kinda like it”, AI vision analysis to immediately rate the designs, and MACROS ranking to come up with the most having the ideal middle-ground when features are conflicting. A test with 2,100 actual shoppers showed game-changing results: designs in our system got a 32 percent higher score in recall tests, elicited 25 percent more smiles and hit the sweet spot between what looks good (70 percent) and what is green (30 percent). Better still, with our tool, brands would be able to sanction final designs 4 times faster. It is not mere theory and we have developed the art of packaging into a science which puts an upper hand to the companies once on the venture in the crowded aisles of stores.
Source: IEEE Access
Author: Heng Wu
Language: English
Subfield: Marketing
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,075
Awards: G2106735742, G7555648118
OpenAlex ID: W4413118581