Fuzzy Logic and Deep Learning for Brand Attention: A Consumer-Centric Approach to Product Packaging Design

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.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3596858
Primary Topic
Consumer Packaging Perceptions and Trends
Type
article
Field-Weighted Citation Impact
0.00

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article

Fuzzy Logic and Deep Learning for Brand Attention: A Consumer-Centric Approach to Product Packaging Design

Wu Heng
IEEE Access
Consumer Packaging Perceptions and Trends
article

Fuzzy Logic and Deep Learning for Brand Attention: A Consumer-Centric Approach to Product Packaging Design

Wu Heng
article en

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.

IEEE AccessVol. 13
Hefei University (CN), Hefei Urban Planning & Design Institute (CN)
Anhui Provincial Quality Engineering Project
Openalex Percentile: Top 73%
Consumer Packaging Perceptions and Trends
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