Product Competitive Analysis Model Based on Consumer Preference Satisfaction Similarity: Case Study of Smartphone UGC
Accurately identifying key competitors across multiple product lines is essential for enhancing the flexibility and competitiveness of product strategies. This study introduces a novel data-driven model for competitive analysis termed the Product Competition Analysis Model based on Consumer Preferen...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Systems |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-8954/13/1/38 |
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| Summary: | Accurately identifying key competitors across multiple product lines is essential for enhancing the flexibility and competitiveness of product strategies. This study introduces a novel data-driven model for competitive analysis termed the Product Competition Analysis Model based on Consumer Preference Satisfaction Similarity (PCAM-CPSS). Unlike traditional methods that rely on assessments of the competitive environment, the PCAM-CPSS leverages sentiment analysis of user-generated content (UGC) to quantify consumer preference satisfaction. This method constructs a network based on product satisfaction similarity to map competitive relationships and employs a community detection algorithm to identify key competitors. To assess the model’s efficacy, we collected and analyzed user reviews of various smartphone brands to serve as an evaluation dataset. We compared the performance of the PCAM-CPSS against two mainstream competitive analysis methods: attribute similarity-based ratings and co-occurrence statistics. The results, evaluated using the Normalized Discounted Cumulative Gain (NDCG) index, demonstrate that the PCAM-CPSS, particularly with price adjustment, offers significant advantages in identifying competitors more accurately than other evaluated methods. |
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| ISSN: | 2079-8954 |