| Literature DB >> 36211867 |
Fang Wang1, Zengguang Fan2, Yuhui Qi3.
Abstract
In order not to be eliminated by the market, enterprises must face various consumer preferences, design products that meet consumer preferences, and enhance competitiveness. This paper combines on-the-spot marketing to study the product preferences of consumers and the personality characteristics of media hosts. This paper introduces the data mining technology of news media into the research of consumer's preference for products. Based on the comprehensive use of media mining technology, customer research theory, and product background and foundation, the specific process of influencing consumers' product preference is established. It can be seen from the study that the personality of the anchor has a great relationship with the consumption level of consumers and the sales rate of products, with an impact of 78.53%. Through this study, we can see that there is a certain relationship between consumers' product preference and anchoring personality. Studying the basic characteristics of the phenomenon live broadcast commodity marketing model has important theoretical value for analyzing the live broadcast commodity marketing model. It points out the direction for the scientific, healthy, and sustainable development of the future live broadcast commodity marketing mode.Entities:
Keywords: field marketing; media analysis; media communication; news dissemination; product preferences
Year: 2022 PMID: 36211867 PMCID: PMC9533055 DOI: 10.3389/fpsyg.2022.1007846
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
Figure 1Grid based method and model-based method.
Figure 2The data crawling flow chart.
Figure 3Information content in data mining tools.
Cluster analysis sample data table.
| Indicator 1 | Indicator 2 | .. | Indicator n | |
|---|---|---|---|---|
| Unit 1 | X10 | X13 | .. | X2P |
| Unit 2 | X20 | X23 | .. | X1P |
| Unit n | Xn1 | Xn2 | .. | qqXnP |
Frequency of emotional tendency of product reviews.
| Product | Favorable rate (%) | Bad review rate (%) |
|---|---|---|
| Mobile | 81.23 | 18.31 |
| Clothes | 95.36 | 2.98 |
| Furniture | 89.31 | 8.97 |
| Medicines and chemical reagents | 87.31 | 15.98 |
Correlation analysis data table.
| Product description quantity | Total comments | Bad review rate (%) |
|---|---|---|
| 2 | 747 | 6.53 |
| 6 | 928 | 9.53 |
| 14 | 674 | 16.53 |
| 12 | 636 | 13.63 |
Figure 4Research and analysis diagram of heat of live broadcast goods.
Figure 6Data map of live delivery marketing efficiency.
Figure 5Data analysis of live marketing with goods.
Figure 7Analysis of the influence of anchor personality.
Figure 8Data analysis diagram of anchor personnel.