<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper explores the GIS spatial analysis technique, which models the data as a whole and performs three-dimensional coordinate transformations, maps points in one coordinate system to another, and then establishes slice maps according to the slice resolution and visualizes and analyzes the data. This paper analyzes the spatial evolution characteristics of product A’s marketing dominance, time domain and geographical concern based on the GIS analysis model and compares the traditional method with the GIS spatial analysis method to analyze the market influence of using GIS marketing in order to highlight the advantages of the GIS analysis method in product marketing and data analysis. The results show that the annual contribution rates of the differences in product A attention between regions from 2013 to 2018 are 36.46%, 40.85%, 46.68%, 48.89%, 43.62%, and 44.21%, with an average value of 45%. The influence analysis efficiency of the GIS analysis method is more than 4.4, whereas that of the original method basically maintains the influence analysis efficiency between 3.8 and 4.0, indicating that the influence analysis efficiency of the GIS analysis method is above 4.4, while the influence analysis efficiency of the original method basically maintains the influence analysis efficiency between 3.8 and 4.0. 4.0, indicating that GIS technology has the absolute advantage for marketing data visualization analysis.</p>
</abstract>

This paper explores the GIS spatial analysis technique, which models the data as a whole and performs three-dimensional coordinate transformations, maps points in one coordinate system to another, and then establishes slice maps according to the slice resolution and visualizes and analyzes the data. This paper analyzes the spatial evolution characteristics of product A’s marketing dominance, time domain and geographical concern based on the GIS analysis model and compares the traditional method with the GIS spatial analysis method to analyze the market influence of using GIS marketing in order to highlight the advantages of the GIS analysis method in product marketing and data analysis. The results show that the annual contribution rates of the differences in product A attention between regions from 2013 to 2018 are 36.46%, 40.85%, 46.68%, 48.89%, 43.62%, and 44.21%, with an average value of 45%. The influence analysis efficiency of the GIS analysis method is more than 4.4, whereas that of the original method basically maintains the influence analysis efficiency between 3.8 and 4.0, indicating that the influence analysis efficiency of the GIS analysis method is above 4.4, while the influence analysis efficiency of the original method basically maintains the influence analysis efficiency between 3.8 and 4.0. 4.0, indicating that GIS technology has the absolute advantage for marketing data visualization analysis.

Three-dimensional visualization and analysis of marketing data based on GIS information technology

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

This paper explores the GIS spatial analysis technique, which models the data as a whole and performs three-dimensional coordinate transformations, maps points...

Three-dimensional visualization and analysis of marketing data based on GIS information technology

Published Online: Dec 06, 2023

Page range: -

Received: Feb 10, 2023

Accepted: Jun 16, 2023

DOI: https://doi.org/10.2478/amns.2023.2.01397

Keywords
GIS information technology, Spatial analytics, Data modeling, Spatial evolution, 3D visualization

© 2023 Zhenhai Yu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Three-dimensional visualization and analysis of marketing data based on GIS information technology

Published Online: Dec 06, 2023

Page range: -

Received: Feb 10, 2023

Accepted: Jun 16, 2023

DOI: https://doi.org/10.2478/amns.2023.2.01397

KeywordsGIS information technology, Spatial analytics, Data modeling, Spatial evolution, 3D visualization

© 2023 Zhenhai Yu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Keywords
GIS information technology, Spatial analytics, Data modeling, Spatial evolution, 3D visualization