Understanding Customer Preferences and Predictive Sales Trends in the Automobile Sector: An Analytical Study with Power BI

In the rapidly evolving auto industry today, knowing the customer's preference is crucial for forecasting future car sales trends and creating business strategies. With this research study, it concentrates on detecting consumer preference and foretelling car sales with Power BI, a contemporary business intelligence platform for data analysis and visualization. The main objective of this study is to examine existing customer trends and predict sales patterns based on survey information. The research also seeks to determine the most desired car models and options, investigate the effect of customer demographics including age, income, and lifestyle, and approximate future demand for electric and hybrid cars. It also investigates the effect of variables such as price sensitivity, fuel efficiency, safety, and smart technology on car purchases. Surveys were conducted using a standardized questionnaire that captured multiple sides of customer behavior, such as preferred vehicle types, price point, fuel type, importance of sophisticated features, and future buying plans. Power BI was used to analyze the responses and reveal latent patterns and visual trends through bar charts, pie charts, filters, slicers, and forecasting models. The findings of the study indicate high customer demand for fuel efficiency, safety features, and technology integration. It also shows increased awareness and interest in electric vehicles, particularly among environmentally aware and younger buyers. Power BI's interactive dashboards offered greater insights by graphically mapping customer segments and sales trends. This study illustrates the effective utilization of business intelligence tools such as Power BI in assisting data-driven decision-making within the automobile sector. Knowing what drives customer choices helps car manufacturers and dealers plan for better marketing, enhance inventory control, and provide products that more closely meet consumers' expectations. This study, in general, provides valuable information on how to align business processes with customer needs in a fast-changing market.

Authors

Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-04-24
DOI
https://doi.org/10.22214/ijraset.2025.69332
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
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article

Understanding Customer Preferences and Predictive Sales Trends in the Automobile Sector: An Analytical Study with Power BI

P. M. Gokulraj
International Journal for Research in Applied Science and Engineering Technology
Big Data and Business Intelligence
article

Understanding Customer Preferences and Predictive Sales Trends in the Automobile Sector: An Analytical Study with Power BI

P. M. Gokulraj
article en

Abstract

In the rapidly evolving auto industry today, knowing the customer's preference is crucial for forecasting future car sales trends and creating business strategies. With this research study, it concentrates on detecting consumer preference and foretelling car sales with Power BI, a contemporary business intelligence platform for data analysis and visualization. The main objective of this study is to examine existing customer trends and predict sales patterns based on survey information. The research also seeks to determine the most desired car models and options, investigate the effect of customer demographics including age, income, and lifestyle, and approximate future demand for electric and hybrid cars. It also investigates the effect of variables such as price sensitivity, fuel efficiency, safety, and smart technology on car purchases. Surveys were conducted using a standardized questionnaire that captured multiple sides of customer behavior, such as preferred vehicle types, price point, fuel type, importance of sophisticated features, and future buying plans. Power BI was used to analyze the responses and reveal latent patterns and visual trends through bar charts, pie charts, filters, slicers, and forecasting models. The findings of the study indicate high customer demand for fuel efficiency, safety features, and technology integration. It also shows increased awareness and interest in electric vehicles, particularly among environmentally aware and younger buyers. Power BI's interactive dashboards offered greater insights by graphically mapping customer segments and sales trends. This study illustrates the effective utilization of business intelligence tools such as Power BI in assisting data-driven decision-making within the automobile sector. Knowing what drives customer choices helps car manufacturers and dealers plan for better marketing, enhance inventory control, and provide products that more closely meet consumers' expectations. This study, in general, provides valuable information on how to align business processes with customer needs in a fast-changing market.

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(4)
Openalex Percentile: Top 87%
Big Data and Business Intelligence
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