Influence of Car Configurator Webpage Data from Automotive Manufacturers on Car Sales by Means of Correlation and Forecasting

Juan Manuel García Sánchez, Xavier Vilasís Cardona, Alexandre Lerma Martín

Research output: Indexed journal article Articlepeer-review

Abstract

A methodology to prove the influence of car configurator webpage data for automotive manufacturers is developed across this research. Firstly, the correlation between online data and sales is measured. Afterward, car variant sales are predicted using a set of forecasting techniques divided into univariate and multivariate ones. Finally, weekly color mix sales based on these techniques are built and compared. Results show that users visit car configurator webpages 1 to 6 months before the purchase date. Additionally, car variants predictions and weekly color mix sales derived from multivariate techniques, i.e., using car configurator data as external input, provide improvement up to 25 points in the assessment metric.

Original languageEnglish
Pages (from-to)634-653
Number of pages20
JournalForecasting
Volume4
Issue number3
DOIs
Publication statusPublished - Sept 2022
Externally publishedYes

Keywords

  • automotive OEMs
  • car configurator data
  • forecasting
  • machine learning
  • Pearson correlation coefficient
  • prediction
  • time series
  • weekly color mix sales

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