Customer Complaints Analysis Using Textmining Method

2022-01-0131

03/29/2022

Features
Event
WCX SAE World Congress Experience
Authors Abstract
Content
In recent years, the automobile industry has been making efforts to develop vehicles that satisfy customers' emotions rather than malfunctions. The Vehicle Dependability Study(VDS) has been strengthened emotion items since the introduction of the new evaluation system VDS3 from 2015. The ratio of emotion items increased from 11% to 25%. In order to clarify the problem and cause of emotion items, we analyzed verbatim which is the customers' complaint data provided by J.D power every year, but it was difficult to extract customers' intention because the number of verbatim is small and expressed in terms of customer’s term rather than engineer’s term. To solve the problem, we are additionally colleting big data such as internet, warranty, online survey. Since the amount of data is very large, we developed textmining techniques such as dictionary, topic, Support Vector Machine(SVM), n-gram to improve process. And we developed the Internet Data Search(IDS) program that everyone in the company can use by web.
Meta TagsDetails
DOI
https://doi.org/10.4271/2022-01-0131
Pages
5
Citation
You, H., "Customer Complaints Analysis Using Textmining Method," SAE Technical Paper 2022-01-0131, 2022, https://doi.org/10.4271/2022-01-0131.
Additional Details
Publisher
Published
Mar 29, 2022
Product Code
2022-01-0131
Content Type
Technical Paper
Language
English