Customer online shopping experience data analytics

采购 竞争对手分析 市场细分 业务 顾客终身价值 营销 客户情报 消费者行为 客户保留 计算机科学 服务(商务) 服务质量
作者
Eugene Y. Wong,Wei Yan
出处
期刊:International Journal of Retail & Distribution Management [Emerald (MCB UP)]
卷期号:46 (4): 406-420 被引量:44
标识
DOI:10.1108/ijrdm-06-2017-0130
摘要

Purpose The purpose of this paper is to develop a customer online behaviour analysis tool, segment high-value customers, analyse their online purchasing behaviour and predict their next purchases from an online air travel corporation. Design/methodology/approach An operations review of the customer online shopping process of an online travel agency (OTA) is conducted. A customer online shopping behaviour analysis tool is developed. The tool integrates competitors’ pricing data mining, customer segmentation and predictive analysis. The impacts of competitors’ price changes on customer purchasing decisions regarding the OTA’s products are evaluated. The integrated model for mining pricing data, identifying potential customers and predicting their next purchases helps the OTA recommend tailored product packages to its individual customers with reference to their travel patterns. Findings In the customer segmentation analysis, 110,840 customers are identified and segmented based on their purchasing behaviour. The relationship between the purchasing behaviour in an OTA and the price changes of different OTAs are analysed. There is a significant relationship between the flight duration time and the purchase lead time. The next travel destinations of segmented high-value customers are predicted with reference to their travel patterns and the significance of the relationships between destination pairs. Practical implications The developed model contributes to pricing evaluation, customer segmentation and package customization for online customers. Originality/value This study provides novel method and insights into customer behaviour towards OTAs through an integrated model of customer segmentation, customer behaviour and prediction analysis.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
空笑完成签到 ,获得积分10
刚刚
SciGPT应助123采纳,获得10
刚刚
longlong完成签到,获得积分10
刚刚
1秒前
LL完成签到,获得积分10
1秒前
在英快尔完成签到,获得积分10
1秒前
zaaa完成签到,获得积分10
2秒前
勿庸完成签到,获得积分10
8秒前
问问问发布了新的文献求助10
8秒前
莱贝特完成签到,获得积分20
10秒前
胡里奥完成签到 ,获得积分10
10秒前
zz发布了新的文献求助10
10秒前
11秒前
11秒前
赘婿应助能干垣采纳,获得10
14秒前
今后应助sayso采纳,获得10
14秒前
丘比特应助戴衡霞采纳,获得10
14秒前
不配.应助weiyi采纳,获得10
15秒前
随机子应助Leo采纳,获得30
17秒前
今后应助1+1采纳,获得10
18秒前
欣喜的秋灵应助shaohua2011采纳,获得10
18秒前
20秒前
奥利给完成签到,获得积分10
20秒前
搞怪网络发布了新的文献求助10
22秒前
余问芙完成签到 ,获得积分10
22秒前
23秒前
23秒前
不配.应助害羞彩虹采纳,获得10
23秒前
是赤赤呀完成签到,获得积分10
26秒前
27秒前
1+1发布了新的文献求助10
29秒前
如意2023完成签到 ,获得积分10
30秒前
30秒前
medmh完成签到,获得积分10
32秒前
SciGPT应助忐忑的阑香采纳,获得10
32秒前
33秒前
35秒前
36秒前
怕黑的道天完成签到,获得积分10
36秒前
kk发布了新的文献求助30
37秒前
高分求助中
Spray / Wall-interaction Modelling by Dimensionless Data Analysis 2000
Evolution 3rd edition 1500
Mantiden: Faszinierende Lauerjäger Faszinierende Lauerjäger 700
PraxisRatgeber: Mantiden: Faszinierende Lauerjäger 700
ALA生合成不全マウスでの糖代謝異常の分子機構解析 520
Mathematics and Finite Element Discretizations of Incompressible Navier—Stokes Flows 500
A new species of Coccus (Homoptera: Coccoidea) from Malawi 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3187770
求助须知:如何正确求助?哪些是违规求助? 2837531
关于积分的说明 8015469
捐赠科研通 2500157
什么是DOI,文献DOI怎么找? 1334772
科研通“疑难数据库(出版商)”最低求助积分说明 637295
邀请新用户注册赠送积分活动 605251