Behavior tracker: Visual analytics of customer switching behavior in O2O market

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Visualization of customer behavior is urgently needed for an increasing number of customer orders on O2O (online to offline) platform. Although many works have been done on visualizing customer opinion or customer click events of one store, visualizing customer switching behavior among stores is still challenging. The challenge is to show customer order records over time and structure the inter-connection among different stores when customer switching behavior happens. In this work, we focus on Takeout O2O service to present a novel visual analysis system for retailers focusing on customer switching behavior patterns. Firstly we define five customer segments based on switching behavior. Then this system enables temporal-spatial driver exploration for different segments through several interactive views. Moreover, in order to visualize inter-connection sequences, augmented streamgraph with the bundled parallel coordinates is proposed as one alternative technique to visualize temporal event sequences. Case studies through collaboration with domain experts also demonstrate the usefulness and effectiveness of this system in helping customer relationship management.

Original languageEnglish
Title of host publicationVINCI 2018 - 11th International Symposium on Visual Information Communication and Interaction
PublisherAssociation for Computing Machinery
Pages17-24
Number of pages8
ISBN (Electronic)9781450365017
DOIs
StatePublished - 13 Aug 2018
Event11th International Symposium on Visual Information Communication and Interaction, VINCI 2018 - Vaxjo, Sweden
Duration: 13 Aug 201815 Aug 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference11th International Symposium on Visual Information Communication and Interaction, VINCI 2018
Country/TerritorySweden
CityVaxjo
Period13/08/1815/08/18

Keywords

  • E-commerce
  • Temporal event sequence
  • Visual analytic system
  • Visualization of customer switching behavior

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