Getting Business Insights through Clustering Online Behaviors

Abstract

This study aimed to explore the online users’ behaviors. Since the Internet was introduced to the market, the various and frequent online activities have increased, and it becomes more important for the businesses to understand the online users. Therefore this study analyzed the online users’ behaviors and segmented the users by usingK-means clustering method using actual clickstream data. There were four different research questions and, thus, four different sets of segmentations. It was found that many people find much of entertaining from online using SNS, games, and so on. In addition, some people only have access to a few specific websites. Some use the online service regularly every day while others use it in a very irregular pattern. People were divided into two groups, weekday group and weekend group. People are likely to be using the Internet either on weekdays or at weekend. Teenagers and people in their 50s are more likely to use it during weekend. In addition, teenagers also show different time zone (e.g., overnight) to use the Internet from other age groups. These results can shed light on understanding what consumers do online and what they are interested in currently and on decision making in marketing strategy.

Online shopping behaviour in the Northern and Southern Great Plain Regions

“…Az online élelmiszerkereskedelem, jellemzően a frissáru termékek tekintetében, nehezen tud terjeszkedni a termékek specialitásai miatt, ezen expanzió jelentős költségbefektetéssel jár (GKID 2022). 2017) szerint több empirikus kutatás irányult az online vásárlók tipologizálására (Kau et al 2003, Pragarauskaité -Dzemyda, 2012, Bang et al 2015, Prashar et al 2016, Jayashree 2016. A 3. táblázatban néhány szerző kiemelése alapján mutatja az elkülöníthető vásárlói csoportokat.…”

“…A 3. táblázatban néhány szerző kiemelése alapján mutatja az elkülöníthető vásárlói csoportokat. Forrás: saját szerkesztés Kau et al (2003), Kurucz (2009), Bang, J. et al 2015, GKI Digital-Árukereső.hu (2015, Piros-Fehér (2020b) alapján…”