Study on Web Analytics Utilizing Segmentation Knowledge in Business to Business Manufacturer Site | Zendy

Akiyuki Sekiguchi | Zendy; Kazuhiko Tsuda | Zendy

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Study on Web Analytics Utilizing Segmentation Knowledge in Business to Business Manufacturer Site

Author(s) -

Akiyuki Sekiguchi,

Kazuhiko Tsuda

Publication year - 2014

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2014.08.164

Subject(s) - computer science , analytics , web analytics , usability , segmentation , key (lock) , world wide web , market segmentation , data science , the internet , human–computer interaction , web development , web intelligence , artificial intelligence , business , marketing , computer security

Web analytics of B to B sites is mandatory for improving usability and leveraging data for marketing. In this study we tried web analytics by some segmentation and confirmed it is effective. We defined some of the segment models (7 segmentation type) and examined web access using some segments. One of the most important segmentations is registered versus unregistered users and we confirmed user behavior is different with each segment. We confirmed key metrics like bounce rate, referrer, and exit page analysis are especially beneficial for B to B manufacturer site enhancement

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