Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data

Tolga Kaya; Ahmet Talha Yiğit; Utku Doğruak

doi:10.1007/978-3-030-51156-2_10

Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data

Tolga Kaya, Ahmet Talha Yiğit^*, Utku Doğruak

^*Bu çalışma için yazışmadan sorumlu yazar

İşletme Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

Özet

The purpose of this study is to suggest a clustering approach to define the main groups of baskets in Turkish fast-moving consumer goods (FMCG) industry based on the sectoral decomposition, the total value and the size of the baskets. To do this, based on the information regarding the 2,965,837 baskets (8,147,233 transactions) of 14293 households which took place in the calendar year 2018, alternative unsupervised learning methods such as K-means, and Gaussian mixtures are implemented to obtain and define the basket patterns in Turkey. A supervised ensembling approach based on XG-Boost method is also suggested to assign the new baskets into the existing clusters. Results show that, “SaveTheDay”, “CareTrip”, “Breakfast”, “SuperMain” and “MeatWalk” are among the most important basket types in Turkish FMCG sector.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Intelligent and Fuzzy Techniques
Ana bilgisayar yayını alt yazısı	Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference
Editörler	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A. Cagri Tolga
Yayınlayan	Springer
Sayfalar	71-78
Sayfa sayısı	8
ISBN (Basılı)	9783030511555
DOI'lar	https://doi.org/10.1007/978-3-030-51156-2_10
Yayın durumu	Yayınlandı - 2021
Etkinlik	International Conference on Intelligent and Fuzzy Systems, INFUS 2020 - Istanbul, Turkey Süre: 21 Tem 2020 → 23 Tem 2020

Yayın serisi

Adı	Advances in Intelligent Systems and Computing
Hacim	1197 AISC
ISSN (Basılı)	2194-5357
ISSN (Elektronik)	2194-5365

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	International Conference on Intelligent and Fuzzy Systems, INFUS 2020
Ülke/Bölge	Turkey
Şehir	Istanbul
Periyot	21/07/20 → 23/07/20

Bibliyografik not

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Belgeye Erişim

10.1007/978-3-030-51156-2_10

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Kaya, T., Yiğit, A. T., & Doğruak, U. (2021). Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference (pp. 71-78). (Advances in Intelligent Systems and Computing; Hac. 1197 AISC). Springer. https://doi.org/10.1007/978-3-030-51156-2_10

Kaya, Tolga ; Yiğit, Ahmet Talha ; Doğruak, Utku. / Basket Patterns in Turkey : A Clustering of FMCG Baskets Using Consumer Panel Data. Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. editör / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A. Cagri Tolga. Springer, 2021. pp. 71-78 (Advances in Intelligent Systems and Computing).

@inproceedings{f217c51efb784c09b7d47ac41bdebfeb,

title = "Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data",

abstract = "The purpose of this study is to suggest a clustering approach to define the main groups of baskets in Turkish fast-moving consumer goods (FMCG) industry based on the sectoral decomposition, the total value and the size of the baskets. To do this, based on the information regarding the 2,965,837 baskets (8,147,233 transactions) of 14293 households which took place in the calendar year 2018, alternative unsupervised learning methods such as K-means, and Gaussian mixtures are implemented to obtain and define the basket patterns in Turkey. A supervised ensembling approach based on XG-Boost method is also suggested to assign the new baskets into the existing clusters. Results show that, “SaveTheDay”, “CareTrip”, “Breakfast”, “SuperMain” and “MeatWalk” are among the most important basket types in Turkish FMCG sector.",

keywords = "Basket analysis, Cluster analysis, Consumer panel, FMCG, K-means, Supervised learning",

author = "Tolga Kaya and Yiğit, {Ahmet Talha} and Utku Doğruak",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2020 ; Conference date: 21-07-2020 Through 23-07-2020",

year = "2021",

doi = "10.1007/978-3-030-51156-2_10",

language = "English",

isbn = "9783030511555",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "71--78",

editor = "Cengiz Kahraman and {Cevik Onar}, Sezi and Basar Oztaysi and Sari, {Irem Ucal} and Selcuk Cebi and Tolga, {A. Cagri}",

booktitle = "Intelligent and Fuzzy Techniques",

address = "Germany",

}

Kaya, T, Yiğit, AT & Doğruak, U 2021, Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Advances in Intelligent Systems and Computing, hac. 1197 AISC, Springer, pp. 71-78, International Conference on Intelligent and Fuzzy Systems, INFUS 2020, Istanbul, Turkey, 21/07/20. https://doi.org/10.1007/978-3-030-51156-2_10

Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data. / Kaya, Tolga; Yiğit, Ahmet Talha; Doğruak, Utku.
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A. Cagri Tolga. Springer, 2021. p. 71-78 (Advances in Intelligent Systems and Computing; Hac. 1197 AISC).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - Basket Patterns in Turkey

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2020

AU - Kaya, Tolga

AU - Yiğit, Ahmet Talha

AU - Doğruak, Utku

PY - 2021

Y1 - 2021

N2 - The purpose of this study is to suggest a clustering approach to define the main groups of baskets in Turkish fast-moving consumer goods (FMCG) industry based on the sectoral decomposition, the total value and the size of the baskets. To do this, based on the information regarding the 2,965,837 baskets (8,147,233 transactions) of 14293 households which took place in the calendar year 2018, alternative unsupervised learning methods such as K-means, and Gaussian mixtures are implemented to obtain and define the basket patterns in Turkey. A supervised ensembling approach based on XG-Boost method is also suggested to assign the new baskets into the existing clusters. Results show that, “SaveTheDay”, “CareTrip”, “Breakfast”, “SuperMain” and “MeatWalk” are among the most important basket types in Turkish FMCG sector.

AB - The purpose of this study is to suggest a clustering approach to define the main groups of baskets in Turkish fast-moving consumer goods (FMCG) industry based on the sectoral decomposition, the total value and the size of the baskets. To do this, based on the information regarding the 2,965,837 baskets (8,147,233 transactions) of 14293 households which took place in the calendar year 2018, alternative unsupervised learning methods such as K-means, and Gaussian mixtures are implemented to obtain and define the basket patterns in Turkey. A supervised ensembling approach based on XG-Boost method is also suggested to assign the new baskets into the existing clusters. Results show that, “SaveTheDay”, “CareTrip”, “Breakfast”, “SuperMain” and “MeatWalk” are among the most important basket types in Turkish FMCG sector.

KW - Basket analysis

KW - Cluster analysis

KW - Consumer panel

KW - FMCG

KW - K-means

KW - Supervised learning

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U2 - 10.1007/978-3-030-51156-2_10

DO - 10.1007/978-3-030-51156-2_10

M3 - Conference contribution

AN - SCOPUS:85088744173

SN - 9783030511555

T3 - Advances in Intelligent Systems and Computing

SP - 71

EP - 78

BT - Intelligent and Fuzzy Techniques

A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

A2 - Oztaysi, Basar

A2 - Sari, Irem Ucal

A2 - Cebi, Selcuk

A2 - Tolga, A. Cagri

PB - Springer

Y2 - 21 July 2020 through 23 July 2020

ER -

Kaya T, Yiğit AT, Doğruak U. Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editörler, Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Springer. 2021. p. 71-78. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-51156-2_10

Basket Patterns in Turkey: A Clustering of FMCG Baskets Using Consumer Panel Data

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Belgeye Erişim

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