A market basket analysis of seven retail branches in Kyrgyzstan using an apriori algorithm

The proliferation of online trading platforms compelled businesses to delve into the analysis of customer behaviour. Therefore, this study seeks to scrutinise customer behaviour in Kyrgyzstan, a previously unexamined market, aiming to augment supplier revenue, service quality, and customer satisfaction. The transaction data employed in this investigation was sourced from the retail sector and processed across seven distinct regions. The analysis was done utilising the Apriori algorithm. Our findings reveal that Bishkek city, the premier sales region, yielded 866 association rules from a dataset of 308,998 records. These rules demonstrate robust connections among items, indicating an 83% probability of relationships between the consumption patterns of various products. The experimental verification highlights significant patterns and associations with a high degree of confidence. The discerned insights can profoundly inform targeted marketing initiatives, optimise inventory management practices, elevate customer experiences, and promise to foster growth within the dynamic landscape of the retail sector.

Authors

Institutions

Publication Details

Journal
International Journal of Business Intelligence and Data Mining
Published
2024-11-29
DOI
https://doi.org/10.1504/ijbidm.2025.10068213
Primary Topic
Global Trade and Competitiveness
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A market basket analysis of seven retail branches in Kyrgyzstan using an apriori algorithm

Rita İsmailova, Nematullah Wahidi
International Journal of Business Intelligence and Data Mining
Global Trade and Competitiveness
article

A market basket analysis of seven retail branches in Kyrgyzstan using an apriori algorithm

Rita İsmailova, Nematullah Wahidi
article en

Abstract

The proliferation of online trading platforms compelled businesses to delve into the analysis of customer behaviour. Therefore, this study seeks to scrutinise customer behaviour in Kyrgyzstan, a previously unexamined market, aiming to augment supplier revenue, service quality, and customer satisfaction. The transaction data employed in this investigation was sourced from the retail sector and processed across seven distinct regions. The analysis was done utilising the Apriori algorithm. Our findings reveal that Bishkek city, the premier sales region, yielded 866 association rules from a dataset of 308,998 records. These rules demonstrate robust connections among items, indicating an 83% probability of relationships between the consumption patterns of various products. The experimental verification highlights significant patterns and associations with a high degree of confidence. The discerned insights can profoundly inform targeted marketing initiatives, optimise inventory management practices, elevate customer experiences, and promise to foster growth within the dynamic landscape of the retail sector.

International Journal of Business Intelligence and Data MiningVol. 26(1/2)
Kyrgyz-Türkish Manas Üniversity (KG)
Zero hunger
Openalex Percentile: Top 63%
Global Trade and Competitiveness
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A market basket analysis of seven retail branches in Kyrgyzstan using an apriori algorithm — Rita İsmailova, Nematullah Wahidi · International Journal of Business Intelligence and Data Mining (2024) | TGRS Research Map | TGRS