SEGMENTATION OF OUTLETS WITH K-MEANS CLUSTERING BASED ON CUSTOMER TRANSACTION DATA TO DEFINE MARKETING STRATEGIES

Abstrak

The largest retail company in South Korea which expanded to Indonesia in 2016 by using the brand GS Supermarket. Currently growing and developing to consist of 7 branch outlets spread across the JABODETABEK area. To be able to survive, develop & compete in this line of business, GS Supermarket must have a marketing strategy that is right on target. In this study the author used the clustering method with the k-means algorithm. This method is done by grouping customers from all GS Supermarket branch outlets based on customer transaction data (total transactions, phone providers and payment method), The result from this study shows that there are 3 clusters consisting of Clusters Mythic which is formed with a high transaction category, using payment methods through EDC Mandiri and BCA, is dominated by consumers who use Telkomsel and XL providers. Epic cluster is formed from transactions below the average of other clusters, using cash payment methods and dominated by non-member consumers. Cluster Legend is formed from medium transactions even though the value is still below average and dominated by consumers with payment methods through EDC BNI. The results of this study showed that the total amount of shopping transactions was dominated by consumers using Telkomsel and XL providers and using payment methods through EDC Mandiri and BCA. So that, the recommended marketing mix strategy can be in the form of establishing certain cooperation and promotions with mobile phone providers and banks.