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Designing Planograms for Retail Shelves: A Visual Merchandising Approach Using Apriori Algorithm and K-Means Clustering of Customer Preferences
Abstract
The development of retail store businesses in Indonesia is widespread across various regions, positively impacting the increase in shopping activities among the community. Alongside the intense competition among retailers, fundamental issues are found regarding the shopping experience of customers who feel uncomfortable and dissatisfied with retail services. Customers are an essential aspect that needs attention, and their desires must be fulfilled to maintain the existence of a retail store. This study attempts to implement the concept of visual merchandising to enhance service quality through the planogram method aimed at improving the visual arrangement of sales shelfs. Regarding the layout of retail stores, shelf arrangement plays a significant role visually in influencing and attracting customer attention while shopping. In this study, two data mining techniques are used. The first method is association rule mining using the Apriori algorithm, which reveals the association rules formed between two or more product items, utilizing a total of 6,325 customer transaction records. The results indicate 12 rules formed based on product categories and 17 rules based on product sub-categories. The second technique is k-means clustering, which is used to identify differences in customer preferences in retail stores based on several variables regarding customers using 104 data customers. In practice, both the apriori and k-means algorithms face challenges, especially when handling large and complex data. Differences in preferences were found among the clusters, particularly regarding product arrangement on the sales shelf, such as grouping products by brand and price. A two-dimensional planogram design was developed to integrate the results from the previous stages. This design considers the availability and specifications of the shelves in the retail store. A planogram adjusted to customer purchasing patterns and preferences is expected to provide good service and positively impact store operations and stock management.
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T. Reardon and R. Hopkins, “The supermarket revolution in developing countries: Policies to address emerging tensions among supermarkets, suppliers and traditional retailers,” Eur. J. Dev. Res., vol. 18, no. 4, pp. 522–545, 2006, doi: 10.1080/09578810601070613.
C. H. Lee, X. Zhao, and Y. C. Lee, “Service quality driven approach for innovative retail service system design and evaluation: A case study,” Comput. Ind. Eng., vol. 135, no. February 2018, pp. 275–285, 2019, doi: 10.1016/j.cie.2019.06.001.
K. Czerniachowska, A genetic algorithm for the retail shelf space allocation problem with virtual segments, vol. 59, no. 1. Springer India, 2022. doi: 10.1007/s12597-021-00551-3.
E. Bilgic, O. Cakir, M. Kantardzic, Y. Duan, and G. Cao, “Retail analytics: store segmentation using Rule-Based Purchasing behavior analysis,” Int. Rev. Retail. Distrib. Consum. Res., vol. 31, no. 4, pp. 457–480, 2021, doi: 10.1080/09593969.2021.1915847.
J. R. Hanaysha, “An examination of the factors affecting consumer’s purchase decision in the Malaysian retail market,” PSU Res. Rev., vol. 2, no. 1, pp. 7–23, 2018, doi: 10.1108/PRR-08-2017-0034.
W. P. Nurmayanti et al., “Market Basket Analysis with Apriori Algorithm and Frequent Pattern Growth (Fp-Growth) on Outdoor Product Sales Data,” Int. J. Educ. Res. Soc. Sci., vol. 2, no. 1, pp. 132–139, 2021, doi: 10.51601/ijersc.v2i1.45.
K. Kaur and H. K. Saini, “Retailer’s awareness regarding use of visual merchandising in apparel retail stores,” Int. J. Home Sci., vol. 8, no. 1, pp. 103–108, 2022, [Online]. Available: http://www.homesciencejournal.com
V. P. S. Arora, S. Sharma, and N. K. Singh, “Nature and Functioning of Visual Merchandising in Organized Food Retailing,” Agric. Econ. Res. Rev., vol. 20, no. June, pp. 441–456, 2007.
M. B. R. Vaja, “Retail management,” Int. J. Res. Anal. Rev., vol. 2, no. 1, pp. 22–28, 2015, doi: 10.4324/9781315560854-16.
I. Surjandari and A. C. Seruni, “Design of Product Placement Layout in Retail Shop Using Market Basket Analysis,” MAKARA Technol. Ser., vol. 9, no. 2, 2010, doi: 10.7454/mst.v9i2.379.
F. R. Feijó and D. Botelho, “Effect of factors related to merchandising on retail sales,” RAE Rev. Adm. Empres., vol. 52, no. 6, pp. 628–642, 2012, doi: 10.1590/S0034-75902012000600005.
H. Chaniago, “Investigation of Factors Influencing Traditional Retail Success in Small Cities in Indonesia,” J. Appl. Econ. Sci., vol. 1, no. 67, pp. 65–75, 2020, doi: 10.14505/jaes.v15.1(67).05.
I. Sachdeva and S. Goel, “Retail store environment and customer experience: a paradigm,” J. Fash. Mark. Manag., vol. 19, no. 3, pp. 290–298, 2015, doi: 10.1108/JFMM-03-2015-0021.
D. Law, C. Wong, and J. Yip, “How does visual merchandising affect consumer affective response?: An intimate apparel experience,” Eur. J. Mark., vol. 46, no. 1, pp. 112–133, 2012, doi: 10.1108/03090561211189266.
C. Ebster and M. Garaus, Store design and visual merchandising: Creating store space that encourages buying. New York: Business Expert Press, 2011.
G. I. Cordova, S. Del Rosario Guerreros Surichaqui, F. Del Pilar Palomino Ricaldi, and W. Vicente-Ramos, “Impact of visual merchandising on the purchase decision of consumers from retail stores in central Peru,” Manag. Sci. Lett., vol. 10, no. 11, pp. 2447–2454, 2020, doi: 10.5267/j.msl.2020.4.005.
A. Pratama, B. Mulyawan, and T. Sutrisno, “Implementation of improved apriori algorithm for drug planograms in XYZ pharmacies and analysis of medicinal procurement planning using ABC critical index methods,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1007, no. 1, 2020, doi: 10.1088/1757-899X/1007/1/012186.
A. Fachrurozi, M. Junaedi, J. L. Putra, and W. Gata, “Algorithm Implementation Of Interest Buy Apriori Data On Consumer Retail Sales In Industry,” J. Informatics Telecommun. Eng., vol. 4, no. 1, pp. 48–56, 2020, doi: 10.31289/jite.v4i1.3775.
H. Kusumo, D. Marlina, M. Novita, and M. T. Anwar, “Analysis of transaction patterns at drug store with Apriori Algorithm,” J. Phys. Conf. Ser., vol. 1869, no. 1, 2021, doi: 10.1088/1742-6596/1869/1/012070.
T. A. Kumbhare and P. S. V Chobe, “An Overview of Association Rule Mining Algorithms,” Int. J. Comput. Sci. Inf. Technol., vol. 5, no. 1, pp. 927–930, 2014, [Online]. Available: https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=d4058d9f3f66c53ddea776c974fbd740afd994b4
S. Sidhu, U. Kumar Meena, A. Nawani, H. Gupta, and N. Thakur, “FP Growth Algorithm Implementation,” Int. J. Comput. Appl., vol. 93, no. 8, pp. 6–10, 2014, doi: 10.5120/16233-5613.
M. Z. Rodriguez et al., Clustering algorithms: A comparative approach, vol. 14, no. 1. 2019. doi: 10.1371/journal.pone.0210236.
Z. Syahputri, S. Sutarman, and M. A. P. Siregar, “Determining The Optimal Number of K-Means Clusters Using The Calinski Harabasz Index and Krzanowski and Lai Index Methods for Groupsing Flood Prone Areas In North Sumatra,” Sinkron, vol. 9, no. 1, pp. 571–580, 2024, doi: 10.33395/sinkron.v9i1.13246.
T. S. Madhulatha, “An overview of clustering methods,” IOSR J. Eng., vol. 2, no. 4, pp. 719–725, 2012, doi: 10.3233/ida-2007-11602.
B. Berman and J. R. Evans, Retail Management A Strategic Approach. Pearson Education India, 2013.
A. R. Biscaia, M. J. Rosa, P. M. e Sá, and C. S. Sarrico, “Assessing customer satisfaction and loyalty in the retail sector,” Int. J. Qual. Reliab. Manag., vol. 34, no. 9, pp. 1508–1529, 2017.
T. Scheffer, “Finding association rules that trade support optimally against confidence,” Intell. Data Anal., vol. 9, no. 4, pp. 381–395, 2005, doi: 10.3233/ida-2005-9405.
B. M. Prakash and Mishra Vivek, “Impact of Store Location and Layout on Consumer Purchase Behavior in Organized Retail,” Anvesha, vol. 10, no. 1, pp. 10–21, 2017.
I. A. Castro, A. C. Morales, and S. M. Nowlis, “The influence of disorganized shelf displays and limited product quantity on consumer purchase,” J. Mark., vol. 77, no. 4, pp. 118–133, 2013, doi: 10.1509/jm.11.0495.
V. Jain, A. Sharma, and P. Narwal, “Impact of Visual Merchandising on Consumer Behaviour towards Women’s Apparel,” Int. J. Res. Manag., vol. 5, no. 2, 2013, [Online]. Available: http://www.ijmrbs.com/currentissue.php
S. W. L. Fong, T. P. Kian, Y. S. Fern, and W. Vincent, “Monetary and Image Influences on the Purchase Decision of Private Label Products in Malaysia,” J. Adv. Manag. Sci., no. December, pp. 312–318, 2015, doi: 10.12720/joams.3.4.312-318.
N. Haj-Salem, J. C. Chebat, R. Michon, and S. Oliveira, “Why male and female shoppers do not see mall loyalty through the same lens? The mediating role of self-congruity,” J. Bus. Res., vol. 69, no. 3, pp. 1219–1227, 2016, doi: 10.1016/j.jbusres.2015.09.011.
J. Clement, T. Kristensen, and K. Grønhaug, “Understanding consumers’ in-store visual perception: The influence of package design features on visual attention,” J. Retail. Consum. Serv., vol. 20, no. 2, pp. 234–239, 2013, doi: 10.1016/j.jretconser.2013.01.003.
R. Chandrashekaran and R. Suri, “Effects of gender and price knowledge on offer evaluation and channel transition in retail and e-tail environments,” J. Prod. Brand Manag., vol. 21, no. 3, pp. 215–225, 2012, doi: 10.1108/10610421211228838.
A. Hübner, F. Schäfer, and K. N. Schaal, “Maximizing Profit via Assortment and Shelf-Space Optimization for Two-Dimensional Shelves,” Prod. Oper. Manag., vol. 29, no. 3, pp. 547–570, 2020, doi: 10.1111/poms.13111.
I. Štulec, K. Petljak, and A. Kukor, “The Role of Store Layout and Visual Merchandising in Food Retailing The synchronized swimming club Medveščak,” Eur. J. Econ. Bus. Stud., vol. 2, no. 1, pp. 139–152, 2016.
H. Kauppinen-Räisänen, “Strategic Use of Colour in Brand Packaging,” Packag. Technol. Sci., vol. 27, no. 8, pp. 663–676, 2014, doi: 10.1002/pts.
X. Drèze, S. J. Hoch, and M. E. Purk, “Shelf management and space elasticity,” J. Retail., vol. 70, no. 4, pp. 301–326, 1994, doi: 10.1016/0022-4359(94)90002-7
.
B. S. Wijaya, M. S. Shihab, S. A. Wijaya, D. Rudianto, and A. Sugandi, “In-Store Brand Communication: When Shelf-Space and Display Seduce Consumers,” Humanit. Soc. Sci. Rev., vol. 8, no. 4, pp. 984–998, 2020, doi: 10.18510/hssr.2020.8495.
DOI: https://doi.org/10.47738/jads.v6i1.375
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