A Novel Sales Promotional Schemes based on Clustering and Linear Regression Analysis

A Novel Sales Promotional Schemes based on Clustering and Linear Regression Analysis
  IJETT-book-cover           
  
© 2024 by IJETT Journal
Volume-72 Issue-4
Year of Publication : 2024
Author : Atul O. Thakare, Soora Narasimha Reddy, Omprakash W. Tembhurne, Parag S. Deshpande
DOI : 10.14445/22315381/IJETT-V72I4P121

How to Cite?

Atul O. Thakare, Soora Narasimha Reddy, Omprakash W. Tembhurne, Parag S. Deshpande, "A Novel Sales Promotional Schemes based on Clustering and Linear Regression Analysis," International Journal of Engineering Trends and Technology, vol. 72, no. 4, pp. 199-208, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I4P121

Abstract
Different sales promotion schemes are used to promote sales among customers. Depending upon the sales promotion mix, the response of customers changes. One of the most common sales promotion schemes is an advertisement. For example, customers of mid-age may respond more positively to an advertisement in the newspaper than an advertisement on social media. Generally, the relationship between dependent (sales) and independent variables (television advertisement, newspaper advertisement, social media advertisement) is inferred using regression techniques. However, suppose the number of customers is from different groups. In that case, one generalized equation may not represent the relationship accurately due to various groups in data because one single line may not fit the data well. In the proposed work, we present an algorithm for grouping customers having similar dependency relationships and then extracting such relationships for each group. The dependency relationship is extracted by using regression and the accuracy is measured using Mean Square Error (MSE). Experimentation on standard and synthetic datasets proves that the proposed method enhances accuracy to a very large extent and it will be practically applicable to extract more strategic information from the dataset.

Keywords
Regression, MSE, R-square, Clustering, Segmented Regression.

References
[1] Peter Duchessi, and Eitel J.M. Lauría, “Decision Tree Models for Profiling Ski Resorts’ Promotional and Advertising Strategies and the Impact on Sales,” Expert Systems with Applications, vol. 40, no. 15, pp. 5822–5829, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Sridhar Ramaswamy, Rajeev Rastogi, and Kyuseok Shim, “Efficient Algorithms for Mining Outliers from Large Data Sets,” Proceedings of the ACM SIGMOD International Conference on Management of Data, pp. 427-438, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Sergios Theodoridis et al., Introduction to Pattern Recognition: A Matlab Approach, Academic Press, 2010.
[Google Scholar] [Publisher Link]
[4] Rui Xu, and Donald Wunsch, “Survey of Clustering Algorithms,” IEEE Transactions on Neural Networks, vol. 16, no. 3, pp. 645-678, 2005.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Kristina P. Sinaga, and Miin-Shen Yang, “Unsupervised K-means Clustering Algorithm,” IEEE Access, vol. 8, pp. 80716-80727, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[6] Ki Hyun Kim, and Jun Geol Baek, “A Prediction of Chip Quality using OPTICS (Ordering Points to Identify the Clustering Structure)- Based Feature Extraction at the Cell Level,” Journal of Korean Institute of Industrial Engineers, vol. 40, no. 3, pp. 257-266, 2014.
[CrossRef] [Google Scholar] [Publisher Link]
[7] Michael Steinbach, George Karypis, and Vipin Kumar, “A Comparison of Document Clustering Techniques,” Technical Reports, Department of Computer Science and Engineering, University of Minnesota, 2000.
[Google Scholar] [Publisher Link]
[8] Ana L.N. Fred, and Anil K. Jain, “Data Clustering using Evidence Accumulation,” International Conference on Pattern Recognition, IEEE, Quebec City, QC, Canada, vol. 4, pp. 276-280. 2002.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Pavel Berkhin, “A Survey of Clustering Data Mining Techniques,” Grouping Multidimensional Data: Recent Advances in Clustering, Berlin, Heidelberg: Springer Berlin Heidelberg, pp. 25-71, 2006.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Alaa Tharwat, “Parameter Investigation of Support Vector Machine Classifier with Kernel Functions,” Knowledge and Information Systems, vol. 61, pp. 1269-1302, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Manuel Fernández-Delgado et al., “An Extensive Experimental Survey of Regression Methods,” Neural Networks, vol. 111, pp. 11-34, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Sarah Mussol, Philippe Aurier, and Gilles Séré de Lanauze, “Developing In-Store Brand Strategies and Relational Expression through Sales Promotions,” Journal of Retailing and Consumer Services, vol. 47, pp. 241-250, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[13] Hao Yu et al., “Self-Paced Learning for K-Means Clustering Algorithm,” Pattern Recognition Letters, vol. 132, pp. 69-75, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Adil M. Bagirov, Arshad Mahmood, and Andrew Barton, “Prediction of Monthly Rainfall in Victoria, Australia: Clusterwise Linear Regression Approach,” Atmospheric Research, vol. 188, pp. 20-29, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Hui Jiang, Zhaosheng Feng, and Guirong Jiang, “Dynamics of an Advertising Competition Model with Sales Promotion,” Communications in Nonlinear Science and Numerical Simulation, vol. 42, pp. 37-51, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Dai, Wenseng, Yang-Yu Chuang, and Chi-Jie Lu, “A Clustering-Based Sales Forecasting Scheme Using Support Vector Regression for Computer Server,” Procedia Manufacturing, vol. 2, pp. 82-86, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Buil, Isabel, Leslie De Chernatony, and Eva Martínez. “Examining the Role of Advertising and Sales Promotions in Brand Equity Creation,” Journal of Business Research, vol. 66, no. 1, pp. 115-122, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Wendy Attaya Boland, Paul M. Connell, and Lance-Michael Erickson, “Children's Response to Sales Promotions and Their Impact on Purchase Behavior,” Journal of Consumer Psychology, vol. 22, no. 2, pp. 272-279, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Yongrui Duan, Tonghui Liu, and Zhixin Mao, “How Online Reviews and Coupons Affect Sales and Pricing: An Empirical Study Based on E-Commerce Platform,” Journal of Retailing and Consumer Services, vol. 65, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Tomáš Formánek, and Ondřej Sokol, “Location Effects: Geo-Spatial and Socio-Demographic Determinants of Sales Dynamics in Brickand-Mortar Retail Stores,” Journal of Retailing and Consumer Services, vol. 66, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Daifeng Li et al., “A Multiple Long Short-Term Model for Product Sales Forecasting based on Stage Future Vision with Prior Knowledge,” Information Sciences, vol. 625, pp. 97-124, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Hui Jiang, Zhaosheng Feng, and Guirong Jiang, “Dynamics of an Advertising Competition Model with Sales Promotion,” Communications in Nonlinear Science and Numerical Simulation, vol. 42, pp. 37-51, 2017.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Harlan E. Spotts et al., “The Role of Paid Media, Earned Media, and Sales Promotions in Driving Marcom Sales Performance in Consumer Services,” Journal of Business Research, vol. 152, pp. 387-397, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[24] Kapil Bawa, and Robert W. Shoemaker, “The Effects of a Direct Mail Coupon on Brand Choice Behavior,” Journal of Marketing Research, vol. 24, no. 4, pp. 370-376, 1987.
[CrossRef] [Google Scholar] [Publisher Link]
[25] Sunil Gupta, “Impact of Sales Promotions on When, What, and How Much to Buy,” Journal of Marketing Research, vol. 25, no. 4, pp. 342-355, 1988.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Zhilin Yang, and Robin T. Peterson, “Customer Perceived Value, Satisfaction, and Loyalty: The Role of Switching Costs,” Psychology & Marketing, vol. 21, no. 10, pp. 799-822, 2004.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Richa Agrawal, Sanjaya S. Gaur, and Archana Narayanan, “Determining Customer Loyalty: Review and Model,” The Marketing Review, vol. 12, no. 3, pp. 275-289, 2012.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Tor Wallin Andreassen, and Bodil Lindestad, “Customer Loyalty and Complex Services: The Impact of Corporate Image on Quality, Customer Satisfaction and Loyalty for Customers with Varying Degrees of Service Expertise,” International Journal of Service Industry Management, vol. 9, no. 1, pp. 7-23, 1998.
[CrossRef] [Google Scholar] [Publisher Link]