Data-Driven SEO Strategy Optimization to Enhance MSME Sales Performance on Indonesian E-Commerce Platforms
DOI:
https://doi.org/10.47738/ijiis.v8i3.262Keywords:
Digital Marketing, Search Engine Optimization (SEO), Data Analytics, MSME, E-Commerce, Indonesia, Ensemble Regression, Random Forest, Gradient BoostingAbstract
The rapid growth of digital commerce in Indonesia has created both opportunities and challenges for Micro, Small, and Medium Enterprises (MSMEs) seeking to increase their online visibility and sales. This study presents a data-driven approach to Search Engine Optimization (SEO) strategy optimization aimed at enhancing MSME sales performance on leading Indonesian e-commerce platforms, including Tokopedia and Shopee. Using a quantitative design, the research integrates Microsoft Excel for preliminary data exploration and Google Colab (Python) for advanced analysis and predictive modeling. The dataset, comprising over 1,000 transaction entries, includes key SEO-related indicators such as keyword rank, website traffic, backlinks, social media engagement score, advertising spend, and monthly sales. Ensemble regression models—Random Forest and Gradient Boosting—were employed to evaluate the predictive relationship between SEO factors and sales outcomes, validated through RMSE and R² metrics. The findings indicate that advertising expenditure (r = +0.83), backlinks (+0.29), and social media engagement (+0.25) are the most influential predictors of sales performance, while website traffic shows a weaker positive correlation (+0.13). These results highlight the critical role of integrated SEO and digital advertising strategies in improving MSME competitiveness. The study demonstrates that accessible analytical tools can empower MSMEs to make data-driven marketing decisions. Future research should expand model generalization across industries and explore additional digital variables to improve predictive accuracy.References
Chaffey, D., & Ellis-Chadwick, F. (2019). Digital Marketing (7th ed.). Pearson Education Limited.
Kotler, P., & Keller, K. L. (2016). Marketing Management (15th ed.). Pearson.
Fishkin, R., & Høgenhaven, T. (2015). Inbound Marketing and SEO: Insights from the Moz Blog. Wiley.
Moz. (2023). SEO Learning Center. Retrieved from: https://moz.com/learn/seo
Google Search Central. (2023). Search Engine Optimization (SEO) Starter Guide. Retrieved from: https://developers.google.com/search/docs
Ministry of Cooperatives and SMEs of the Republic of Indonesia. (2023). Transformation Annual Report
Digital MSMEs. Jakarta: Ministry of Cooperatives and SMEs.
Statista. (2024). E-commerce in Indonesia – Statistics & Facts. Retrieved from:
https://www.statista.com/
Rahmawati, I., Anugrah, P., & Setyawan, D. (2020). The influence of SEO on
Increase in MSME Website Traffic. Journal of Technology and Business, 11(2), 120–128.
Suhendra, R., Utami, T. D., & Latifah, F. (2022). SEO and Social Media Synergy
in MSME Digital Marketing. Journal of E-Business and Management, 5(1), 35–42.
Nugroho, M., & Kartika, A. (2023). Optimizing MSME Product Sales in
Marketplace Through SEO Strategy. Journal of Digital Economy, 4(1), 45–54.
Hastie, T., Tibshirani, R., & Friedman, J. (2017). The Elements of Statistical
Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer.
Astuti, A., Lestari, R., & Saputra, A. (2021). E-Commerce Sales Predictions
Using Gradient Boosting. Journal of Computer Technology and Science, 3(4), 88–95.
Patel, N. (2023). SEO Unlocked: Free SEO Training Course. Retrieved from:
https://neilpatel.com/seo-unlocked/
SEMrush. (2024). E-commerce SEO Guide: How to Increase Online Store
Traffic. Retrieved from: https://www.semrush.com/blog/ecommerce-seo/
Ahrefs. (2023). Beginner’s Guide to SEO. Retrieved from:
https://ahrefs.com/seo.
HubSpot. (2022). What is SEO? Learn SEO in 2022. Retrieved from:
https://blog.hubspot.com/marketing/what-is-seo.
Ghozali, I. (2018). Multivariate Analysis Applications with IBM SPSS 25
Program
(9th ed.). Semarang: Publishing Agency of Diponegoro University.
Sugiyono. (2022). Quantitative, Qualitative, and R&D Research Methods.
Bandung: Alphabet.
Widyastuti, R. & Hartati, I. (2022). Digital Marketing Strategies for MSMEs
in Facing the Industrial Era 4.0. Journal of Business Transformation, 6(2), 22–30.
Syahputra, F. (2023). The Role of Google Colab in Improving Data Literacy
MSMEs. Journal of Informatics and Business Data, 7(1), 15–24.
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