Trendyol Group Highlights Strategic Use of Data Science and Analytics to Support Scalable Growth

Trendyol Group has shared an update.

The company highlighted its approach to data science and analytics, emphasizing the importance of selecting the appropriate methods—from regression and tree-based models such as XGBoost to deep learning and large language model (LLM) architectures—based on the specific business problem. The post notes that in some cases, machine learning is not necessary and that heuristics, rules, or traditional analysis can be more effective. Trendyol promoted a live broadcast and a recorded meetup focused on current analytics trends and real-world problem solving.

For investors, this communication underscores Trendyol’s continued investment in advanced data capabilities and disciplined model selection, which are critical for optimizing logistics, personalization, pricing, and risk management in large-scale e-commerce operations. A mature analytics culture that integrates data science with business understanding can improve decision quality, operational efficiency, and customer experience, potentially supporting revenue growth and margin expansion over time. While the post itself does not disclose new financial metrics or concrete product launches, it signals that Trendyol is actively developing and sharing analytics expertise, which may help sustain its competitive position in a data-intensive industry and attract analytics talent needed for scalable growth.