Which industries are leading the implementation of process mining, and which are lagging behind? In which business processes is process mining actively used, and where has it yet to be implemented? This...
Webinar: Automated Recommender Systems with Megaladata


Date and Time: 3/3/2025 7:00 p.m. (Mexico City)
Meeting Format: Online (via Google Meet)
Meeting Format: Online (via Google Meet)
Overview: Discover how automated recommender systems can revolutionise customer experiences and drive business profitability. In this webinar, we’ll explore two key approaches for creating recommendation models using Megaladata:
- Recommendations in Digital Marketing: Learn how personalised recommendation engines can boost conversion rates, enhance customer engagement, and refine marketing strategies through the power of AI models and data analysis.
- Recommendations in Unit Economics for Online Stores: Explore how to optimise pricing, manage stock levels, and implement demand-driven sales strategies. Gain valuable insights into understanding customer behaviour and maximising profits in a digital marketplace.
What You’ll Learn:
- How data-driven recommender systems function
- Implementation of digital marketing and price optimisation models in Megaladata
- Real-world use cases and practical examples in e-commerce and CRM
- The advantages of personalization and automation using low-code AI platforms
Speakers:
Daniel Núñez, Data Scientist at Neural Factory
Samvel Arustamov, Project Manager at Megaladata
Language: English
Register now to discover the best route to personalization and profitability with AI and Megaladata!
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About Megaladata
Megaladata is a low code platform for advanced analytics
A solution for a wide range of business problems that require processing large volumes of data, implementing complex logic, and applying machine learning methods.
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