Predictive analytics for marketing (Synchronous e-learning)
Training Provider: NATIONAL UNIVERSITY OF SINGAPORE
Course Reference: TGS-2020501990
S$570
Original: S$1,900
Save S$1,330
About This Course
1. Grasp the significance and potential of predictive analytics in shaping modern marketing strategies.
2. Harness the power of AI to predict future marketing trends, ensuring businesses stay ahead of the curve.
3. Discover the tools and techniques to predict potential customer churn, enabling the development of strategies to retain valuable clients.
4. Learn how to segment customers using machine learning algorithms, allowing for more precise and effective marketing campaigns.
5. Dive deep into text analytics to extract actionable insights from customer feedback, enhancing customer satisfaction.
What You'll Learn
This 2-day intensive course delves deep into the application of predictive analytics and machine learning to solve marketing challenges. Participants will gain hands-on experience in using advanced algorithms and tools, empowering them to make data-driven marketing decisions.
Day 1: Begins with a foundational understanding of predictive analytics, moving into marketing forecasting, churn prediction and retention strategies.
Day 2: Concentrates on customer segmentation, target marketing strategies, and customer feedback analytics.
Throughout both days, participants will engage in a blend of theoretical learning and practical exercises, ensuring they're equipped with both knowledge and hands-on experience.
Day 1: Begins with a foundational understanding of predictive analytics, moving into marketing forecasting, churn prediction and retention strategies.
Day 2: Concentrates on customer segmentation, target marketing strategies, and customer feedback analytics.
Throughout both days, participants will engage in a blend of theoretical learning and practical exercises, ensuring they're equipped with both knowledge and hands-on experience.
Entry Requirements
Basic knowledge of marketing principles and a familiarity with data analytics will be beneficial, though not strictly necessary.
Course Details
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