Search

    AI-Driven Customer Value Management

    Duration: 240 minutes Hosts: Artur Machno, Data Scientist/Senior Consultant, DS & AI Practice Team This session is offered as a scheduled group session with our expert.
    Ask for available time slots
    AI-Driven Customer Value Management-1
    AI-Driven Customer Value Management-2

    What to expect

    This course is designed to teach you how to utilize artificial intelligence (AI) and machine learning (ML) to improve customer value management (CVM) strategies. It will cover topics such as product recommendation engines, propensity to buy models, customer value models, churn prediction, and cross-selling and upselling techniques. You will gain a comprehensive understanding of how AI can be used to analyze customer data, predict behavior, and optimize marketing and customer service efforts to increase customer value and loyalty.

    Challenges of CVM Without AI and ML

    Personalized Engagement

    Maximized Customer Value

    Reduced Churn

    See how customer value is managed without the use of AI and ML tools.

    Learn how to use ML to segment customers and make personalized recommendations to increase engagement and loyalty.

    Discover how to use value models to improve marketing and sales and identify opportunities for cross-selling and upselling.

    Learn how to utilize churn models to prevent customer churn, leading to increased retention and revenue growth.

    Challenges of CVM Without AI and ML

    Personalized Engagement

    See how customer value is managed without the use of AI and ML tools.

    Learn how to use ML to segment customers and make personalized recommendations to increase engagement and loyalty.

    Maximized Customer Value

    Reduced Churn

    Discover how to use value models to improve marketing and sales and identify opportunities for cross-selling and upselling.

    Learn how to utilize churn models to prevent customer churn, leading to increased retention and revenue growth.

    Challenges of CVM Without AI and ML

    See how customer value is managed without the use of AI and ML tools.

    Personalized Engagement

    Learn how to use ML to segment customers and make personalized recommendations to increase engagement and loyalty.

    Maximized Customer Value

    Discover how to use value models to improve marketing and sales and identify opportunities for cross-selling and upselling.

    Reduced Churn

    Learn how to utilize churn models to prevent customer churn, leading to increased retention and revenue growth.

    Machno
    Machno

    About Our Speaker

    Artur Machno holds over a decade of experience in data science, applying his expertise in a range of sectors such as banking, gambling, and FMCG. He has a doctorate in quantitative finance, reflecting his deep interest in the application of quantitative methods. As an assistant professor, Artur combines teaching and research at AGH University, bridging the gap between theory and practice.

    Ask for available time slots

    Fill in and submit this form to signify your interest. Within two days of registering, a representative will reach out to you to discuss your team’s knowledge needs and provide available time slots for you to choose from.
     

    Related Topics

    AI_ What Is AI Hiding From You_

    XAI: What Is AI Hiding From You?

    This presentation will begin with an overview of the methods for explaining black-box machine learning (ML) models. It will then...

     Read more about XAI: What Is AI Hiding From You?

    Spectral Methods_ Concepts and Applications

    Spectral Methods: Concepts and Applications

    They say time reveals all things — but what they don’t say is that we also need to use the proper methods to obtain most of time’s...

     Read more about Spectral Methods: Concepts and Applications

    Data Augmentation via Mixing Images

    Data Augmentation via Mixing Images

    This presentation covers recent advances in data augmentation via mixing images for computer vision. You’ll gain a deeper...

     Read more about Data Augmentation via Mixing Images