CVM Essentials, Personalization, Pricing, and Data Analysis

Welcome to another insightful episode of CVM Stories! In this episode, we had the pleasure of interviewing Ignas Brazdauskas, a Telco industry expert with a 12-year background in Lithuania and Qatar. Ignas shares insights on Customer Value Management, the role of data analysis, and its impact on the telecom industry.

In this episode you’ll learn about:

• Factors influencing customer choices and the importance of delivering value.
• Challenges in changing prices and the impact on customer decisions.
• The role of CVM in the company’s Profit and Loss Statement (PNL).
• The need for increased attention and recognition of CVM in the telecom sector.
• Strategies encompassed within CVM, including pricing, product, and distribution.
• Effective team structure for implementing CVM, including roles and responsibilities.
• The importance of data analysis and insights in CVM.
• Leveraging customer data for business growth and retention.
• The perpetual nature of CVM, involving data models and automation.
• Ignas’s career journey from data analyst to specializing in customer retention and analytics.
• Collaboration, trust, and teamwork in CVM success.
• Recommendations for data analysts and measuring the impact of CVM initiatives.
• Challenges in applying CVM strategies in traditional marketing channels.
• Ignas’ proudest moments and the value of collaboration with exceptional colleagues.

Ignas emphasizes that customers make choices based on perceived value and the importance of delivering value with precision and speed. He also highlights the challenge of changing prices, which are often the quickest factor customers consider.

Discussing the unique challenges and opportunities in the telecom sector, Ignas believes that CVM deserves more attention. He explains how CVM directly impacts a company’s Profit and Loss Statement (PNL).

Delving into the intricacies of CVM, Ignas advocates for a data-driven approach focused on customer upselling, retention, and acquisition. He emphasizes that CVM encompasses price, product, and distribution strategies.

To implement CVM effectively, Ignas suggests structuring the team with a data analyst, campaign manager, and strategist. He also recommends incorporating daily operations and an IT-focused role for automation and collaboration.

Ignas highlights the perpetual nature of CVM, involving constant refinement of data models and automation. Drawing from his personal journey, he emphasizes the potential of leveraging customer data for business growth.

Collaboration and teamwork are essential in CVM, combining creativity and data analysis. Ignas offers recommendations for data analysts, such as understanding customer behavior and making data-driven forecasts.

Measuring the impact and effectiveness of CVM initiatives is crucial, and Ignas cautions against applying CVM strategies in traditional marketing channels. Aligning behaviors with desired outcomes is key.