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marzo 13, 2019

Protect customer base and maximize revenues in telecoms

Eric Van Haetsdaele

Business Development Manager

Eric Van Haetsdaele has 20+ years of experience in IT and telecom companies. As Business Developer of EXFO’s Data Science & Advanced Use Cases PU (Product Unit), he is helping wireless operators use customer insights from Network to automate Operations in Technical & Marketing based on AI, while developing a better and individualized understanding of customer behavior to issue differentiated offers and monetize this data goldmine.

Prior to joining Astellia, Eric held different executive pre- and post-sell positions at Alcatel-Lucent and Nortel. Eric holds a DEA Communication Systems degree from the Paris UMLV University and a Master degree from ESIEE.

The big question facing communication service providers today is where to find real opportunities for value creation. While the pressure is on to keep the pace with the latest technical innovations (such as 5G), greater investment in customer experience management might be the key to CSPs successfully establishing themselves as market leaders in customer satisfaction. An increased emphasis on customer experience initiatives will enable operators to grow their subscriber base while minimizing churn and creating a more predictable revenue stream to fund the growth of their business. By offering compelling user experiences where every interaction is personalized, fast and user friendly, and simultaneously providing adapted bespoke offers, operators will be able to differentiate themselves from their competitors by better meeting the needs of their customers.

In this webinar, we will demonstrate how to leverage AI and machine learning to prioritize customer experience and thereby protect and generate revenue streams. To do so, we will examine several compelling use cases addressing the following topics:

  • Churn prediction – By using a unique machine learning predictive model, which works with variables from the network on top of traditional CRM variables, it is possible to identify the behaviors of customers, then act accordingly to better serve their needs and retain them.
  • Fraud prediction – Effective investigation of SIM Box fraud protects against significant financial losses and compromised quality of experience for customers.
  • Multi-SIM user identification – The ability to identify multi-SIM users gives operators the power to re-engage lapsed subscribers and therefore retain them. Increased subscriber intelligence can be used to achieve higher levels of customer loyalty.
  • Customer insight and segmentation – The best route to subscriber centers of interests is through the categorization and segmentation of web traffic to increase customer lifetime value. In addition, predictive analytics helps to increase knowledge and understanding of customer behavior so that operators can provide them with optimum offers from which they can derive the most value.