How MVNOs Can Use AI Automation
for Smarter Business Operations

By: Bernhard Kraft

Telcos are sitting on a data gold mine, and it grows larger and richer every moment of every day, driven by billions of network events. Customer data, which charts real-time behaviors and preferences, can help mobile virtual network operators (MVNOs) identify high-value customers, predict customer churn, pinpoint new market opportunities, and improve the operational running of their networks. What’s less well-understood is how to tap into, and monetize, this treasure trove of data. That’s where the interplay between business support systems (BSS) and AI comes into play. But what does this relationship look like?

For many years, telcos have lost valuable ground to digitally native tech giants and seen their profit margins and ROI dwindle. They face a stark dilemma to either “tinker around the edges to achieve incremental gains or make a bold choice to reinvent their value-creation formula.” (McKinsey) Advanced AI, with its ability to access, integrate, and analyze vast volumes of data in real-time, has the potential to supercharge the path to value creation and transform the business operations of MVNOs. However, legacy systems, and to a certain degree “legacy thinking,” have hampered transformation efforts to date.

That is now changing. The rate at which telcos are embracing digital evolution is accelerating, and increasing numbers are now successfully accessing, analyzing, and leveraging their BSS data to train and power artificial intelligence.

How AI is Transforming Telco Business Operations

Artificial intelligence is built on continuously updated machine learning (ML) algorithms, large language models (LLMs), natural language processing (NLP), and proactive, automated actions. All of this begins with the vast amount of BSS data and the ability to analyze in real-time and automate personalized customer outreach. Generative AI models that harness LLMs and NLP, based on continuous training powered by BSS data, are making chatbots more sophisticated, dynamic, and capable of successfully handling complex customer service interactions. For instance, revenue and cost prediction models that are powered by real-time BSS usage data can help MVNOs deliver more compelling offers, maximize existing investments, and provide better customer experiences. This seamless automation and process re-engineering results in efficiencies with wide-ranging impacts, from fraud detection and prevention to sales and lead management. The potential impacts of AI-powered BSS data might be wide-ranging, but the technology is still under-utilized. Three of the surest paths to rapid value creation are outlined below.

1. Self-care: A win-win for customers and MVNOs

Consumer feedback consistently reveals overwhelmingly positive attitudes to self-service when done well. Three-quarters of survey respondents saw self-service as a convenient way of addressing customer service issues, while two-thirds actually preferred it to talking to a company representative.

Getting self-service right isn’t just good for customers, it’s also an attractive deal for MVNOs, who can expect to reduce waiting times, lower call volumes and customer service costs, increase sales, and improve customer satisfaction. With intelligent BSS-powered analytics and real-time integration with advanced, generative AI platforms, pioneering MVNOs are increasingly able to offer customers solutions that are personalized and highly contextual, as well as identify new cross- and up-selling opportunities. Guinea Mobile in Peru, for example, has used a highly flexible, cloud-based BSS solution that seamlessly integrates with AI tools that streamline its onboarding process for new customers down to just four clicks.

2. Tailored offers and optimized products

Real-time analytics that evaluate behaviors and usage patterns reveal what’s really happening on the networks. Using market segmentation analysis, MVNOs can harness these insights to better bundle products and offers tailored to the needs of that specific segment. For example, MVNOs can identify dual SIM usage and customize offers against those usage patterns. One MVNO in Africa was able to improve offer uptake significantly by regionalizing it based on 30 geographic locations. Meanwhile, other MVNOs are broadening the bundling techniques they offer based on their customers’


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