Harness the Power of AI to Revolutionize Your MVNO
By Danielle Rios Royston, CEO of TelcoDR and Acting CEO of Totogi
There is a well-known story in the United States about a Major League Baseball team based in California, the Oakland Athletics. In 2002, it had one of the lowest payrolls in the sport and a squad full of rookies and veteran players at the end of their careers.
The team’s ability to compete was in question, but then-General Manager Billy Beane stepped up with a fresh idea. Instead of chasing expensive star players with his limited budget, he decided to use DATA to find top performers flying under the radar. The move was so successful that it was chronicled in the book Moneyball: The Art of Winning an Unfair Game and a movie by the same name starring Brad Pitt and Jonah Hill. By using data to get a leg up on his competition, Billy Beane changed the game of baseball forever.
Today’s MVNOs are looking at a similar moneyball opportunity in the world of telco. Historically, their network provider’s legacy, on-premise tech stack kept them from getting killer ideas to market quickly and hampered their efforts to differentiate beyond simply reselling network access. With razor-thin margins, they lacked resources to develop unique offerings or advanced technical capabilities. This meant that MVNO customers often ended up with “me too” rate plans and undifferentiated customer experiences.
But thanks to the power of the public cloud, artificial intelligence (AI) and machine learning (ML), MVNOs can now turn the tables and use DATA to build subscriber loyalty, reduce churn, and uncover new revenue streams.
To do this, MVNOs have to cozy up to the public cloud and embrace the real magic: using AI and ML to design tailored plans for individual subscribers.
The Opportunity
Everyone in telco is familiar with charging platforms, but the mistake people make is thinking they’re limited to the outdated chargers offered by old-school charging vendors. There are new charging solutions, like Charging-as-a-Service and Plan AI products from Totogi (where I’m acting CEO) that use AI and the public cloud to learn from subscribers’ choices, gather rich insights, and use this knowledge to enhance the subscriber experience for everybody.
Totogi’s carrier-grade, Software-as-a-Service (SaaS) products don’t just record transactions in a database so they can be sent down the line to a billing system. Instead, they collect highly-structured charging data that ML models can turn into rich insights that can be used to find new subscribers, stop churn, and grow ARPU.
The One-Model Approach
A common mistake MVNOs make when adopting AI/ML is building customized models trained solely on their limited data sets. But leveraging AI successfully requires massive quantities of high-quality, structured data for model development. It also demands extensive compute power and data science expertise for ongoing enhancements—resources most MVNOs lack.
Totogi’s approach overcomes these barriers. Instead of using separate models for each customer, Totogi has developed a single AI/ML model trained on aggregated charging data from its global customer base. This single model builds on exponentially more data than any one MVNO could collect itself, and with continual tuning by Totogi's team of data scientists, it maintains cutting-edge accuracy and applicability.
It's all about data. Totogi uses a one-model approach because training an ML model requires a quantity of data and diverse data. Training only on an MVNO’s own data runs the risk of generating too many false positives by using data that’s overly similar. In addition, data needs to be well-structured and in the same format. This is difficult for many traditional vendors to achieve because their customers’ data is spread wide, some on premise, some in the cloud, in different schemas, and on different platforms and versions.
Chips and more chips. Totogi has gone ALL-IN on the public cloud. Some people still don’t understand why this is a huge advantage, but every year it becomes more clear: when you’re on the public cloud, it’s easy to use other public cloud assets, such as the AI chips needed to bring costs down while training an ML model. Thanks to AWS’ investment in Trainium and Inferentia, Totogi uses those chips whenever it needs to. Legacy on-prem vendors can’t do this, and it has become increasingly difficult to buy the sold-out $100,000 Nvidia servers needed to train an ML model on premise.
Constant improvement. ML models need trained data scientists to tweak and update them continually. By working with a vendor like Totogi, MVNOs get access to this expensive care and feeding without having to pay hundreds of thousands of dollars for it. Even better, working with one data model allows Totogi to focus on ongoing improvement, with the sole goal of optimizing overall performance.
The advantages of this one-model approach for MVNOs are obvious:
Supports MVNO focus on utilizing insights instead of model development
Provides data science expertise and resources without having to hiring talent
Saves significant time and costs
Speeds return on investment
Compare this approach to other vendors that say they are adding AI and ML to their charging products and promise to build you a customized model. These companies are creating models for each customer, running only on their own data. This one-model-per-customer approach is laden with hidden costs, operational missteps, and a perpetual game of catch-up with evolving ML technologies. But most importantly, it doesn’t provide for enough charging data to unlock the game-changing competitive advantages of a robust ML model—something that is especially important for MVNOs.
Everyone’s Favorite Question
MVNOs considering Totogi’s solutions often ask the same question: “If we all use the same model, where is the differentiation?” It’s a valid query given that MVNOs compete in a crowded marketplace. Yet, Totogi's one-model approach is actually what opens the door to the differentiation MVNOs seek. It provides actionable insights that they can use to set themselves apart from competitors. They could never uncover these insights using only their limited data.
The key to successful differentiation lies in using the model-driven insights effectively. Armed with exceptional suggestions to drive revenue and reduce churn, an MVNO’s team still needs to get them into the market, and every team will do that differently. I’ve seen organizations hesitate, doubt, and just plain stop because they are afraid of what could happen, and I’ve also seen organizations run and see amazing results.
It’s important to remember that models alone don’t create impact. Fortune favors the bold, and MVNOs that utilize the insights with speed and effectiveness will gain the competitive advantage. This will be what drives successful differentiation.
Time to Moneyball
Around the world, big operators are investing heavily in AI to revolutionize their businesses. The good news is that MVNOs don’t need big bucks to jump on this bandwagon. With options like Totogi that are purpose-built to serve them, MVNOs of any age and size can use the public cloud, AI, and ML to streamline plan creation, strengthen marketing campaigns, predict churn, and identify new revenue streams.
Disruptive SaaS platforms offer a wealth of options to help MVNOs punch above their weight. Rather than waiting years for transformative capabilities to trickle down through the telco hierarchy, today’s MVNOs can tap turn-key solutions to rapidly deliver the kind of distinctive customer experiences that even large operators are still only beginning to explore.
With the power of the public cloud and AI behind them, MVNOs are poised to shape the next era of human connectivity. The time for telco moneyball is now. Are you ready?
About the author
Danielle Rios Royston,
CEO of TelcoDR and Acting CEO of Totogi
Danielle Rios Royston is Founder and CEO of TelcoDR and the acting CEO of Totogi. She has 25 years of enterprise software experience – the last 10+ as a CEO specializing in turnarounds. As telecom’s leading public cloud evangelist, Danielle has raised $1Billion to fundamentally transform telco software, propelling the industry to new heights with the power of the public cloud. Widely recognized as a thought leader, Danielle has been asked to speak on some of the biggest stages in the industry and featured in numerous publications. She resides in Austin, TX, and holds a B.S. in computer science from Stanford University.