The huge amount of data we produce and consume is exploding around the world at an unprecedented rate. The data growth analysis shows that most of today’s global data was generated in the past two years. On average, every person created at least 1.7 MB of data per second in 2020. The world’s population is projected to generate 463 exabytes of data per day by 2025. Ubiquitous smartphone adoption and ever-increasing consumer dependence on mobile devices are the major growth drivers, with mobile data volumes predicted to increase tenfold over the next five years.
As mobile users create billions of touchpoints every day, high quality and, in many cases, actionable data points flow through each operator’s network. However, according to Forbes, less than 0.5 percent of this data traffic is properly analyzed in order to achieve additional added value, a major reason for this being the unmanageable weight of the data traffic involved. For example, on a typical network in South America, there will be around two billion data events every day. The profitable analysis of these data points to gain customer insights has so far proven to be an insurmountable technical and operational challenge.
Enter AI and ML: cost-effective data insights
In the past, operators mainly marketed their customers through traditional campaign lines with non-personalized bulk SMS offers to buy top-up or airtime packages, which may have been sent once a month. Typically, the conversion rates for such campaigns are less than one percent. Data visualization offers the opportunity to completely change the operators’ understanding of customer behavior and buying patterns. The huge volume of data that users are generating on their mobile devices today, combined with new AI and machine learning-led capabilities in data analytics, means that operators can now gain more insight than ever before into what customers are doing, what their needs are, and when is the optimal moment to get in touch with them. This new ability to microsegment and micro-market to customers based on real-time requirements—whether for top-up, small loans, or Mobile wallet loans or transactions – can generate conversion rates of up to 10 percent, which is more than ten fold increase in marketing success for operators and a significantly improved user experience for mobile customers.
The technological breakthrough in the ability for operators to visualize these billions of customer touchpoints every day has been cloud-based machine learning and artificial intelligence, which provide the ability to manage, process, and analyze data much more cheaply than before. Machine learning and AI offer the processing capability to find highly targeted “needle in a haystack” data at cost levels that make economic sense for operators. The key to unlocking the potential of data has always been whether it can be processed at a profitable cost, and AI and ML are finally delivering the elasticity that will make operators’ big data ambitions a reality. For example, to study a 50 million customer base, the cost of analyzing all of the customer records generated and delivering actionable results can now be as high as € 1,0002,000 per day, which is an attractive business model from an operator perspective.
Know your customer: right offer, perfect time
Which datasets can be analyzed and how can they be monetized to increase operator revenues and better meet customer needs? It all depends on the granularity and real-time analysis of what the customer is doing in that moment. All networks offer a number of static data points, such as what phone a customer is using, their typical data outputs, and more standard CRM. However, the ability to aggregate real-time data about a customer’s interaction with their device provides the ability to spot patterns and create segmentation that can lay the foundation for many more effective marketing campaigns and create happier, more loyal customers.
A data event is generated every time a phone tries to connect to the carrier’s network, check email, upload a TikTok video, or view sports scores. Operators can look for general patterns at these events in order to deliver timely offers that could be better tailored to potential areas of interest such as football, games, business, etc. For example, if the soccer World Cup tournament is running and data usage could be higher, Carrier Prepaid customers with very low data credit could offer a short-term data package that the customer can stay connected to. With five billion prepaid customers worldwide, each busy with running out of data or airtime in a continuous natural lifecycle, the ability for operators to offer instant top-ups, product packages or even small loans to ensure continuous connectivity is a huge advantage for both the customer and the service provider.
