Leveraging AI to deliver a personalized experience in the new normal
In today’s world, gaming, video streaming and social sharing experiences drive consumer broadband usage in both mobile and fixed networks. These same activities are the ones which have grown the most during the global pandemic and in our “new normal,” and together sum up to 80% of Internet traffic worldwide.
Bad experiences with these applications cause consumers to switch plans or even switch their communication service provider (CSP) altogether. In fact, 50% of smartphone users will be ready to switch their provider in 12 months if they cannot enjoy immersive experiences, such as gaming, virtual travel, video capture and streaming, or smart home video detection, such as a package delivery, according to research conducted by Nokia.
Those most likely to switch are highly engaged users – such as remote workers, gamers, video streamers – who manage their lives on their smartphones. They represent a higher lifetime value to their providers than those who don’t show interest.
All these applications and services are highly experience-sensitive. Providers need to ensure their customers get the experience they are expecting based on their needs, at the right time and location, in the devices they use, and in the touch points they interact with.
How Artificial Intelligence (AI) and Machine Learning (ML) can help
It is key to understand how different subscribers perceive different experiences while gaming, attending a smart venue or traveling virtually. Each of these experiences will vary for different individuals: e.g. a man in his 30s who works from home versus a teenager who moves around the city. These experiences need to be predicted across various touch points, such as OTT game apps or smart venues, the network, call center, retail, and billing.
It is also crucial to proactively identify anomalies and factors contributing to experiences. For negative experiences, the need is to act fast and resolve issues before they impact gaming customers, for example. For positive experiences, targeting the right customers at the optimal time for an add-on purchase in a smart venue can make a huge difference in revenues. This read will tell you more about the gaming experience & the social sharing experiences in smart venues use cases.
AI and ML create the possibility to look at each subscriber based on their individual profile, including demographics, device used or mobility to predict the experience more accurately, taking into account the individual sensitivities, biases and expectations. The insights software learns with changing dynamics either in the CSP’s network, customer segment or market and adapts predictions accordingly.
Different people have different perceived experiences based on their profiles
Provide personalized, in-the-moment experiences
A holistic approach to data collection, analysis and consumption is needed to produce reliable, robust and scalable experience insights based on rich and diverse data sets. Sharing these personalized experience insights across the organization brings greater consistency between the decision-making processes, both tactical and strategic. This means having a common language across CSP functions, such as operations, care, marketing and management, and it requires open, well-governed access to data, with flexible options to consume it.
Real-time and predictive capabilities manifest insights which reflect “in-the-moment” customer experiences, instead of reactive, “after-the-fact” reporting. By leveraging AI and ML, CSPs receive priceless insights into every moment with each and every customer, in real-time, enabling them to better meet their needs before issues arise and ensure positive experiences for all customers regardless of fluctuating demands caused by the global pandemic.
