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Internet Service Providers (ISPs)
today are surviving not thriving. The average number of internet-connected devices in the home has increased over threefold in the last decade. TVs, laptops, smartphones, tablet computers, and game consoles are all competing for limited bandwidth in the home putting an increasing load on gateways and other equipment provided by the ISP. This poses a serious operational challenge for ISPs in a highly competitive price-sensitive market. Furthermore, ISPs are fielding more service calls than ever related to third-party OTT services and home devices, including many poorly designed and unsecured IoT devices, further eroding margins.

For ISPs, competition is fierce, and significant subscriber growth, both in terms of number and revenue, is hard to achieve. Therefore, attacking operational efficiency to expand margins and improve customer satisfaction to reduce customer churn is a great solution.

One of the big areas of expense that operators are targeting are service calls and truck rolls, with related callbacks and No Trouble Found (NTF) device swaps, related to onboarding, core network, home network, and device issues. It is estimated that an average large ISP incurs operating expenses of ~2% of revenues related to service calls, truck rolls, device swaps, and customer support. This is a significant burden and is growing each year. Further analysis reveals that nearly 40% of the calls are related to categories such as Wi-Fi, authorization, slow browse, and device firmware issues that have known patterns and can be proactively uncovered and predicted, with the right use of data management and machine learning algorithms. This ability to analyze large amounts of Customer Premise Equipment (CPE) parameters and network data combined with customer call center integrations, and device management capabilities for real-time updates are a powerful combination that is generating real business outcomes.

Looking at most ISPs, what we see is that the data to make decisions exists, and the systems and processes to drive business value are mostly in place. So, the question is why are so many ISPs providing a sub-optimal product support & service experience? The answer is that driving value from a wide range of data sources is complex. It is more than just implementing data science or just following the right processes and integrations. It takes four streams working in concert:

  1. Technology: Processing the amount of data that comes from home networks, CPE devices, core network elements, call centers, technicians, etc. in a timely manner to make it worthwhile is a complex software engineering and DevOps task
  2. Domain Expertise: This data needs to be crossed with individuals who deeply understand all the relevant domains, including experience with the core ISP network, the call center, and home networking.
  3. Data Science: This is a data science problem and you need skills that you find in world-class data scientists to continue to ask the domain experts the right questions and drive higher-resolution information from the data.
  4. Remediation Implementation: This is effectively a different set of domain expertise with the ability to make changes in an industry that is historically resistive to change. Specifically, you need to engage optimal actions based on guidance provided by an AI solution which could involve initiating a reboot, adding an IVR ambush, changing a call center flow, etc.

As an example, Ayla Networks is working with a tier 1 ISP that expects to save more than $75M annually in support-related expenses through the use of device data analysis and data science learning models managed through Ayla’s cloud-based TransformAI solution. This high-value use case is only scratching the surface and can potentially add nearly a full percentage point in operating margins.

Starting with a cost-savings mindset, has related benefits, such as improving the overall end-user experience through early detection and resolution of QoS problems, which in turn reduces customer churn rates. It also becomes a competitive advantage that can draw new subscribers, driving growth in the long run. And internally within the ISP, it drives a virtuous cycle of product quality improvement, low unit replacement rates, and higher business agility.

The digital transformation of the ISP is long overdue, yet the maturity of IoT and ML technology has only just reached an optimal point to justify the business case for investment. Ayla Networks is pioneering the initiative to take ISPs to the next generation of IoT & ML-led operational excellence. To learn more about Ayla IoT and the partnerships with ISPs check out our solution brief, infographic, personalized content journey, or contact info@aylanetworks.com.