The Internet of Things (IoT) offers consumers with the ability to DIY their homes and take control of all aspects of the technology in their everyday life. However smart today’s technology may be, troubleshooting is inevitable. GetCRM, a company that specializes in customer relationship management, found that 90% of customers expect a company to offer a self-service portal. In addition, Business Insider reported that 73% of consumers want to be able to solve product or service issues on their own. This is especially true for Telecoms. Machine learning offers a unique way for service providers to improve their network performance analytics while also building customer loyalty and trust.

The Science Behind Machine Learning

Most people are familiar with the idea of artificial intelligence, even if it’s just a reference to the latest sci-fi movie. AI has become a popular subject across technology, with companies rushing to adopt the technology. Machine learning is the facet of AI that allows computers to learn by themselves and perform operations without the need for human interaction. Machine learning is more than just a movie plot; it’s a real technology that is being implemented today in a variety of fields. Transparency Market Research (TMR) estimates 36.1% compound annual growth between 2016 and 2024.

Computers implement machine learning by recognizing and learning patterns. Take a classic “If/Then” scenario. If you tell your Amazon Alexa device to play “Here Comes the Sun” by the Beatles, thanks to AI and machine learning, your device recognizes the context of the command and can provide a result, in this case, playing the song. Since Amazon’s launch of the Alexa systems in 2014, the active machine learning algorithms that Alexa devices employ have allowed the device to react more naturally and significantly reduce the number of errors by 25%.

Another example of machine learning at work is through personalized ads. It’s no coincidence that after browsing online for new products, those same products seem to pop up everywhere in the form of sponsored ads.

How Machine Learning Helps Home Networks

As more consumers opt to DIY their home network environment, it becomes increasingly important for service providers to offer self-service opportunities. Machine learning answers that call. Managed Wi-Fi systems like Optim from Actiontec provide consumers with an easy to navigate dashboard that puts their entire home network at their fingertips. Optim goes beyond simply managing the devices on a network by adapting to each consumer’s unique networking needs. Machine learning technology allows Optim to drive consumer interaction and satisfaction through features such as automatic band steering, enhanced security analysis, and real-time network performance monitoring. Machine learning can produce predictions of performance or failures and work to proactively mitigate or resolve those issues, especially in the home network. These tools allow consumers to address and resolve network issues without the hassle of contacting customer service and even having to schedule an in-home service call. Machine learning influences two major areas of the home network:

1. Security – Data is often encrypted for consumer privacy and security purposes. Encrypted data makes it extremely difficult to identify malware unless the data is decrypted. Machine learning is able to easily navigate through a plethora of data to identify patterns that point to malware activity.

AI, Machine Learning, and Telecom

IoT and smart devices in the home is growing at a rapid rate and each of these devices generate. Internet service providers and telecoms are in the cross section between consumer and Internet based technology. Because of this unique position, it comes as no surprise that the telecommunications services industry is one of the fastest growing industries in the world. The revolutionary world of IoT depends on machine learning to process massive data sets more efficiently than traditional methods of data management. In addition to improved data management, telecoms that implement machine learning tools could lead to new revenue streams.

Machine learning provides telecoms with transformation opportunities based on data derived from consumer behavior, predicting their needs and wants based on data collection. Self-learning networks improve efficiency while cutting down on associated costs. ISPs who implement machine learning and offer those tools to consumers are at a competitive advantage, creating opportunities for growth and brand recognition.

As AI and machine learning continues to evolve, some telecom providers are opting to maintain and build on their current data infrastructure. Analytics firm IDC predicts that 31.5% of the telecommunication organizations are mainly focusing on utilizing current infrastructure and 63.5% are committing to investments on AI systems. With the vast amounts of data processing necessary to keep up with IoT, telecom companies will have to adapt to the demand. Machine learning is an ideal tool for the that particular area.

The Future of Machine Learning

There are five main areas where we can expect machine learning to make improvements.

5. Quantum computing

The tech industry is booming. Many of the driving factors of technology hinge on the advancement of AI and machine learning. Telecoms and Internet service providers are in the unique position to bridge the gap between AI and consumers while also capitalizing on potential growth opportunities. One thing is certain: the telecommunication industry has experienced a boost thanks to the tools provided by data science and machine learning.

Manage your WiFi with Optim

The Optim Managed WiFi Solution is a cloud-based Wi-Fi management solution for Service Providers and their End Users. Optim allows you to optimize your WiFi by providing a holistic view into the WiFi home network – automatically detecting weak WiFi signals and other underperforming network devices.

Does your Service Provider have Optim? Learn More about the Advanced Tools available for your Internet Service Provider.