Machine learning is a supremely powerful tool being used in every industry under the sun to drive change, innovate creative solutions, and encourage better decision making and a streamlined customer or user experience in every realm. It’s all around us, whether we know it or not. Every time you open your web browser and see suggested sites, a machine has learned about your browsing habits and is attempting to streamline your user experience. Every time a takeout website like Grubhub or Caviar suggests an eatery you may enjoy, you can know that an algorithm has learned about your eating habits (and what time of day you prefer pasta or an omelet) so as to make ordering that much easier for you. The machines learn about individualist make their lives easier, but they also learn about whole markets and industries in order to make them easier to manage as well.
Many industries use machine learning and business intelligence platforms in order to streamline their workflow and operations. In fact, according to the latest Gartner Magic Quadrant Data Science report the advances being made in the realm of machine learning, business intelligence, and data analytics is truly breathtaking. With data analytics companies developing tools that provide real-time streaming data that can be used alongside historical data to provide insights into ongoing trends, and immersive visuals that make all of that information easy to digest and turn into actionable decisions, it’s an exciting time to be a market leader or technology user.
One industry that uses machine learning in startlingly advanced ways is the telecom arena. Telecom companies like AT&T, Verizon, and T-Mobile make use of machine learning and business intelligence platforms every day. These vendors work with huge amounts of data in order to keep their customers’ sensitive information safe, predict upcoming trends, and optimize prices in order to make their products relevant and accessible to large swaths of the population. Keep reading to learn about some of the key ways in which the telecom sector uses machine learning to drive and maintain their businesses on a daily basis.
Recognizing and Stopping Fraud
Telecom companies have access to a large amount of sensitive information. After all, with our phones on us at all times, having access to our phones is akin to having access to our every movement. Fake user profiles, theft, and illegal access to accounts or personal information are all ways in which fraud can impact customers of a telecom company. It should go without saying that someone who experiences fraud will not feel safe working with the vendor that allows their data or profile to be hacked. For this reason and many more, training algorithms to use data analytics in order to recognize the tiniest hint of fraud can be in the best interest both of the company and of the customer.
Predicting Customer Lifetime Value
Many ways in which we use our telecom services are not paid out immediately. In fact, most aren’t. We pay our phone bill every month, many of us pay off the cost of our devices over many months, and we pay for device insurance on a monthly basis. In order to understand how much each customer is “worth” to a company’s overall revenue, telecom companies must make use of predictive analytics and machine learning so that they can understand what their revenue is likely to be in the coming months and years. By using algorithms to crunch those numbers, telecom firms can streamline their processes and make better business decisions.
Staying Abreast of Customer Needs
The telecom sector is one in which predictive analytics can be especially useful. Customers tend to bounce around telecom services, always searching for less expensive services to meet their needs. In addition, advances in network capabilities and product design also have customers looking at other options that may meet their increasingly intricate demands. Using machine learning in order to keep track of market trends and gain insights into customer wants and needs allows telecom companies to stay ahead of the game and invest in products and services that will retain loyal customers for years to come.