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How Telecom Companies Use Machine Learning & Artificial Intelligence

Posted on the 31 May 2020 by Questnewsgroup
How Telecom Companies Use Machine learning & Artificial Intelligence

Nowadays, Artificial Intelligence (AI) and machine learning have been hyped through vendors, social media, and researchers. Innovative societies like telecommunication industries are already working towards reaping the full benefits of what these technologies can offer. In this article, we shall discuss the six remarkable ways telecom companies use machine learning and Artificial Intelligence.

1. Improving Customer Service Experience

Many telecommunication industries are relying on AI and machine learning to improve their customer service experience. They use the technologies mainly through chat-bots and virtual assistants to give quick responses to their customers. Today, machines are automated to recognize customers' texts and predict their possible problems. With AI, telecoms can identify, recognize, react and propose the correct service to their clients in a matter of seconds. The historical and personalized information of clients helps telecoms to come up with better services and products, as well as marketing ways that can attract traffic. Let's have an in-depth of virtual assistants and Chat bots.

Virtual Assistants

The role of virtual assistants is to automate and escalate appropriate responses to support requests. Support requests refer to the several customers' requests to a company to help in the processes of set up, installation, troubleshooting, or even maintenance. This mechanism not only helps to improve the customer experience but also reduces the overall business costs allocated to customer satisfaction.

Chat bots

The role of Chat bots, on the other hand, is to analyze support requests, learn how to route them, and answer the customer queries where possible. Chat bots are also able to recognize sales opportunities, relate them to similar products, and alert the consumer on the products that they may be interested in. The mechanism is automated to handle thousands of search queries within the shortest time possible and without human intervention. With machine learning and AI, the Chat bots are also able to offer voice and speech services. This, in turn, makes telecommunication industries effortlessly improve their customer service experiences.

2. Improved Network Optimization

How Telecom Companies Use Machine learning & Artificial Intelligence

An additional field where Artificial Intelligence is handy is on network optimization. Telecoms that combine their Self Organizing Network (SON) with Artificial Intelligence mechanisms can continuously familiarize and reconfigure their networks based on their existing needs. AI is also beneficial when it comes to designing networks because the new networks that are AI-enabled can be self-optimized and self-analyzed. Such are excellent options as they are efficient in offering reliable and consistent customer service experience.

3. Predictive Maintenance

The best way telecoms can meet the needs and preferences of their clients is when they avoid outages. Artificial Intelligence enables predictive maintenance, which is an essential platform to improve customer service satisfaction. With this prediction, companies get insights into the desires of their customers. These insights, in turn, help the companies to monitor their equipment and adjust appropriately according to the historical information that they have about their clients. Companies will also anticipate for equipment failure and fix it proactively.

4. Robotic Process Automation (RPA)

Telecoms are examples of companies that have large volumes of customers regularly. With such a number to be handled daily, human efforts become inferior. If the telecoms are to work with human hands, there would be human error in every step of the interaction. With Artificial Intelligence and machine learning, business processes are automated through RPA. RPA can meet the bulky request without delays. The works of robotics are monotonous and rule-based, therefore making work very efficient and accurate. According to statistics, telecoms gain substantial profit margins when they apply this tool. Therefore, RPA computing is one of the best ways of transforming a company.

5. Detecting Fraud

The algorithms of machine learning helps in recognizing fraudulent activities like illegal access, theft, fake profiles and much more. The machine learning algorithms learn what appears as ordinary activities and spots irregularities from data sets. The advantage of algorithms is that it can detect the fraudulent activities quicker than what human analytics can do. The algorithms also provide quick and real-time answers to any activities that require investigation.

6. Predictive Analytics

Telecoms have extensive data from its customers. The industry, therefore, relies on both Artificial Intelligence and machine learning to obtain significant business insights from the data. With the data analytics, companies can make a quick and healthy business decision. The analytics also helps in customer sub-division, prevent churn, product and service development, price optimization, refining product margins, and much more.

Conclusion

The fast-growing rate of the telecommunication industry has leveraged the technologies to help improve customer experience, facilitate self-service, and improve equipment maintenance while reducing the operational costs. It is, therefore, important for companies to apply the technologies to get insights that will help improve their operation.

This article was written by Seamus Dunne of Conversation Piece. Seamus has vast experience working within the telecommunications sector as he is a leading supplier of unified communications technology to the Irish sector.

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