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The telecommunications industry is undergoing a seismic shift, driven by the advent of constantly evolving technology. 5G technology has led to faster, more reliable network connections and has enabled a new era of IoT and smart device connectivity. The rise of AI and machine learning has revolutionized customer service and network management, which allows for more personalized user experiences and predictive maintenance. The increasing integration of cloud computing in telecom infrastructure has enhanced data storage and processing capabilities, paving the way for more efficient and scalable network solutions.
The average user struggles to keep up. But fortunately, these massive industries are in the hands of some of the world’s finest minds, such as Venkata Ashok Kumar Gorantla, a visionary AI and ML leader who is currently serving as an Associate Director at Verizon. His stellar reputation has made him a thought leader in multiple industries, including healthcare and communications, and has secured him the coveted role of a Globee Awards judge and a Stevie Awards judge.
“Using the latest tech – like AI – does not mean that any companies should leave out the human aspect of customer service,” Ashok says. “Our job on the back end is to make sure that this technology enhances the customer experience. We use tech like AI and ML for predictive analytics and customer interaction in order to up the ante when it comes to the quality of service.”
Redefining Customer Interactions with AI/ML
Ashok explains that – when used right – AI and ML technologies can serve as the keystones in transforming customer service from reactive to proactive, from generic to personalized.
“Traditionally, customer service models in fields like telecommunications have been largely reactive,” Ashok shares. “It involves customer support teams addressing issues only as they arise. For example, even if there was a known issue with a particular service, many companies would still just wait for customers to call in and complain rather than address it ahead of time.”
Ashok’s work involves implementing tech that shifts this paradigm by leveraging AI/ML for predictive customer service. This involves analyzing customer data and interaction patterns to anticipate needs and problems before they escalate, enabling a more proactive approach to customer service.
Personalization at Scale
One of the most significant impacts of AI/ML in customer service is the ability to offer personalized experiences at scale. “I have worked to develop algorithms that analyze vast amounts of customer data to understand individual preferences and behaviors,” says Ashok.
He explains that this data-driven approach allows telecom companies to tailor their interactions and services to each customer’s unique needs, enhancing the overall customer experience. And it allows for individualized experiences on a large scale – across millions of customers, each of whom has a different set of needs and expectations from the companies they do business with.
“For me, it goes back to my decade-long career in the healthcare sector,” says Ashok. “Even working in the tech aspect of healthcare, you are exposed to a dizzying array of different patient needs. Every patient’s health is unique. And every customer of, for example, a wireless provider has unique needs as well.”
Efficiency and Automation
AI/ML technologies are also pivotal in increasing the efficiency of customer service operations. “A lot of people worry about AI-driven chatbots and virtual assistants replacing people, or providing poor service to customers,” says Ashok. “Much of my work has been to combat that by automating routine inquiries and tasks.”
This, he says, serves to free up human customer service representatives to handle more complex issues. “There are plenty of customer contacts that are easy and routine,” says Ashok. “Automating these ensures that customers receive quick and accurate responses. But more complicated problems require the human touch. There needs to be empathy and rapport, things a chatbot can’t offer. And that is why we view AI as so beneficial – it doesn’t replace people, it helps them do their jobs better.”
Automation in customer service also extends to network maintenance, where AI algorithms can predict and preemptively address network issues, reducing downtime and improving service reliability. With less downtime comes fewer customer complaints – and again, the customers are getting better service more quickly, and human reps can focus on complicated issues.
Enhancing Customer Loyalty and Retention
“While my work is definitely quite keenly focused on improving service efficiency and personalization, it also focuses on enhancing customer loyalty and retention,” says Ashok. He says that telecom companies should prioritize providing timely and personalized service in order to build stronger relationships with their customers, and AI/ML-driven insights allow for a deeper understanding of customer satisfaction drivers;.
“When we know what customers want – or don’t want – we can provide that,” Ashok explains. “Since AI can analyze vast amounts of data very quickly, and with higher accuracy than humans, it provides vital insights into customer expectations. Say you have thousands of customer surveys; AI can quickly analyze all of them and determine that – just for example – 25% of customers want more affordable family plans. The company can then examine its service packages and adjust accordingly.”
The overall goal is to let companies know how to refine their offerings and communication strategies to better meet customer expectations. When customers realize that they are being listened to, and that companies are willing to make changes based on customer satisfaction and requests, it’s a huge loyalty driver.
Challenges and Evolutions
Implementing AI/ML in customer service, however, comes with its set of challenges. “It’s important to address issues like data privacy, ethical use of AI, and making sure that AI and Ml systems are free from biases,” says Ashok. His approach involves continuous refinement of algorithms and adherence to ethical standards to ensure that AI/ML technologies are used responsibly and transparently.
But challenges aside, Ashok is optimistic about the future of these technologies. He even predicts that AI and ML will play an increasingly integral role in customer service. This includes the use of advanced predictive analytics for hyper-personalized services and the integration of AI in emerging areas like 5G and IoT. The future also holds the potential for AI/ML to facilitate new forms of customer interaction, such as augmented reality (AR) and virtual reality (VR) based support systems.
Venkata Ashok Kumar Gorantla’s vision and work in AI-driven telecommunications is certainly setting ever higher benchmarks for customer service. He’s also pointing the way toward the future of the industry, with his innovative use of AI/ML technologies. He is transforming traditional customer service models, leading to more efficient, personalized, and predictive customer experiences – and making customer service more responsive, intuitive, and customer-centric than ever before.
https://www.linkedin.com/in/ashokgorantla/
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