How AI is helping revolutionize telco service operations

Running operations in the telecommunications industry is often considered highly complex, and the most successful companies in this sector excel at it. This involves a synchronized and flexible approach across various business units, each of which could be a large business on its own. In recent years, artificial intelligence has shown promise in simplifying these operations by optimizing different functions. Telecom companies are just starting to explore this potential, with operators finding success in using AI to improve service operations, like enhancing in-store customer experiences, call center efficiency, and deploying employees in stores, call centers, and the field.

The challenging economic environment in recent years has made it intimidating to invest in new solutions for telecom companies. However, the potential benefits are significant. Leading telecom companies have already started implementing AI in their field and service operations. Digital newcomers in the industry are also adopting AI as networks become more software-defined and cloud-based. Staying competitive will require keeping pace with both the technology and the leaders in the field.

Enhancing the retail customer experience

AI tools can significantly improve operations, especially in retail settings, where they can break through current bottlenecks. For instance, setting up a phone line in a retail store can take up to an hour on average, offering a prime opportunity for upselling. AI can help by providing personalized ads and offers to customers in the store. It can also integrate online and physical retail functions, ensuring that devices and accessories are in stock and available. If something is out of stock at a particular store, items can be shipped to customers' homes. This means stores can offer a fully customizable supply of accessories, satisfying more customers.

However, to make this happen, retail outlets need sufficient staff on hand to assist customers effectively. Smart scheduling is crucial, but forecasting staffing needs in retail is challenging. AI tools, such as machine learning, can eliminate guesswork and manual processes in forecasting and scheduling. They can use historical data and external information like demographics and online search trends to predict staffing needs with up to 80 percent accuracy.

Improving operations in the contact center

Advanced AI applications are helping top telecom companies in two key ways. First, they aim to minimize the need for customers to contact them for preventable issues. Second, they want to make the most of opportunities to upsell when customers do reach out. These self-healing solutions involve various processes.

For example, billing inquiries generate a lot of customer calls. A self-healing AI solution would assess the main reason for the billing issue, the customer's billing history, their long-term value, and the likelihood of calling due to a billing change. Then, it would take various actions based on the situation. One customer may just need an explanation on their bill, while another might require a retroactive data package. Some customers may consider upgrades or other revenue-boosting actions, in which case it's better for them to call.

This self-healing AI sorts customers into groups based on their likelihood to call and the potential impact on revenue and customer value. It predicts the effects of different self-healing actions and selects the best one to enhance customer value. Over time, it can improve its decisions with a machine-learning feedback loop.

Additionally, self-healing AI can reduce call center demand by addressing wireline device issues before customers notice them. It continuously checks device speed and performance, comparing them to nearby devices to decide on the best action. If customer intervention is needed, it predicts their likelihood to call and prepares the necessary information. For on-site problems, a team can be dispatched before customers experience network issues.

These measures significantly reduce call volumes, allowing agents to focus on complex, value-added tasks, and improving customer and employee experiences. AI-driven smart scheduling for call center staff optimizes staffing levels based on customer needs, creating a more efficient system over time.

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Improving the field force capabilities

In the field force journey, telecom companies need to balance the needs of customers, employees, and external factors beyond their control. Smart AI coaching solutions can enhance the performance and service quality of frontline workers and their supervisors, benefiting both customers and employees. These advanced tools utilize machine-learning algorithms to provide performance insights and coaching materials based on employees' performance data. This results in timely, context-specific digital guidance and positive prompts to encourage desired behaviors.

Field force operations can benefit from smart scheduling, especially in ensuring technicians arrive on time. Weather and traffic can disrupt schedules, impacting customer and employee satisfaction. Machine learning-based AI can analyze historical data, weather, and traffic information to dynamically reschedule technicians in the field. It can also predict potential technical issues based on historical and customer data, notifying technicians about the necessary parts for their daily visits. Telecom company that used historical data to improve forecasting and workforce management achieved an 80 to 90 percent increase in accuracy.

In conclusion, the integration of AI-based smart coaching and intelligent scheduling into telecom field force operations has proven to be a game-changer. It not only enhances the performance and job satisfaction of employees but also significantly improves customer experiences. By tailoring coaching and optimizing schedules based on individual needs and external factors, telecom companies can boost productivity, service quality, and overall efficiency. This innovative approach, driven by artificial intelligence, holds the potential to transform the telecommunications industry, ensuring smoother operations and higher customer satisfaction levels.

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