How Does ML, AI, RPA, and Automation Affect Call Center Service?

The call center industry is always on the lookout for new ways and means to make their operations and service delivery more efficient, secure, and productive. It is no surprise then that this industry has been quick to identify the potential gains to be had from using relatively new technologies like machine learning, artificial intelligence, robotic process automation, and automation tools to make operations and service delivery more seamless and effective.

Traditional contact centers have had their fair share of limitations. Whenever a customer calls a call center, they speak with an agent who verifies their details and account and asks what he can do for the customer. The process of gathering information is usually quite difficult for the service agent. They need to quickly jump between various systems to help customers with their needs. In recent years, technologies like RPA in call centers and automation in the call center industry have gained prominence and been recognized for their ability for boosting call center service with automation. Read on to find out more about how automation, AI, and machine learning are changing call centers.

1. The Impact of Artificial Intelligence and Machine Learning in Call Centers

   

   AI and machine learning are impacting call centers like never before. Most predictions project that businesses can benefit significantly from using machine learning. Machine learning is a process built on algorithms that enables a system to learn from inputs such as historical data, new experiences, or instructions. The goal is for the system to be able to observe patterns and adapt its decision-making process to suit the patterns. Artificial Intelligence refers to a broad umbrella of technologies that essentially attempt to recreate human-like intelligence in machines.

   Machine learning and AI have the potential to identify and implement improvements to call center processes such as service provision, call routing, and scheduling. Companies can also provide data to these technologies to help them determine the best time to attempt sales, debt collection, or other tasks. This is possible with the insights that machine learning provides.

   A few call centers are also using artificial intelligence to drive live interaction analytics. Some companies are leveraging the power of call center AI to enhance CX by providing human agents with speech and emotion analytics to help them understand customer disposition.

   The benefits of ML and AI in call centers is that there is scope for continual process refinement. There is also the potential for complex processes to be run with reduced or no human involvement.

   However, it should be noted that ML and AI are not yet refined enough to be able to completely replace human agents. At most, they will enhance the ability of human agents to better serve customers. Also, call centers looking to incorporate AI and ML into their processes will need to make quite heavy investments.

2. The Impact of Robotic Process Automation in Call Centers

   

   If you are looking to automate your contact center, one way to go about it is to leverage the power of robotic process automation (RPA). RPA is already quite established in some businesses and industries and is finding its way into the call center industry as well. Automated tasks like data entry can be performed using RPA. RPA can involve multiple steps and span different software.

   The advantages of RPA are quite obvious. RPA affects call centers' operations by helping to perform repetitive tasks at a far greater rate than a human ever could. Back-office processes are ripe for RPA implementation and can potentially save significant amounts of money for corporations. They can help ensure shorter calls that are of much higher quality, leading to enhanced customer experience. Furthermore, RPA can be set up to run 24/7, 365 days a year. It provides very high accuracy and is available to almost any type of business.

   A potential drawback of RPA is that it can proliferate bad or poorly-designed processes across the call center. It requires continual effort to create leaner processes to ensure the long term survival and efficacy of the call center. However, the impact of RPA in contact centers will only continue to grow.

3. API Automation in Call Centers

   

   APIs, which are software interfaces that connect up different systems, act as a type of universal hub and translator. Call centers are using APIs to create automation to establish new and improved processes. The ability for integration by automating APIs is a significant benefit. Users don't need to log in multiple times and systems can access all the required data from one place.

   The addition of a robust automation platform in call centers enables call centers to develop very advanced automated processes ranging from more intelligent call routing, virtual queueing, and contact recycling. It also breaks up the siloes that often plague call center operations. Agents can also have a single view of all the pertinent customer data.

   One drawback to API integration is that there is a high level of technical and programming skill involved in creating ideal call flows. This is being dealt with by making deploying APIs across a no-code platform to enable any member of the team, irrespective of coding expertise, to create what is required.

Conclusion

Machine learning, artificial intelligence, and robotic process automation have the potential to provide significant benefits to call center companies. One key benefit of these technologies is the significant time savings they can offer by automating repetitive tasks like back-office operations. Most call center firms are aware of these relatively new technologies and are keeping a close eye on development to implement these technologies at the right time. These technologies have the potential to cause significant disruptions in the contact center industry, but they are not yet mature enough to do so now. However, increasingly more call centers are incorporating ML, AI, and RPA into their workflows to enhance productivity and customer experience and cut costs.

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