Make Contact Centers Intelligent, Responsive and Resilient with AI

How AI drives optimization, personalization, and resilience for better customer service

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In March 2020, when countries across the world initiated lockdowns in response to the COVID-19 pandemic, contact centers were thrown into chaos, disrupting the lives of both contact center executives and customers.

With the changing paradigm and greater uncertainty, customers were reaching out more than ever to get their concerns addressed. A recent study by AI and machine learning firm Tethr found that between March 11, when  WHO declared COVID-19 as a pandemic, and March 26, the percentage of calls scored as “difficult” by customer service teams more than doubled. The study covered roughly 1 million customer-service calls involving more than 20 companies representing a broad cross-section of industries.

From canceled travel plans to understanding insurance policies, industries across the board witnessed an uptick in the queries coming in via a multitude of channels. At the same time, contact center executives too are grappling with the change, many of them working from home for the first time in their lives.

Contact Centers have been historically struggling to find a balance between optimizing costs and driving personalization. Customers today expect interactions with enterprises that are highly personalized, conducted across devices and platforms. They also expect quick responses. For instance, more than half of the consumers expect a response from customer service within an hour, even on weekends, as per a study by Edelman Digital. The COVID crisis just added a third dimension around resilience.

As we continue to grapple with the global health crisis, it is time for us to think about making transformational changes to the way organizations run their contact centers that would not only make them more effective in creating positive customer experiences but also make them resilient.

Improving Efficiency and Delivering Superior Experience with AI

Leveraging AI and Automation to drive optimization, personalization, and resilience in contact centers can make a substantial impact on improving efficiency and delivering superior customer experience.

Enhanced Agent Productivity

An intelligent email system that can sense the frustration of the customer from the tone and language of the email written by him/her sounds like every agent’s best aid. An AI-driven advanced email response management system can expedite resolutions by fetching the right information after collecting and analyzing customer emails. This reduces manual effort, accelerates turnaround time, and improves customer experience. It also provides agents with quick visibility into the required customer details so that they can resolve issues faster and effectively.

An omni-channel approach to addressing customer queries can minimize voice calls and thereby free up time for agents, allowing them to be more effective. Gartner had predicted that 25% of customer service and support operations will integrate virtual customer assistant (VCA) or chatbot technology across engagement channels by 2020, up from less than 2% in 2017.

To enhance call center productivity for a gas distribution company in the United States, Infosys enabled a seamless customer experience by providing multiple channels of communication as well as tools for self-analysis of consumption. This minimized customer contact via call centers and rationalized the cost of customer service.

Greater Customer Experience and Insight

Each day, a contact center gets countless calls and emails from customers. These interactions generate a treasure trove of data, which can be analyzed to gain valuable insights that could streamline processes and improve customer satisfaction. AI can help connect the dots between the data points to deliver greater personalization and change the way businesses interact with their customers. Analytics can also help drive a data-oriented value realization approach.

One great case in point is Cisco, which adopted a World Class Customer Service (WCCS) model that brings together all touchpoints and processes into a true “Digital OneOffice” aimed at serving the customer as effortlessly and seamlessly as possible, often without any actual human-to-human interaction. For instance, this model uses cognitive routing to determine the customer’s intent and routes the customer either to a live agent, a robotic process, or a blend of the two based on what it deemed the optimum way.

Social Media Engagement

Customers often consider engaging with their brands on social media to be highly effective given that these interactions reside in the public domain. So, brands are extremely vigilant about complaints or negative comments and are likely to address them on priority to maintain a positive share of voice. Ninety percent of millennials use social media as per a 2019 survey from Emarketer. The COVID-19 pandemic has increased social media usage even further.

Manual tracking of social media requires considerable bandwidth and resources. Given the countless unstructured interactions and huge volumes of data created, AI-based data collection, analytics, and governance have an important role to play. Machine Learning can help glean useful customer insights and track emerging trends at scale.   

Lasting Effects of COVID-19

One of the biggest lessons from the COVID-19 pandemic is the need to build greater resilience in business processes. In the context of contact centers, this translates into moving away from treating each customer interaction as a transaction to looking at it more holistically including all the activities, information, collaboration, etc. in terms of how and where they fit within the larger lifecycle and driving more value in each interaction. It is about making processes as independent and automated as possible to ensure seamless and personalized resolution of customer queries. While the pandemic may not last, the changes that it drives are more likely to be permanent.


Copyright © 2020 IDG Communications, Inc.