6 Ways Intelligent Automation is Transforming the Customer Service Industry

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Today’s world has become accustomed to everything being just one click away – including customer service. Customers are no longer used to waiting around for anything and can seek assistance through one of the many smart devices available on the market to cut back on time they think may be wasted waiting. This change has given rise to the likes of personalized requests and bespoke services, resulting in a huge influx of business.

When a business grows, several aspects within the various departments of a company undergo changes and the customer support or service team is no exception. In this era of cutthroat competition, prompt and seamless customer support can help a business stay ahead of its competitors. This is why contact centers, call centers, and customer service teams of several large and small companies are resorting to intelligent automation systems.

How intelligent automation helps the customer service industry

Today’s service-oriented companies wish to save money and time and offer error-free deliveries by automating a good percentage of their daily operations. Intelligent automation, which is inclusive of Artificial Intelligence (AI), robotic process automation (RPA), and multi-cloud architecture solutions, is helping the customer service industry achieve goals in the presence of a smaller workforce in less time.

Here is a list of ways intelligent automation is boosting customer experience:

1. Enhancing the speed of response: The speed at which an issue is resolved has a significant effect on a customer’s CX journey. Present-day consumers lead fast-paced lives and expect quick solutions to every problem they encounter. Experiencing delays can motivate customers to think about the business or brand in a negative light, which can prove disastrous for the brand. Even though employing more resources will lighten the impact for a short while, adopting advanced technologies such as AI-powered chatbots and assistants to help customers via text and calls will help companies gain momentum in terms of immediate customer support.

2. Ensuring omnichannel support: The Internet has made it possible to reach anyone at any point in time and companies across sectors are leveraging this to strengthen their customer service. No longer confined to good-old phone calls, customer support is increasingly being conducted through emails, texts, social media, live chats, and more. Even though having an omnichannel presence has worked in the favor of companies, it has increased the pressure on human agents to be available and work beyond their designated hours. Companies can solve this problem by integrating AI-backed tools capable of prioritizing requests based on severity and responding to the easy ones through FAQs and answers stored in the database.

3. Improving the quality of response: Humans are more prone to errors while robots are not. Unfortunately, in the field of customer service, a singular error can cost the brand a precious client. Robotic process automation can automate manual yet error-prone tasks, such as data entry for the agent’s benefit. This way, employees don’t have to devote a substantial amount of their time to menial tasks and instead can focus on creative and strategic aspects of CX. In addition to this, generative AI tools like ChatGPT can suggest well-structured and articulate responses to human agents so they can communicate pleasantly with the customer.

4. Personalizing customer experience: Effective personalization of customer requests helps to cement customer-agent relationships. Artificial Intelligence powered software can enable something called ‘customer profiling,’ which involves tracking and keeping a tab of out-of-the-ordinary requests and preferences that makes a customer different than the others. Big and small companies are leveraging these insights to create personalized touchpoints throughout the customer experience journey.

5. Using smart insights to reduce churning rate: Most strategists spend a significant amount of time analyzing the exit of a once-loyal customer. Some cases have apparent outcomes, and some don’t. Machine learning algorithms can provide insight for the ones where the brand is unable to pinpoint the reason for a customer’s abrupt exit. These algorithms can study patterns and analyze huge chunks of data sets. They can prompt the agents to work on the areas that need improvement and help managers to make bias-free and effective decisions.

6. Using predictive analytics to meet goals: Companies set new goals for every quarter and predictive analytics can help a company of any scale to meet its goal. Whether it is enriching customer engagement or targeting new customers, the analytics produced by any trusted data analytics software will enable brands to make sound business decisions. In addition to this, predictive analytics can also be used to analyze potential risks of a business move and subsequently create plans to tackle them.

Now, more than ever, customers have begun to demand faster responses, personalized services, convenience, ease of communication, and higher levels of exclusivity. In turn, many companies are willing to go the extra mile to guarantee the above-mentioned requirements and meet these growing customer demands. Organizations across distinct fields are adopting intelligent automation as part of their business strategy, with companies like Alibaba, Unilever and HSBC already using it to predict what customers want and streamline end-to-end CX respectively. By finding creative ways to embrace intelligent automation, businesses can revolutionize their customer service, ultimately leading to a significant enhancement in the customer experience and paving the way for sustained success.

Sohaib Ahmed
Sohaib Ahmed is Senior Director of CX Program Strategy at HGS, the leader in digital-led customer experience and business process management, where he builds relationships with marketplaces and connects companies with comprehensive CX solutions. His expertise spans cloud communications, automation, AI, and lean operations to provide technological and operational insights. Prior to HGS, Sohaib served in a technology strategy consulting role covering North America and EMEA with Accenture specializing in the BFSI, retail, and energy sectors. Sohaib holds a master's degree in computer science.

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