Over the last few years, customers’ expectations of a satisfying service experience have undergone a significant change. Customers now demand customized solutions to their problems, delivered with agility. To address this need, businesses are adopting technology to enhance the speed of their customer service. These customer requirements have made it imperative for businesses to adapt Artificial Intelligence (AI) technologies and robotics to ensure seamless service delivery. AI can reduce response times by sorting through messages and other data at a greater speed. However, AI technology cannot be used in isolation to address customer concerns.
Automated services often generate robotic responses, resulting in customer dissatisfaction as the solution is not tailored to meet their needs. Integrating ideas and solutions from humans can bridge the difference between a customer dealing with unsatisfactory robotic responses and a customer satisfied with the quick and unique solution to their problem. While AI systems can process data and messages at infinitely faster speeds, they still need a human element to carry forward businesses and their process services.
Applying design thinking for customized solutions
Design thinking is one way to approach this collaboration. It offers the ability to include a human element to build upon AI’s existing technology to create effective solutions for customer problems. Combining human intelligence with AI and robotics can give businesses the required edge in customer service. Businesses can build upon AI’s efficient processes to create meaningful solutions that address their customers’ concerns. Ideally the solution provided should be a combination of AI and human creativity to provide the best service experience for customers. Integrating design thinking with AI processes offers multiple benefits to the business. It not only speeds up the implementation of AI but also allows a business to test multiple scenarios simultaneously, allowing it to offer the right solution in a shorter span of time.
Regulatory requirements are an influential factor across industries, be it banking and financial services or media, retail, and legal industries. In case of regulations applicable to the AI industry, companies can save millions of dollars in lawsuits by constantly updating their AI systems’ responses to complex scenarios. This can be achieved successfully, with the help of “design thinking” with human intelligence ensuring a smooth solution alongside AI technology.
For a process with an objective to ensure an ideal customer experience, the model approach with design thinking would evolve over a series of steps to combine human intelligence and AI. The first order of business would be to assemble a team comprising representatives on behalf of the customers and other stakeholders to determine the feasibility of a proposed solution. The team would need to identify the specific issue being faced by the customers. Having identified and analyzed the issue, the design thinking team would need to come up with possible scenarios to develop and test with the AI technology.
Finding the optimum solution for the problem would be time consuming for human intelligence alone. However, the AI’s cognitive intelligence would allow the team to test each scenario to identify the optimum approach to a customer issue much quicker. Based on these results process maps would be created to provide initial guidance to the cognitive bot. A prototype would be created based on the combined results of human intelligence and AI. Finally, this prototype would be tested with results being monitored in real time, with the team correcting any deviations from the process maps. This coupled AI’s self -learning capabilities would ultimately result in the creation a more efficient solution.
An illustration of how design thinking helps enhance customer satisfaction
To illustrate the process described above, let us take the example of a global bank that needed to improve its customer satisfaction and engagement.
Step 1: A team that represented customers and stakeholders, members of the operations team, and technical experts was assembled. The team members were expected to provide guidance on whether an idea was feasible.
Step 2: They identified that the customer service team needed to reduce the handling time of chats, using multiple case studies from across the bank as a reference.
Step 3: In the case of the bank, the team created a comprehensive list of all customer case types processed by existing agents, refining a shortlist of case types that occurred most often.
Step 4: Finding the best solution for the problem at hand would have taken weeks for human intelligence alone. However, with AI’s cognitive intelligence, the team could use the system to test each scenario to identify the best approach to a customer issue.
Step 5: Combining the results of both human intelligence and AI, the team created a prototype to showcase how the chat-bot would help make the online chat function smarter, saving valuable seconds from the overall chat time.
Step 6: Finally, the team put the cognitive bot in a test environment to identify the most effective responses to customer queries. A combination of real time monitoring, the cognitive bot’s responses being refined by the team and the chatbot’s own self-learning capability allowed the team to ensure that the chatbot would correct itself and speed up the process of solving a customer’s issue.
Ultimately, the bank was able to refine its customer query chat function with the help of AI.
Following more simulated learning sessions, AI systems will be able to solve customer queries with greater ease. Advancements in the domains of AI and robotics have ensured that humans and computers can interact more naturally, and the gaps in communication are closing rapidly. In future, design thinking will become an indispensable part of AI implementation, to develop the best processes for customers and organizations.
About the Author
Pinaki Ghosh heads the Credit and Collections practice for Wipro’s Digital Operations and Platforms business. Pinaki’s industry experience of nearly 20 years spans areas of Operations, Analytics, Legal Debt Collections, Early/Late-stage Collections, and Recoveries program management for delivery across the globe. He has also led automation and transformation initiatives within Wipro, and played active part in new business acquisition initiatives while managing clients’ Digital operations as a single point of contact. Pinaki received his Post Graduate Certificate from the Indian Institute of Management (IIM) Calcutta.