By Chandrashekar Mantha and Guneet Vijan
Customers expect personalised and efficient service, and the emergence of generative AI has led to a significant shift in the way businesses approach customer service and customer delight. Like human interactions, AI, and NLP-enabled voice bots and chatbots can understand customer queries and provide accurate and personalised recommendations and solutions.
Customer experience (CX) automation has now become a crucial enabler for companies to improve customer experience, drive efficiencies, reduce costs, and engage, acquire, and retain customers. That’s where CX automation solutions come in which can handle customer queries seamlessly, provide hyper-localisation and personalisation in terms of local language capability, leverage data analytics to action upon business insights utilising customer behaviour and preferences, as well as implementing natural language processing (NLP) to understand and interpret human language, intent, entity, context, and sentiments to answer user queries.
An important aspect is defining the clear business objective of using technology. Understanding the customer journey and experience, and then reverse engineering it with technological advancements is the optimal way to achieve outcomes. Identifying key touchpoints in the customer’s journey where generative AI can add value becomes the foundation of building any use case. –
“You’ve got to start with the customer experience and work back toward the technology, not the other way around.” – Steve Jobs
Another important aspect is to prioritise transparency and ethical considerations, ensuring that generated content aligns with the company’s brand guidelines and avoids any sort of bias. Guardrailing the Large Language Model (LLMs) is necessary to make sure the responses or recommendations generated are not absurd and more predictable and relevant to the problem statement. Companies need to develop a collaborative strategy where the amalgam of human-assisted domain training on the Generative AI model results in an enhanced personalised experience for both customers and agents. As Generative AI models require frequent fine-tuning, performing iterative development and setting up a testing framework becomes crucial for any AI-based intervention. Careful evaluation and consideration of these factors are essential for organisations to make informed decisions and leverage the benefits of generative AI effectively.
Top ways customer experience can be improved with the help of Generative AI:
One of the key areas where Generative AI will drive great value is enhancing the existing customer support across channels. Generative AI and LLM powered omni-channel bots hold transformative potential for businesses across sectors. These chatbots/voice bots deliver 24/7 customer support, resolving queries promptly and efficiently, while also automating repetitive tasks like order tracking and appointment scheduling. By gathering insights and behaviour of customers, further prediction models can be built to offer end-to-end process automation. Their ability to swiftly adapt to various languages and understand regional nuances is no match to current operation-heavy language/skill-based resource allocation practices. These bots efficiently automate routine processes, ensure optimal resource allocation, and provide a seamless user experience all this while maintaining the brand’s identity and guidelines. In essence, generative AI and LLM-powered chatbots empower businesses to elevate their customer engagement strategies, cultivate brand loyalty, and drive overall efficiency.
In the realm of ever-changing social media, Generative AI can process unstructured data, such as customer reviews, comments, and CSAT scores, to analyse sentiment and gain valuable insights. By applying natural language processing (NLP) techniques, Generative AI models can understand the context, emotions, and themes within the text. This use case enables companies to extract actionable information from the unstructured data, identify trends, and measure customer satisfaction effectively.
Generative AI auto-categorises unstructured data and further divides the data into sub-clusters to perform root cause analysis on it. For instance, in a customer support scenario, the AI system can group similar customer complaints or issues together into clusters, allowing companies to identify common problems and prioritise them for resolution. Additionally, by analysing the root causes of these issues, businesses can implement targeted improvements to enhance their products or services, leading to better customer experiences and increased operational efficiency.
The transformative impact of Generative AI on customer experience cannot be overstated. As technology continues to evolve, businesses must adapt to the latest trends, however, companies need to utilise the human domain expertise with advancements of Generative AI to harness the full potential of AI-powered solutions. By integrating Generative AI-driven automation, companies can not only elevate their customer experience but also cement their position as pioneers in the age of customer-centricity. As we venture into the future, it is essential for businesses to embrace AI as a catalyst for change and redefine the boundaries of customer engagement to stay ahead in the ever-competitive market.
The authors are partner, risk advisory, and director, risk advisory, Deloitte India,respectively
Follow us on Twitter, Facebook, LinkedIn
