Welcome to a new era of AI customer service, where generative AI is redefining customer interactions, making them more personalized and efficient, while amplifying the human touch.
In this blog, we’ll dive into this new era and explore how embracing Generative AI can benefit customer service and support teams, and why it’s a crucial tool for staying ahead in the competitive landscape.
But first, let’s understand the core differences between Conversational AI and Generative AI.
Conversational AI and Generative AI: understanding the differences
What is Conversational AI?
Conversational AI is a form of artificial intelligence (AI) capable of understanding human intents and conducting human-like conversations. By leveraging NLP (Natural Language Processing), NLU (Natural Language Understanding), and ML (Machine learning) technologies, conversational AI understands customer intents and provides relevant responses based on existing knowledge from its database.
In customer service, conversational AI is used to power AI chatbots and automate the majority of repetitive tasks – from answering customer queries, routing calls or scheduling appointments. AI chatbots understand customer intents and provide intuitive responses 24/7, across communications channels.
What is Generative AI?
Generative AI is a form of artificial intelligence that uses neural networks and large language models (LLM) to identify patterns in its training data and generate new content. Generative AI learns from historical data, understanding the context, language, and prompts, constantly evolving its capabilities and generated content.
What is the difference between conversational AI and generative AI?
Conversational AI and generative AI each have their own goals and uses. While conversational AI is focused on facilitating discussions that simulate human interaction and delivering relevant responses, generative AI is centered on crafting and producing new, original content.
Another difference is that conversational AI requires a massive volume of training data to accurately comprehend and respond to human language, while generative AI analyzes patterns in the data and generates content based on these patterns and structures.
How generative AI is redefining the customer experience
Generative AI is already setting roots in the customer experience field, as more businesses look to adopt its capabilities. However, generative AI isn’t here to replace conversational AI. Both technologies are essential to achieve higher levels of personalization, customer satisfaction, and business efficiency.
Generative AI for customer service: unlimited knowledge at humans’ fingertips
Generative AI provides service reps with vast but accurate knowledge to answer customers’ requests. Agents can use GenAI to rephrase their responses or adjust their tone and avoid errors or typos.
Another way GenAI is revolutionizing customer service is automation. Utilizing generative AI enables businesses to enhance their automation capabilities – equipping customer service chatbots with advanced language processing capabilities.
The benefits are substantial – recent research by McKinsey indicates that businesses can save up to 60-70% of employees’ time by utilizing generative AI. Another research has found that implementing generative AI increases the hourly average handling time by 15%.
Customer support automation with ChatGPT: faster, more efficient and personalized
Customer support teams are constantly overwhelmed with repetitive requests, often described by customers in different ways. By utilizing AI chatbots, support teams can understand a broader set of intents, yet they are still limited and requires constant maintenance and training.
GenAI tools such as ChatGPT can help amplify existing AI chatbots, while keeping the original script and objectives. You can use ChatGPT’s language model to generate a wider range of customer intents, train your chatbot, and deliver personalized experiences at a larger scale.
For example: you can automate various customer support requests like tracking order status, resetting passwords, providing store hours, handling returns and exchanges, and answering frequently asked questions, thereby enhancing efficiency and allowing customer support representatives to focus on more complex, high-value interactions with customers.
Generative AI for sales: a new sales assistant emerges
Generative AI also has the potential to revolutionize sales. By deploying an automated sales assistant powered by GenAI, businesses can automate key sales use cases such as lead qualification, renewal requests, and transaction processing.
In lead qualification, for example, generative AI can engage with customers and analyze conversation data to determine the likelihood of conversion, ensuring that sales teams focus their efforts on the most promising opportunities. It can also categorize and prioritize leads, schedule follow-ups, or manage a contract renewal process, reducing the manual workload on sales representatives.
A study by McKinsey indicates that investing in AI can lead to a revenue increase of up to 15%. Furthermore, it can elevate sales ROI by a substantial 10%-20%, by optimizing sales operations, enhancing targeting precision, and personalizing sales journeys, thereby ensuring that the sales teams are effectively driving revenue growth.
Generative AI for call centers: key to minimizing costs
Generative AI has the potential to drastically reduce call center operational costs. By enhancing human productivity, automating routine tasks and providing tailored experiences, generative AI, combined with conversational AI, can help call centers to minimize the number of incoming conversations, reduce wait times and call abandonment rates (CAR), accelerate average handling times (AHT), and reach cost-efficiency.
Moreover, it’s clear that younger generations like GenZ are moving away from phone calls towards business messaging. In this reality, businesses will have to adopt GenAI into their digital customer service as well, to ensure they meet customer needs, wherever they are.
Generative AI: amplifying the human touch, not eliminating it
69% of employees fear AI may take their jobs, but that’s not the case when it comes to customer service. In reality, contact centers suffer from a massive agent shortage, projected to worsen in the coming years.
What will be the role of AI? AI will fill in for the necessary workforce, while empowering the existing human teams with knowledge and tools to effectively handle customer requests, focusing on higher-level tasks and complex problem-solving. So, eventually, generative AI will amplify the human touch and elevate the customer experience.
Now that we’ve finished diving into the different aspects of generative AI, you’re probably thinking – “How do I get started with Generative AI in my business? What kind of solution should I look for?”, “Is it complicated and requires development skills?”.
Well, the answers are not as intimidating as you might think.
Getting started with generative AI in customer service: 4 key steps for entering the new era
Step 1: Identify and choose an AI-driven customer communications platform
Start by selecting a leading AI-driven omnichannel customer communications platform that natively enables you to deploy AI chatbots and amplify them with generative AI, without requiring any coding skills.
This omnichannel platform will also allow you to manage all customer interactions across channels from a single agent workspace, serving as a central interface for human agents and AI chatbots. This will ensure the foundation you build on is robust and reliable.
Step 2: Deploy advanced generative AI virtual assistants
Once the foundational platform is in place, you can launch your GenAI virtual assistant to automate end-to-end use cases. For example: you can scan your website’s FAQ page and let the virtual agent answer instantly based on the provided database.
To do so, you need to define which main use cases you want the AI to automate, equip it with the relevant knowledge, and launch it across your main customer communication channels. This will not only provide a better experience but also enhance your service efficiency and quality.
Step 3: Introduce human agents with generative AI
Agents should understand generative AI’s capabilities and how it can make their work and life easier. Enable agents to explore and understand the functionalities and applications of these advanced tools in real-world customer service scenarios, to provide them with knowledge and enhance their productivity.
Step 4: Measure and optimize business performance
After setting up generative AI, it’s vital to consistently monitor and evaluate its performance. Analyze call abandonment rates, resolution rates and CSAT scores for conversations involving generative AI. Modify your script to ensure human assistance is available when required. Regularly review conversations and make adjustments to meet evolving customer needs and expectations.
Conclusion
Generative AI has infinite potential to revolutionizing customer service, support and sales. Embracing the new era of generative AI is not about eliminating the human touch, but about providing more value to customers, through combining artificial intelligence with human empathy. This synergy ensures that the essence of the human touch is not lost but is, in fact, enhanced, leading to more meaningful and satisfying customer experiences.
It’s time to join a new era, with Generative AI at your fingertips.
