Editorial
The Gist
- AI advantage. Generative AI in customer service revolutionizes support by enhancing efficiency and collaboration.
- Agent boost. Applying generative AI can reduce agent attrition rates by 25% and improve overall job satisfaction.
- Data power. Generative AI aids in quickly analyzing customer data, providing valuable insights to improve service.
Like quicksand, managing customer expectations is hard to stay on top of — a problem that’s exacerbated when 52% of customers drop a brand after a single negative experience. Thankfully, with generative AI’s push into the enterprise, customer service teams can be equipped to overcome these challenges and deliver experiences that keep customers returning.
Let's take a look at generative AI in customer service.
As businesses continue to explore opportunities to implement generative AI in customer service operations, some claim that the era of assisted support is over. Will generative AI take over the jobs of support agents? The short answer is no.
Instead, organizations will need to transform their customer support into a more collaborative model that incorporates generative AI, as they shift away from the traditional-tiered model and improve self-service. Customer experience teams will be able to provide more effective and efficient service to customers with the help of generative AI.
AI in Customer Service: Addressing Agent Attrition
Agent retention has always been a huge challenge for support teams. Generative AI in customer service has the ability to handle simpler cases, such as frequently asked questions. By automating routine inquiries and tasks, generative AI promises quick answers to common problems. With tier one cases being speedily solved through automation, agents are more challenged in their work with more complex cases that require their expertise and a more nuanced, human approach.
This is especially critical when the average agent attrition rate is 42%, with non-challenging and repetitive work contributing to this number. The application of generative AI has been found to lower agent attrition rate by 25%, according to McKinsey research. Bonus — human and AI collaboration in customer support teams also leads to improved customer satisfaction through increased case resolution efficiency.
Generative AI in customer service can speed up the process of documenting, accessing and sharing information from a knowledge base, shaving down the time support teams spend on this rote but key task and allowing them to find solutions to customer problems faster.
Related Article: What You Should Know About AI Customer Service Tools
Generative AI Can Provide Valuable Customer Insights
Agents are trained to connect the dots between a problem the customer is facing and the right solution. But it is almost impossible to draw patterns from a singular case, and it's time-consuming to manually comb through cases to identify trends.
Support organizations are sitting on a gold mine of information. The challenge is on how they can efficiently navigate through this information to find the valuable insights that can improve the customer experience.
In comes generative AI. With its “superpower” to swiftly analyze vast amounts of data, support leaders should leverage generative AI as a "short-cut” for recognizing patterns. These insights can then be used to improve the product/service, thus creating a positive impact on the customer experience.
But generative AI’s “superpower” doesn’t stop there — agents can leverage it as a copilot, assisting them throughout the entire resolution process. By suggesting solutions, customer responses and the next best action, generative AI’s impact on reducing resolution times and preventing escalations can be significant.
A study from the National Bureau of Economics Research found that generative AI increased agent productivity by 14%, measured by issues resolved per hour, while a McKinsey case study showed a decrease of more than 20% in cost-to-serve for customer interactions.
Finally, generative AI enables higher personalization at scale, as it can leverage all relevant data points (user actions, customer profile, documentation, etc.) to empower agents with insights to deliver a tailored experience for each customer.
Related Article: Customer Service Chatbots: AI Can Enhance Your CX
Generative AI Can Improve Self-Service
Self-service is becoming increasingly popular — 69% of customers prefer to solve a problem on their own – and generative AI in customer service can augment it by providing highly personalized and human-like answers. But when customers fully resolve their issues using self-service, three things tend to need to be true: they understand the information, they trust the source of information and they can confirm this is the best way to solve their problem. They need to feel confident in the answer they get when using search supported by generative AI. Customers want to see where content comes from — provide links to show what sources were used to generate the answer to their question. This allows them to fact check, and avoids hallucinations that are a valid concern with this type of technology when not executed properly.
Related Article: How to Leverage Your AI-Powered Customer Support Strategy
The Future of Generative AI in Customer Service
Generative AI will transform customer service for the better through agile case resolution, more personalized experiences, and boosted agent creativity and proficiency. In fact, the technology is already helping customer support agents increase their productivity by 14%.
Customer expectations have changed; we’ve moved from searching for answers to search for advice. While there are other AI concerns — data privacy, security, accuracy to name a few — it shouldn’t stop businesses from beginning to implement generative AI and finding a trusted technology partner to help remove these risks. It is here to stay. Much like how the internet was once the unknown frontier and is today a familiar tool at our fingertips, so too will be the case with generative AI.
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As the technology continues to improve to be more accurate, secure and safe, what customer support teams need now is to learn and adapt generative AI in customer service into their everyday environment. Your customers want it, and if you aren’t using it, you are opting to compete against it. It’s that simple.
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