8 min read Generative AI is rapidly transforming how businesses operate across various functions.
From personalized marketing campaigns to advanced analytics, AI has become a cornerstone of innovation and efficiency across departments. And one of the upcoming as well as promising areas of its application is customer support and service.
In this post, we’re going to discuss all about Gen AI for customer support and service.
Table of Contents
What is Generative AI for customer support?
Generative AI in customer support refers to using AI systems to generate human-like text, responses, or content based on incoming queries, questions, and inputs. It helps customer support teams automate repetitive tasks like answering FAQs or routine requests, generating personalized responses based on past interactions, understanding customer sentiment to adjust tone of voice, and providing multilingual support for global audiences.
Why use generative AI for customer support and service?
Implementing Gen AI in customer service comes with several benefits, including:
1. Increased efficiency
Gen AI can handle up to 80% of repetitive queries. This frees up human agent time to focus on more complex queries/ issues. According to a McKinsey report, this can help increase customer support productivity levels by almost 40%.
2. Improved customer satisfaction
Gen AI can help deliver instant, accurate, and personalized responses to customers. Studies have shown that 75% of customers are more likely to remain loyal and give repeat business to companies that offer easy and fast support services.
3. Cost savings
Automating routine tasks can help businesses reduce their customer support operational costs by up to 30% without compromising on the quality of service offered.
4. Scalability
Gen AI alongside automated workflows can help businesses manage higher volumes of customer interactions simultaneously. This is especially helpful during peak seasons when the expectation for faster query resolution also increases.
5. Advanced personalization
Generative AI in customer service can help businesses deliver a higher degree of personalization in support. This includes going beyond their name to understand their lifecycle with the company, previous purchases and preferences, and more.
6. Empathetic support
With the ability to analyze conversations in real time to understand the sentiment behind them, businesses can offer more empathetic support. Gen AI in customer support here helps them show consumers that they are heard and seen.
7. Improved insights
AI-powered tools can analyze customer interactions on a deeper level. Businesses can uncover trends, sentiments, and recurring issues proactively to refine their strategies for better customer experiences.
What are the different ways to use Generative AI in customer support?
Here are some ways in which we’re seeing businesses use Gen AI in customer service:
1. Auto-generating customer replies
Gen AI can understand customer queries, pull data from knowledge bases, and help agents draft replies quickly.
2. Assisting agent responses
Gen AI can use inputs from human agents to generate detailed responses to customer queries, which can help save time typing and speed up responses across channels.
3. Automate note-taking
Gen AI can monitor customer conversations in real time. These systems can capture key points during the call, letting agents focus on keeping the flow of conversations.
4. Identifying customer FAQs
Gen AI can identify recurring customer queries and categorize them. This helps businesses identify and improve their knowledge bases and streamline their self-service options.
5. Automating post-call summaries
Instead of manually writing summaries or follow-up notes after calls, Gen AI can help agents automate the process. This can also help standardize the structure and uploading of detailed post-call notes, reducing the time spent on documentation.
6. Simplifying call transfers
With detailed call summaries, Gen AI along with automated workflows can help enable seamless handoffs. This helps provide complete context to the human agent or the next team that is involved in resolving the customer query.
7. Identifying automation opportunities
Gen AI can help identify patterns in customer support queries. This helps discover opportunities to automate routine processes to save time and cost of operations while ensuring customer satisfaction.
8. Set QA scorecards
Quality assurance has become increasingly important with multichannel support strategies. Gen AI in customer service can analyze historical data and identify key performance indicators tailored to specific workflows. It can also automatically fill in subjective criteria with supporting evidence to improve the quality of QA processes.
9. Identify training opportunities
By analyzing interactions and resolution paths, Gen AI in customer service can help highlight areas where the process needs improvement. This can include opportunities to upskill or reskill agents to manage support queries better.
10. Real-time agent alerts
Gen AI can monitor ongoing conversations to flag issues that require immediate attention based on set criteria. This could include a change in customer sentiment or agent behavior, prompting supervisors to step in timely to resolve potential escalations.
11. Measuring customer emotions
Gen AI can detect emotions like frustration, confusion, or relief in conversations. This can help agents handle situations more empathetically for better outcomes towards customer satisfaction.
12. Translating customer calls
Gen AI enables real-time multilingual communication. So agents can convert speech to text and translate it with ease, allowing them to interact with customers in their preferred languages.
13. Generate knowledge articles
With Generative AI, agents can quickly draft detailed knowledge articles based on the conversation. Automating this process helps ensure support teams have access to updated and accurate content to assist future customers.
14. Personalizing customer engagement
Gen AI customer support systems can be integrated with CRM and marketing tools. This helps tailor responses that resonate with a customer’s unique history, needs, and preferences to create an engaging conversational flow.
15. Offering proactive support and service
Gen AI enhances decision-making with real-time analysis of current and past interactions. It can help use insights from customer history and previous resolutions to suggest outreach opportunities that boost first-contact resolution rates and reduce the overall number of support queries submitted.
16. Improved sentiment analysis
Gen AI in customer service goes beyond surface-level sentiment analysis. It can help identify sentiment trends over time, tracking positive, negative, and neutral changes in conversations, and offering actionable insights that can help resolve queries more efficiently.
17. Co-pilots to agents
Gen AI can also act as a co-pilot to customer support agents during live interactions. It can provide suggestions, reminders, and context, leading to better outcomes and shorter query handling times.
18. Automating customer feedback
Collecting and categorizing feedback is crucial to improve customer support and service. With Gen AI businesses can organize insights into actionable categories to improve offerings across departments.
19. Improved multichannel communication
Gen AI ensures a consistent brand experience across email, chat, social media, and other channels. It helps tailor interactions and processes to fit the unique characteristics of each platform while maintaining brand voice and messaging style.
Common pitfalls of using Generative AI in customer support
While there are several ways in which Gen AI can make customer support efficient and effective, here are some common pitfalls to avoid:
- Inaccurate responses – AI systems can generate incorrect or irrelevant responses. Ensure you regularly update the inputs provided and fine-tune the responses for the systems to learn.
- Lack of empathy – AI lacks the emotional intelligence of human agents while handling sensitive issues. It’s important to set up a seamless hand-off to agents and train AI agents to tackle such concerns.
- Data privacy – Handling customer data requires strict compliance with regulations like GDPR and CCPA. It’s important to ensure the solution you use is compliant to all.
- Over-reliance on AI – Human agents may start to be overly dependent on AI for managing customer support. It’s important to set clear guardrails with dos and don’ts and train your agents.
- Implementation – Deploying Gen AI solutions requires an upfront investment. This includes infrastructure, training, and ongoing maintenance, which can cause friction for businesses.
Conclusion
Gen AI in customer support and service opens a lot many doors to making the process more effective and efficient.
But the only way to implement Generative AI into your support functions is to identify the use cases you’d like to address and find a solution that lets you build out custom workflows.
Auralis AI helps businesses set up customized and advanced AI workflows for support teams, automating 70% of the process.
To know more, book a demo.
