Businesses are excited about AI in customer service, it makes support more efficient, is available 24/7, optimizes support costs, handles multiple customers simultaneously across platforms, provides personalized help, understands human language and sentiment, and more.
With the powerful potential of AI and its ever growing scope in customer support tools, there are also challenges such as identifying the right AI tools for your business, getting human agents and AI to work together, etc. The key is finding the right balance – letting a well-trained AI model handle manual tasks while human agents add that personal touch.
In this article, we discuss AI that’s built specifically for customer service and its benefits for customers, agents, and leaders alike.
What is AI in customer service?
AI in customer service helps businesses respond faster and improve support. It includes chatbots, automated replies, and data analysis to solve problems quickly. AI makes support more efficient and helps customers get answers anytime.
It can handle common customer questions, identify sentiment, provide personalized responses, and improve agent efficiency and customer satisfaction. It also helps analyze customer interactions to find trends and pinpoint areas where businesses can enhance their support operations.
The benefits of using AI for customer service
Customers today typically expect quick responses: 6-15 seconds for chat, emails answered within an hour, and resolutions on the same day. Meeting these expectations is crucial for great customer service.
AI improves customer experience as it is available 24/7, can deflect L1 queries and FAQs for faster resolutions, and act as the perfect copilot for human agents, enhancing their efficiency. Let’s take a closer look at how AI benefits customer service:
1) 24/7 customer support
Unlike human agents, AI systems can operate continuously. It can provide round-the-clock customer support without the constraints of human limitations. It can be helpful for customers who live in different time zones or have queries outside of business hours. This ensures that customers get instant support whenever they need it. AI-powered support also enables businesses to scale and handle overflowing customer enquiries without compromising service quality or response times.
2) Optimized support costs
Implementing AI in customer service operations reduces the need for a large support team, as AI-driven tools can manage numerous queries simultaneously such as:
- Dealing with similar customer queries and frequently asked questions
- Guiding customers around the website or app
- Updating records for new and existing customers
This not only lowers operational costs while maintaining high service standards, but also reduces possible human errors, making it a cost-effective solution for customer support.
3) Improved agent productivity
As customer service agents receive a number of different queries everyday, ranging across various topics, it is easy to get overwhelmed or confused between conversations. AI for customer service, powered by generative AI, acts as the perfect co-pilot to help agents navigate these situations easily by
- Summarizing conversations and emails with customers
- Rephrasing agent messages to suit the brand tone and voice
- De-duplicating tickets and clustering them to find common themes in customer tickets
- Offering suggestions for next best actions
And more!
4) Lesser agent burnout
By taking over repetitive and mundane tasks, AI reduces the workload on customer service teams, minimizing stress and preventing burnout. This ensures a more motivated and satisfied support team, capable of delivering better customer service.
5) Enables informed decision-making
AI tools provide precise and comprehensive reports, offering insights into customer behavior and support performance. These accurate analytics enable businesses to make informed decisions, identify trends, and continuously improve their customer service strategies.
6) Proactive customer service
AI in customer service goes beyond just addressing queries; it can actively suggest products or services based on a customer’s history and customer preferences. By analyzing past interactions, history, and customer behavior, AI technology can help to provide personalized recommendations and enhance the overall customer experience along with increasing sales.
A part of providing proactive support is also being predictive. Predictive support is when you detect possible issues before they become problems. So, instead of waiting for customers to reach out with problems or inquiries, implementing a predictive support model uses data analytics, AI, and a robust knowledge graph to forecast customer behavior.
Examples of AI in customer service
1) Chatbots
Chatbots are one of the most effective AI tools in customer service, functioning much like a digital customer service representative. They can significantly enhance customer relationships by providing seamless and personalized experiences. They can:
- Answer frequently asked questions
- Collect information and details from customers to give personalized service experiences
- Route customers to appropriate support agents
- Deflect L1/L2 queries by offering troubleshooting steps for common issues, such as resetting passwords or recovering lost data, etc. significantly reducing the resolution time.
2) Virtual assistants
Virtual assistants are advanced AI tools that help to perform tasks better and engage in more complex customer interactions. Utilizing natural language processing (NLP), these tools understand and respond to user input in a way that feels human-like. They can also be used to provide customer support by answering questions, resolving issues, and providing recommendations. Moreover, virtual assistants can be integrated with backend systems, ensuring quick access to relevant information and freeing up human agents to deal with customer service issues.
3) Generative AI and natural language processing (NLP)
Businesses use advanced AI algorithms such as natural language processing (NLP), to understand and respond to human language. This tech helps determine what customers are asking and their sentiment. Combining it with generative AI helps provide relevant, engaging, and empathetic replies. This approach builds a stronger bond with customers and improves their experience.
4) Machine learning
Machine learning is a type of AI that allows computers to learn without being explicitly programmed. Its capabilities are used in customer service to identify patterns in customer data, such as finding common customer issues and customer churn. Later, this data can be used to improve customer service by providing more targeted support and preventing customer churn.
5) Intelligent workflows
In the traditional workflow, customers have to wait in a long queue to speak to an agent and then transfer to multiple departments before resolving any issues. And this can be a frustrating experience for customers.
This is where we need AI-powered intelligent workflow to eliminate the problems and route customers to the right place at the right time. AI can do this by analyzing customer data, such as the type of issue, the customer’s language, and the customer’s sentiment. This data can then be used by agentic AI systems to match the customer with an agent who has the expertise and skills to resolve their issue quickly and efficiently.
AI-powered workflows can provide several benefits for businesses, including:
- Reduced customer wait times
- Improved customer satisfaction
- Increased agent efficiency
- Reduced costs
This approach ensures quicker and more efficient support, eliminating unnecessary wait times for customers.
6) AI-powered analytics
AI technology excels in analyzing vast amounts of customer data to derive actionable insights. By understanding customer behavior, preferences, and pain points, businesses can make informed decisions to optimize processes, and continually improve customer service.
7) Multilingual AI support
Make communication easier with multilingual support using Conversational AI. This technology understands a customer’s language and translates the conversation instantly, making support more convenient.
Enhancing the personalization of conversations is achieved by incorporating multilingual support automation software into your customer service solution. The AI gains access to valuable customer information, including location, device used, buying preferences, conversation history, and more. This holistic understanding enables the AI to provide tailored support, creating a more personalized and effective interaction.
For instance, consider a situation where a bot automatically detects the customer’s language through factors like location and the chat window text. This advanced technology ensures a smooth and responsive multilingual support experience.
How can AI improve customer service?
AI in customer service refers to using intelligent technology to create fast, efficient, and personalized support experiences. This includes - automating interactions, streamlining workflows, assisting agents, saving time, and bringing down costs.
AI can bring significant enhancement to customer service by automating responses, analyzing customer sentiment, and providing personalized assistance. It reduces wait times, enhances agent efficiency, and identifies trends in customer interactions to optimize support operations, leading to increased customer satisfaction and loyalty.
Here’s how businesses can improve their customer service and grow globally:
1. Boost self-service with AI-powered chatbots and knowledge-based articles
Businesses can use AI to handle routine customer queries, provide information, and initiate basic issue resolution even outside regular business hours. This not only enhances the overall customer experience but also saves costs by automating routine tasks.
For instance, DevRev’s AI agents can deflect customer queries by
- Engaging them in a conversation
- Providing relevant answers
- Leading them to the right articles for more information
Its Retrieval Augmented Generation (RAG) pipeline pulls information from a number of sources, including knowledge base articles, past conversation history, and support tickets to provide the most accurate response. This allows you to handle complex,multi-part inquiries with ease.
The best part about DevRev’s chatbot platform is that it can be deployed within minutes and is unrestricted by the limitations of chatbot builders and decision trees. This is a departure from the conventional way of building bots, towards a more dynamic, self-learning, and truly AI landscape.
Here are the results MadRewards saw after using an AI-native support platform to
- Optimize support operations
- Scale down the support team
- Maintain the same level of customer satisfaction
Before | After |
|---|---|
Manual processes with email based support | Manual processes with email based support | AI-powered chatbot deflecting a huge portion of the basic incoming queries, in addition to email and live chat support |
Huge customer support team spread across the globe, supporting customers in a complex, manual process | Customer support scaled down to a team of two, handling complex queries that require human intervention. |
Significant cost overhead | Cost-effective and optimized support operations, while maintaining customer satisfaction |
2. Empower support teams to be productive with AI agent-assist
Using AI helps businesses deflect simple tasks like answering initial questions, providing basic information, etc. This means the support team can spend more time on complicated issues that need human intervention.
AI can also go a step further and work hand-in-hand with human agents to make their work more productive and efficient. For instance, here’s how DevRev’s AI agents, powered by generative AI, makes the lives of human agents easier:
- Summarize conversations: Support agents can simply use the “/summarize‘’ command and get the gist of the conversation without losing the context to the finer details. This helps them quickly get started on resolving the problem, drastically reducing the customer wait time and queueing time.
- Rephrase replies: Human agents can also ‘Rephrase’ and ‘Change tone’ at a click of a button with the help of the AI agents. This ensures that customers get a clear, cohesive response to their queries as soon as possible.
- Knowledge base creation: While the human agent works with the customer to resolve their query, the AI agent works in the background, analyzes customer conversations, and generates a comprehensive knowledge base article. Once created, the article is shared with the team for approval and publishing. This process enables AI to continuously self-learn and respond to similar questions that arise in the future, further boosting the deflection rate.
3. Gain deep insights for faster decision making with AI-powered analytics
AI-powered analytics provide comprehensive insights into customer behavior, support trends, and service performance. vast amounts of data quickly and accurately, identifying patterns and predicting future needs. You can use these insights to make informed decisions, optimize processes, and enhance customer experiences.
For example, with DevRev’s powerful RAG analytics, you can:
- Track queries, answering rate, and generated Q&A.
- Discover the most relied-upon content by users.
- Analyze the daily breakdown of answered vs. unanswered questions.
- Gauge agent effectiveness with an interactive answering rate line graph.
- Get actionable insights by analyzing performance by channel and refining your knowledge base with unanswered questions.
And more!
DevRev also provides PLuG user observability that lets you identify potential issues before your customers raise it as a problem. This enables you to proactively fix them before it hinders your customer experience.
Here’s how Aditya Birla Capital proactively navigated blind spots in their app
The challenge: The product and design teams at Aditya Birla Capital, a leading finance and Fortune 500 company in India, initially relied on quantitative data or anecdotal feedback from customers to improve their product.
They could not get a detailed understanding of their user interactions to identify the problems their users encountered while navigating the app.
The solution: DevRev’s PLuG observability gave the teams at Aditya Birla Capital a window that shows them how real life users are engaging with their product. This allowed them to see how users interact with the product rather than hoping that users interact as intended.
The result: With real-time insights, they were able to optimize their app’s interface, making it more intuitive and user-friendly, ultimately enhancing the user experience and keeping customers satisfied.
What are the challenges of AI in customer service?
The hardest challenge most businesses face with AI in customer service is finding the right tech partner who suits their needs, with blockers being around:
- High initial costs and integration complexities
- Ensuring data privacy and security is crucial
- Well-trained AI models with human empathy,
- Continuously monitoring and updating of AI models as required to maintain accuracy and relevance
It’s important that you choose a tech vendor who has AI built into the very foundation of the product, and not just bolted on in an attempt to be relevant.
Get your company ready for tomorrow with AI in customer service
AI not only cuts costs but also improves customer service interactions. It’s not just about customer service—it helps your entire company grow globally. Gear up for the digital future now and secure lasting competitive advantages of using AI in customer service.
Support platforms, such as DevRev, that has AI infused in its foundation and is powered by generative AI, enables you to leverage AI across your support process:
- Enhance self-service
- Boost deflection rates
- Provide agents with a powerful AI-ally
- Get accurate numbers for fast decision-making
And ultimately, improve customer experience. All in one go, with DevRev.
Get started today.
