Exceptional customer service isn’t just a preference anymore. AI tools reduce friction at every touchpoint to increase agent efficiency and create more personalized experiences for customers.
Automation tools like chatbots quickly answer routine questions and can direct more complex inquiries to agents. Conversational AI tools can also generate content to send to customers, allowing teams to focus on high-level problem-solving and relationship-building.
Automation
One of the most common applications of AI in customer service is automation. Most companies use automated responses to help customers solve low-hanging fruit problems without involving human agents. Automation tools like chatbots, email bots, and other solutions allow for quick, efficient response times and provide a consistent experience for the customer.
Another way businesses leverage automation is by using it to improve self-service. By building out a knowledge base and FAQs, customers can often find the answers they need to resolve their own issues. This reduces strain on the support team and allows them to focus on more complicated cases.
Many companies also leverage AI to streamline their agents’ internal processes and improve customer experience. For example, intelligent triage automatically analyzes a ticket to determine the customer’s intent and language, and then routes it to the right agent to help resolve the issue. This helps eliminate wait times, makes it easier for agents to resolve tickets, and avoids the need to transfer the customer back and forth between departments or reps.
Additionally, AI can automate workflows involving written documents and forms, including W-2 forms and customer correspondence. This helps to reduce the number of documents an employee needs to handle and can save time by removing the need for repetitive tasks like scanning, data entry, and sorting.
As a result, the use of AI in customer service can make employees more efficient and happier at work. It helps reduce the burden of repetitive, manual tasks, which can help combat employee burnout and lead to better outcomes for the customer. In addition, intelligent tools can make it easy for teams to collaborate with a single view of all customer messages and clear visibility of their task load to avoid duplication and miscommunication. By streamlining processes and reducing customer friction, companies can deliver on their promise to provide exceptional customer service.
Sentiment Analysis
Whether through surveys, ratings, social media, chats, or another feedback channel, customers often use words and phrases to describe their satisfaction with your product. Sentiment analysis quantifies and monitors customer sentiment so you can identify and respond to any potential faulty features or service issues before they become an escalation.
Sentiment analysis algorithms can interpret a wide variety of text, including speech and video. They scour reviews and customer conversations to identify positive, negative, or neutral sentiments and determine emotional tone. Using natural language processing and machine learning, the software can recognize patterns in language to make predictions about future trends.
However, it’s important to note that not all algorithms are created equal. The more complex the language, the more difficult it is for algorithms to identify the sentiment correctly. This is because the system needs to understand context and tone, such as sarcasm or irony, which can be difficult to detect in text alone. Sentiment detection also struggles with pronoun resolution, which is the ability to understand which antecedent is referring to a particular word or phrase.
Aside from detecting customer sentiment, automated processes like voice and text analysis can be used to prioritize pending issues and assign them to agents who can best resolve them. This helps prevent case backlogs and ensure that your customers receive speedy support, which has been shown to increase customer satisfaction and brand loyalty.
AI can help sift through customer feedback to identify key patterns and provide predictive analytics to help you plan for the future. This type of data can be useful to cross-organizational teams, such as sales and marketing, and individual agents who can use this information to tailor their approach to the customer.
Rhythm Energy, an oil and gas company, used sentiment analysis and automation to streamline workflow and improve customer experience. By implementing the technology, the team was able to save over a thousand hours in their workweek while maintaining the same level of high-quality customer service. With this time saved, they were able to allocate more resources to training new hires and other initiatives that improve the overall customer experience.
Routing
Ticket routing is an often time-consuming, laborious task that can lead to errors and frustrated customers. AI can automate this process, allowing your agents to focus on resolving complex interactions. This also allows your support team to operate round the clock, making your brand accessible to night owls and early risers alike.
Using Levity’s automated text analysis tools, you can create a custom AI model that processes your data according to the labels you specify. This is a powerful tool for companies that receive a large volume of customer messages. You can automatically categorize data in a streamlined, time-saving workflow by identifying key phrases and sentiments.
This means you can send the right information to the correct team member—at the exact moment they need it. You can also use this feature to analyze common questions and identify trends in your customer service data. By noticing patterns, you can make product changes that improve the user experience or eliminate certain problems altogether.
Advanced chatbots can greet customers with a friendly hello, answer simple questions, and connect them to the right agent. These bots can come pre-trained to understand the top issues specific to your business, enabling them to quickly respond to customers with a personalized message. The more they learn, the better they perform—research shows that customers are more satisfied with quick, consistent responses.
With access to the right data and customer context, chatbots can also provide proactive recommendations for a more personalized and engaging experience. This could include products or services they’ve shown interest in, their website behavior, buying preferences, conversation history, and more.
One of the most effective ways to use AI in customer service is through predictive analytics, which provides an overview of your customers’ past and potential future behaviors. This data enables you to anticipate their needs and predict what they might do next. By understanding their motivations and habits, you can create a more targeted marketing strategy to keep them engaged with your company and build loyalty.
In addition, you can help your customers resolve their problems faster by providing them with more relevant escalation paths. For example, if an agent does not resolve a customer’s issue in a timely manner, you can recommend that they escalate the request to a supervisor or manager.
Analytics
AI tools streamline support processes by automating repetitive and time-consuming tasks and enabling agents to focus on high-value work. However, it’s important to note that automation is not meant to replace humans. Instead, it should serve as a tool that makes the agent’s job easier and provides them with additional data and insights to better serve customers.
One of the most common forms of customer service AI is chatbots. Chatbots help businesses handle simple requests, such as product inquiries or billing questions, freeing up human resources to address higher-value customer issues and provide more personalized support.
Many AI tools also have the capability to understand a variety of languages, allowing companies to support a global customer base. This is particularly helpful when it comes to handling customer feedback, as AI can sift through comments from multiple sources, including social media and reviews, and identify sentiment, tone, and vocabulary.
With the right software, AI can automatically sort and prioritize incoming tickets. This allows teams to respond to more customers in less time and reduce their average ticket handle time, which leads to a happier, more satisfied customer.
Another benefit of customer service AI is its ability to analyze large amounts of data. This can be used to identify common themes in customer support queries and help improve your product. For example, if you see that your customers are having trouble with a specific feature, AI can recommend ways to fix it or train agents to resolve these issues more efficiently.
AI can also help you identify key customer trends in order to make informed business decisions. For instance, if you notice that your team is frequently contacted about a particular aspect of your product, AI can suggest that you expand this section in your knowledge base or create new articles on the topic.
AI is becoming more sophisticated and able to handle more complex problems that require a deeper understanding of your product. This helps your business save time and money while creating a better experience for your customers, which leads to loyal brand advocates who will promote your product for you.
