Artificial intelligence (AI) technology is making its way into almost every industry. One industry that we’re seeing it take over duties in is customer support. Utilizing AI in your business is an excellent way to gather data and improve the customer experience. With that being said, there are advantages as well as drawbacks.
AI in customer support
Now more than ever, companies have access to big data and advanced analytics that make their lives easier. While these tools are excellent for scaling a business, they can also be used to improve customer support. AI is becoming commonplace in many customer experience models, and with good reason.
The world of customer support has been evolving alongside technology. When a customer has a bad experience, they’re going right to social media to tell everyone about it. Customers want their issues resolved immediately, and that’s where AI comes in.
Examples of AI in customer support
There are several ways AI can be used in customer support to benefit the customer as well as the employee.
Chatbots and conversational AI
When you think of customer support AI, the mind usually goes to chatbots. Typically, chatbots are used to easily and quickly resolve customer support inquiries. For example, customers can ask a chatbot about a variety of questions and there will be pre-programmed answers. Chatbots aren’t necessarily powered by actual AI.
Conversational AI takes the chatbot one step further. This technology allows chatbots to interact with customers more accurately, instead of repetitive answers. Conversational AI allows customers to get the answers they need to more complex questions quickly, and helps companies deliver excellent customer support.
Natural language processing
Simply put, natural language processing (NLP) is a branch of AI that gives machines the ability to understand language the way we as humans would. This capability allows technology such as chatbots to interact with customers in a more personal way. NLP is commonly found in digital assistants, as well.
Customer sentiment analysis
Sentiment analysis is data gathered to tell how a customer feels. AI tools can be used to analyze a customer support request to find the tone and how they were feeling when they sent it in. This will allow agents to properly address the support request and be mindful of the emotional undertones that can signal if a customer is unhappy, dissatisfied or showing signs of wanting to churn.
AI assistants
As AI continues to get smarter, why not use it as an assistant? It’s a great tool for assisting customers as they go through onboarding and trying new features. AI can also assist agents utilizing NLP and other tools to help them understand and solve customer support tickets quickly.
Machine learning
For customer support, technology needs to be ever-evolving to fit new needs. Machine learning (ML) is what gives AI applications the ability to learn without someone having to program them anew each time. Machine learning is what gives something like ChatGPT its edge.
Automatic ticket creation
Customer support tickets can be overwhelming on both the customer and agent ends. AI can streamline the process with automatic ticket creation and routing, and filtering out tickets that can be solved with chatbots.
Automatic ticket routing
Ticket routing is another area where AI can be of assistance. Automating this task will save agents time and energy that can be better spent on customer support.
5 ways AI can improve your customer experience
Anticipate and predict customer behavior needs
Technologies such as predictive modeling, ML, and data analysis allow businesses to predict customer behavior and issues that will result in a support ticket. Using session replay tools to do this is an excellent option. Having access to session replay tools can allow agents to see that something isn’t working properly, or that a customer is struggling on the page. This can help identify room for improvement in the customer experience.
Provide proactive support
Did you know only 1 out of every 26 customers will ever report a problem to support? The rest will typically give up and stop using the service. Session replay tools give agents the opportunity to reach out to a customer when there’s an issue immediately. If agents don’t have to depend on customers reporting problems, they can be a whole lot more proactive and prevent churn. Some session replay tools utilize AI/ML to look for patterns, identify issues and send alerts to agents and developers.
Personalize customer support
In the same vein, ML/AI can be used to predict what problem individual users are likely to run into and create nuanced customer personas. This gives agents the ability to provide customers with more personalized support. Using predictive modeling to identify patterns and determine what a particular user is likely to do next or what they want can be very powerful. Personalization can also help boost customer loyalty. In fact, a study showed that 71% of consumers expect companies to provide personalized experiences.
Reduce support burdens
AI chatbots that use NLP and customer sentiment analysis can reduce support burdens by dealing with level 1 support requests. Just remember that there is a right and a wrong way to use automation because too much of it can be a turn-off. Chatbots can also function as powerful data-collection tools.
Provide multilingual support
Support teams can be expensive and difficult to scale, especially if you operate in various markets. Leveraging AI for multilingual support can be just the ticket and help you keep costs down while providing top notch service for all of your customers. In fact, 69% of global consumers believe that it’s important that brands offer the entire customer experience in their native language. Case in point: the company Unbabel has successfully implemented multilingual customer support using AI to better serve their consumers and helps other companies do the same thing.
The drawbacks and challenges of using AI in customer support
It’s important to remember that no technology is perfect. Using AI for customer support is going to have challenges and drawbacks.
System integration issues
With so many applications and software available, make sure that the AI tools you choose will integrate with your current systems and all the tools in your tech stack. AI should fit into your infrastructure seamlessly, not make it more challenging. You should also make sure that AI tools won’t affect load times on your app.
Evolving support team
As AI becomes an integral part of the customer support team, it’s going to make some jobs obsolete, including:
- Live chat boxes
- Sorting customer support tickets
- Automated emails
- 24/7 customer support
With that being said, the need for humans in customer support will still be essential because people still prefer talking to people over chatbots, but jobs are going to change. For instance, AI is going to save customer support agents a lot of time by filtering out requests that can be completed with chatbots. This will give agents more time to focus on complex level 2 and 3 support requests and other parts of their job.
AI will also make it easier to analyze large portions of customer data to improve the customer experience. It will also give management a better way to analyze employee productivity. Overall, AI is going to improve customer support jobs by taking over menial tasks and giving employees more time for other tasks. This may mean taking on other duties to fill gaps that employees may not have been hired to do, or want to do, so flexibility going forward is going to be a must.
Customer preferences
Many customers have a negative view of AI in customer support. This opinion typically stems from a bad experience with a chatbot or something along those lines. While AI can be frustrating, when implemented properly it should ideally improve the customer experience. AI is also rapidly improving every day.
Conclusion
The bottom line is that AI isn’t going anywhere anytime soon. Customer support professionals should embrace this technology to make their lives easier. While there is a negative association with AI, businesses shouldn’t be afraid to embrace this technology to improve their customer experience. The important thing is implementing it the right way to work for you AND your customer base.
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