AI-Based Customer Support Is Easy to Implement

AI-Based Customer Support Is Easy to Implement

Managing engagement and communication across all channels in a way that meets customers’ expectations is challenging, but necessary. McKinsey notes that about two-thirds of millennial consumers expect real-time customer service when they reach out to a business, and about 75% of all consumers expect service consistency across all channels. Advancements in AI based customer support is making it easier than ever to achieve this.


Why AI-Based Customer Support is a Game Changer

AI-based customer support comes with many benefits, not the least of which is that AI tools like chatbots make it possible to respond to customers 24/7, no matter what device they’re using or where they’re located. Gartner lists three main ways that AI improves customer support, and it’s not just about responding to consumers in real time. They are:

  • Efficiency – AI helps improve processes by augmenting and automating tasks previously relegated to humans. This isn’t just about automation. Augmenting human work with AI could mean, for example, using AI to generate a summary after a human agent completes a call. 
  • Enhanced customer experience – AI improves customer experience in direct-to-customer ways (e.g., the 24/7 chatbot example, above). But it also provides invaluable behind-the-scenes support to customer service teams by, for example, surfacing relevant insights during a service call or chat. This reduces or eliminates the need for service agents to hunt around for the answer they need. Additionally, AI-powered knowledge management systems help customers find the right information on their own. 
  • AI-driven insights – Analyzing data is a slog, plus it’s easy to make mistakes or miss important insights. AI support tools use machine learning to act on data-driven insights that inform agent interactions, improve processes based on common customer issues, and personalize service across the various touchpoints and channels. 

All of this works together to enhance the customer experience. Even when operating behind the scenes, AI helps agents and customers get the answers they need more quickly and efficiently than if everything had to be done manually.

Impact of AI for Customer Service

According to a McKinsey’s 2022 Global Survey on AI, some of the most adopted AI use cases are those that involve customer service functions. These include service operations optimization, customer service analytics, and contact-center automation. Using AI for customer service support can impact the entire customer experience. It contributes to:

Faster response times 24/7 availability equals fast – often instant – responses to customer inquiries. Chatbots can triage questions and direct people to service agents if needed, but they can also route customers to self-serve options or use ML to respond directly in context.  

Predictive analytics – A standout feature of AI is that it can analyze large datasets and use ML to make predictions. AI tools use customer behavior, purchase history, and interactions across channels to offer proactive solutions based on customer prompts (e.g., auto-completing a search query, recommending information based on a customer’s past interaction history, etc.) 

Enhanced efficiency – Another standout feature of AI is automation, which helps businesses cut costs in a few different ways. Automating tasks that are repetitive, time-consuming, and easy-to-delegate-to-a-robot means that you can do more with smaller support teams. Tasks like support ticket management, sentiment analysis, and wait time updates can be managed by AI. Since AI can handle multiple queries simultaneously, it provides an extra layer of backup for small teams.

Implementing AI-Based Customer Support

The best way to approach the implementation of AI customer support is to define your needs and map them to specific goals. Are you looking to reduce response times, handle high volumes of queries, or personalize customer interactions? All three?

Being specific is the best way to find a solution that integrates with your existing customer support infrastructure. Keep in mind that technology is only one part of the equation. Your staff will need training and support so they can leverage AI tools effectively. And remember, providing human support remains a crucial ingredient in delivering good customer experiences. 

AI comes with some specific challenges including: 

  • Data privacy – Customers trust you with their information. The system you choose should be enterprise ready, meaning they have processes and features in place to safeguard customer data. 
  • Technical roadblocks – Given the complexity of AI systems, it’s essential to have robust IT support to help with onboarding, integration, and deployment. 
  • Team resistance – Change can be daunting. Some team members might resist the shift to AI for a variety of reasons, not the least of which is they’re worried about it replacing them. Make sure you highlight to AI-enabled support tools are meant to enhance human customer support, not replace it.

Considerations When Choosing An AI-Based Customer Support Solution

If you’ve just begun researching AI customer support software, the first thing you should do is make sure it does what you need it to. It should be able to scale as your business grows – and your customers’ inquiries grow along with you. 

Test drive whatever tools you’re considering and make sure they’re intuitive and easy to use. Complex tools that are hard to learn can do more harm than good. Your team should be able to learn a new system quickly so they can begin benefiting from it quickly. And here’s a pro tip: go for a vendor who’s got your back, someone who provides the support you need to guide you when things get glitchy.

Shop around. Compare what’s out there, read reviews, and consider customer feedback from other businesses who have experience in whatever platform you’re considering. You should also circle back with your customer service team to see what would be helpful to them when it comes to features and usability. 

The Future of AI in Customer Support

The landscape of customer service is shifting due, in a large part, to AI. Companies can use AI to analyze their customer data and provide hyper-personalized support. Automated personalization at this level, combined with tools like chatbots and comprehensive knowledge bases, provide the level of support customers have come to expect (even demand).  

Innovative new tools like AI-driven voice recognition systems are adding to the adoption of AI in customer service while predictive analytics allow businesses to peer into the future, anticipating customer needs based on historical patterns and interactions. 

Self-service portals in industries like healthcare, finance, and banking are another rising trend. They make it easy for people to schedule appointments, make transactions, and access knowledge repositories—all without human intervention. The potential ROI of investing in AI for customer service is strong. They enable support teams to assist more people, make them more efficient, and provide better service.