It’s easy to get excited about AI and customer service. After-all, it promises to elevate the customer experience by making sure that every time a person reaches out to your company, they have a brilliant customer experience: personal, immediate and convenient support on their terms. But it doesn’t make sense for every company to adopt AI customer support agents today.
Here are the things you should consider when you’re evaluating whether or not to adopt AI to power your customer service.
How to Evaluate Whether You Need an AI Agent
#1. Volume of Tickets
The higher the volume, the more benefits you’ll reap with an AI simply due to the number of customers AI can manage automatically, optimizing support resources. The benefit of high volume, however, goes deeper than that. AI that leverages deep learning gets better from experience, and the more interactions it has, the smarter it will become. If an AI is managing a fraction of tickets in the first month, this would be expected to rise significantly higher over time with high volume. If you have lower volume, an AI can still impact your customer service, but its knowledge trajectory will not be as steep.
#2. Repeatable vs. Non Repeatable Issues
Do at least 40% of your tickets span repeatable issues? AI can learn how to offer high-quality responses to repeatable issues, enabling your human agents to manage the rest. If your company gets a lot of unique, first-time and complex scenarios, your support would be better managed by a combination of human and AI agents. Use AI to classify tickets and route it to the right agent automatically, so it helps your human agents perform even more effectively.
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#3. Business System Flexibility
Can the business systems your company uses for support tickets be accessed via APIs? A Support AI needs the ability to resolve, not just respond. To meet consumer expectations, it needs to handle both generic and account-specific inquiries. Depending on your business, resolving issues might be accessing an order management system to provide shipping status, tapping into a CRM to pull up loyalty information and help with reward redemption, or sync up to a booking engine to facilitate the rebooking of a flight. Being able to pull relevant data in real-time will provide the authority that consumers expect an AI to have.
#4. Training Data
AIs need to be trained, and the more data you have available, the more tickets it will be able to resolve and the higher the confidence it will have in providing a response. Training data can include historic emails, call center logs, social media exchanges, FAQs and other marketing collateral. If you don’t have access to this type of data, compiling a database of the issues and how the AI should respond will be your first step.
What will success look like for you? Is it how many tickets an AI can solve on its own versus needing to escalate to a human? Is it CSAT?
What metrics are you trying to improve? Many of our customers seek to decrease the amount of time it takes to resolve a ticket, the total cost it takes to resolve an issue and even monetization led by AI-driven personalized support.
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While many people have traditionally measured AI on its ability to behave like a human using the Turing Test, this is not what should be the focus. It should be on how well the AI can solve problems. How well it is at providing high-quality resolutions, how effectively it is supporting human agents with recommended replies and intelligent routing, the impact on the time it takes to close tickets, and how it is learning over time.
Asking how you are going to measure the success of your AI upfront allows you to set clear expectations. It’s essential that all of the stakeholders within the organization understand the AI training process, and that how well an AI performs on day 1 is not indicative of its overall impact. It will improve over time, but it needs experience.
#6. Support Channels
What are the most common channels your customers are reaching out on for support? AI Agents work well on email, social and Web/app chat. While AI Agents can deploy an omnichannel experience to provide the most impact, understand what your highest trafficked channels are to create a high-impact roll out plan.
AI-powered customer service is the future. Let’s chat and see how Netomi can help you transform your customer experience.
For more information on customer service, visit:
- Zendesk vs. Freshdesk: Which Is Better?
- Best Help Desk Software Platforms In 2021 [Features, Pricing, and More]
- 7 Ways to Provide Personalized Customer Service (Plus Benchmarks and Stats)
- What Is a Virtual Contact Center?
- Measures of Success: Our Top 10 Chatbot Evaluation Metrics
- Email Support: The Pros and Cons of AI Customer Service Tools
- The Best Chatbot for a Website in 2022 and Beyond [Review and Key Features]
- The 15 Best Knowledge Base Tools