How to build a world-class AI customer service team
Templates and guidance on building a customer service team that uses both AI and human agents to their fullest potential.
Learn MoreIf there’s one crystal clear way to differentiate your business from your competitors, it’s to excel in your customer service. 80% of customers say the experience a company provides is just as important as its products and services, and 88% say good customer service makes them more likely to purchase again.
Unfortunately, only 45% of customers are “very satisfied” with their interaction with a business.
But there’s a solution that can turn the tide: omnichannel customer service. Offering faster resolutions and a seamless switch between support channels, omnichannel customer service is a noticeably better experience than disparate channels working in a silo.
But here’s the caveat. In order to achieve this with a traditional customer support model, you need hundreds of support agents to offer real-time and personalized responses across all support channels. To deliver fast and personalized responses on multiple channels (and at scale), you either need superpowers or an AI agent. We recommend an AI agent.
In this guide, we dive into the basics of AI omnichannel customer service , provide a quick overview of how you can implement it, and discuss how AI will drive omnichannel experiences in the future.
Omnichannel customer service is an integrated and seamless approach to delivering customer service across all support channels. It’s the gold standard for how you treat customers in today’s no-excuses business world.
Let’s think it through. How exactly would you deliver a unified experience across channels? What’s the best way to ensure that customers can leave one channel and pick up conversations on another, as if they never left?
There are two ways.
The first is a prehistoric, human-powered method. Your systems are integrated and talk to each other, so customers have the option to switch channels without having to reinitiate conversations. But on the backend, support agents are working 24/7 to maximize the system’s speed, accuracy, and quality.
Then there’s another method powered by AI. An AI omnichannel customer service system addresses the lack of scalability of the human-powered method, assuming the role of a support agent. It answers customer queries over chat, email, and phone while retaining context. The traditional method works, but an AI agent works for you.
Let’s see how. Suppose your customer’s smart watch stops working while they’re at work. They initiate a chat via your website, but there’s no “press 1 for that, press 2 for that” nonsense; they’re directly connected to an AI agent. They state the problem, and in response, the AI agent offers a few troubleshooting steps. But since they’re at work, they request the AI agent to send this information over email to have a look later.
When they’re commuting back home, they have a few minutes to spare and decide to call your company. The voice AI agent verifies their identity and continues the conversation. The voice AI agent could say something like, “Were you able to resolve your problems with the troubleshooting steps shared earlier?”
Multichannel customer service means delivering support on every channel your customers use. If you provide multichannel support, your customers can get in touch via live chat, email, and phone, but they won’t be able to transition from one channel to another without reinitiating their conversation.
Omnichannel is an evolved version of multichannel customer service. It aims to deliver consistent experiences for customers across channels by integrating various systems. Customers can switch the channel according to their preference without the need to repeat themselves.
For example, when a customer wants to switch to a phone call from live chat, they can call support, verify their identity, and continue the conversation with a support agent without explaining everything from scratch.
Here’s a quick summary of the differences:
Preparing for implementation can be overwhelming. Where should you start, what tools would you need, how much would you need to invest upfront? Let’s dive into a quick overview of how you can implement AI omnichannel customer service and get these questions answered.
Primarily, you need two types of tools — tools that can perform support-related tasks using AI technologies and ones that can store data, whether that’s customer data or information related to your product and processes. Here are the tools you can add to your tech stack:
AI agent
Your AI agent is the most critical piece of software for two reasons. One, the AI agent is what your customers directly interact with. Second, it provides the AI technologies needed to build an automated omnichannel customer service workflow. As the first order of business, look for an agile, fast, and friendly AI agent that can automate responses across all channels — email, messaging, and voice.
Ada’s AI Agent is the only fully generative, omnichannel customer service automation platform, while other tools take a hybrid approach, combining generative AI and traditional workflows.
Translation?
Ada’s AI Agent generates more natural, human-like responses and is capable of executing scripted workflows. This results in higher Automated Resolution rates across channels. It delivers fast, accurate, and personalized responses 24/7 and at scale. Here’s how it helps you:
CRM
The CRM is where your customer data lives. When a customer is sent over to another channel, the support rep should be able to pull customer data and interaction history from the CRM. This ensures the rep has the information necessary to deliver great service. An AI agent can do the same thing — understand customer preferences and generate more personalized responses.
For example, when a customer asks for shopping recommendations on your ecommerce website, the AI agent looks at the customer’s previous purchases, sees that the customer recently bought a sweatshirt, and upsells them on a matching product like sweatpants or slippers.
Other software
Various tools can complement an AI agent in delivering an omnichannel customer experience. For example, the AI agent can interact with your inventory management software to answer WISMO queries or modify orders, or with your invoicing software to share a copy of an invoice with a customer on request. The specific systems depend on your business and workflow.
Once your tech stack is ready, it’s time to integrate these tools and build a workflow. Ideally, you want to integrate every piece of customer service software you use. The idea is to allow information to travel easily between systems while ensuring data security.
Your software solutions likely have various ready-to-use integrations . If they don’t offer this for one or more systems in your stack, you’ll need to integrate them using APIs. Here’s why integrations are important:
After you’ve integrated the systems, set up workflows. When a customer requests an update in their invoice, the AI agent should know where to look (your invoicing software) for information and execute the change for the customer.
Understanding the dynamics between support channels helps you determine how they’ll work together and the best way to use them in a specific scenario.
For instance, when your customer starts a conversation in WhatsApp and their query requires a technical expert to jump in, the AI agent should be trained to schedule a callback or route the customer to your call center, where an agent can take over.
Don’t be pushy, though. Forcing your customers to jump on a call or write a detailed email when they’d prefer to continue using chat is the last thing you want to do. Just recommend a more efficient support channel for their query and give them the option to continue using their preferred channel.
Self-serve options aren’t exactly “support channels,” but your customers want them. 67% of respondents mentioned they prefer self-service over speaking to a rep in a survey. Self-serve options not only allow customers to find answers independently but also act as a resource for your AI agent.
Let’s use a knowledge base as an example. Just like a CRM is home to customer data, the knowledge base accommodates information related to processes, features, policies — basically everything related to your product, service, and company.
When a customer asks an AI agent how they can request an account statement, the AI agent can look up the information in the knowledge base and generate an accurate answer. The knowledge base also enables customers to self-serve and reduces the load on your support desk.
As experts explain in an HBR article :
“Corporate investment in self-service technologies has been enormously effective at removing low-complexity issues from the live service queue, and most companies we’ve studied report a steady reduction in such contacts over the past few years.”
A knowledge base is an excellent tool to deliver self-service, but the AI agent can also guide customers to other resources like video tutorials, FAQs, and interactive guides and walkthroughs.
An omnichannel system can integrate any support channel. Here’s a quick rundown of support channels you might include in your omnichannel setup:
Omnichannel customer service sounds great in theory. But does it make an impact where it matter s — your bottom line and customer experience? Here’s how investing in omnichannel customer service can help:
A 5% increase in customer retention can increase a company’s revenue by 25% to 95%
- Hubspot
AI is transforming customer service as we know it. Let’s take a quick peek at how AI will drive your omnichannel experiences in the future.
Hyper-personalization isn’t about using a customer’s first name in an email anymore. It’s about making your customers feel like you can read their minds. AI analyzes customer behavior, preferences, and interactions across all channels and uses them to create one-of-a-kind personalized experiences.
Let’s say a customer reaches out to you regarding a fairly basic issue. But they’re in no mood to play around. Their first message is, “I’ve been trying to set up an automated workflow using tool XYZ, but I keep getting an error. I thought this software was supposed to be easy to use! Please refund my subscription money.”
That may be a bit of an overreaction, but as sentiment analysis evolves, your AI agent will handle these situations more gracefully. The AI agent might assess the customer’s churn risk and current mood and generate responses accordingly.
For example, in this case, the AI could generate a sympathetic response — “Hi Nathan! Sorry to hear you’re having trouble automating your workflow with tool XYZ. Please find an overview of the process below. We’re also happy to schedule a one-on-one call to help you resolve the problem and answer any questions.”
Predictive analytics is like a crystal ball for customer service. It offers insights into your customer’s preferences and behavior patterns, allowing you to anticipate their needs and address potential concerns before they turn into bigger problems.
With predictive analytics, you can push CX beyond digital and physical barriers. Think about a potential customer shortlisting products on your website. They hope to narrow their choice down to a few items, visit your store to see these items, and then complete the purchase.
When the customer walks in, the salesperson has all the context needed to help the buyer continue their journey. In fact, they can also identify opportunities to upsell. The AI algorithm automatically generates suggestions based on products they explore online and previous purchases.
Video calls are currently one of the most interactive support channels. You can see the customer, share your screen, and handhold them when resolving a problem. Video calls have limited relevance, though. For example, if you’re a clothing company, you can’t help your customer with a sizing issue over a video call.
Picture this: You sell furniture through your ecommerce website. You have an in-house interior designer to help customers select the right designs and colors when shopping for furniture. A customer initiates a chat seeking help with choosing the furniture designs for their home.
Instead of relying on a CAD drawing or video recording of the customer’s house, what if the interior designer could help the customer choose furniture items using augmented or virtual reality? Customers can visualize the furniture sitting on their patio in 3D and get a much better idea of how that piece of furniture will actually look.
Sound fancy? IKEA first did it 11 years ago.
The concept isn’t exactly new, but as AI technologies and AR/VR devices mature, the effectiveness of these service channels will have a significant impact on service quality.
Create an implementation roadmap and test your omnichannel systems before taking them live. A small glitch could translate to a major problem — 17% of American customers could walk away from your brand after just one bad experience and 59% of them will leave after several bad experiences.
The most effective way to prepare? Choosing reliable software solutions. You can do everything right, but if the tool malfunctions, you lose reputation and revenue from loyal customers for good.
At Ada, we’re committed to helping you deliver exceptional customer service that helps you stay ahead of the curve with the latest AI technologies. If you’re eager to learn how Ada’s AI Agent can be instrumental in your omnichannel customer service tech stack, get in touch today .
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