Key Takeaways:

• AI omnichannel customer service is an integrated approach that uses artificial intelligence to deliver seamless, personalized support across all customer touchpoints.
• Unlike multichannel support, omnichannel enables customers to switch channels without repeating themselves or losing conversation context.
• Implementation requires four key steps: building your tech stack, integrating systems, creating routing strategies, and developing self-serve options.
• Benefits include faster resolutions, lower churn, personalized experiences, and greater customer loyalty.
• Future trends point toward hyper-personalization, predictive analytics, and AR/VR integration in customer service.

If 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. 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: an automated software system that uses artificial intelligence to handle customer inquiries, resolve issues, and perform tasks without human intervention.

In this guide, we dive into the basics of A I omnichannel customer service , provide a quick overview of how you can implement it, and discuss how AI will drive omnichannel experiences in the future.

What is AI omnichannel customer service?

AI omnichannel customer service is an integrated approach that uses artificial intelligence to deliver seamless, personalized support across all customer touchpoints, including chat, email, phone, and messaging, while maintaining conversation context as customers move between channels.

Omnichannel customer service is the gold standard for how you treat customers today.

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 the traditional, 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 around the clock 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 scalability limits 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, and instead of pressing 1 for this and 2 for that, 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?"

omnichannel vs. multichannel customer service

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:

Quick guide to implementing AI omnichannel customer service

Preparing for implementation can be overwhelming. Where should you start, what tools would you need, how much would you need to invest upfront?

The four key implementation steps:

1. Build your tech stack – Select AI agent, CRM, and complementary software
2. Lay the groundwork – Integrate systems and build workflows
3. Create a routing strategy – Define how channels work together
4. Build self-serve options – Develop knowledge bases and self-service resources

Let's dive into each step in detail.

Step 1: Build your tech stack

Primarily, you need two types of tools: ones 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.

When evaluating AI agent platforms, look for ones that use generative AI to produce more natural, human-like responses while also being capable of executing scripted workflows. This results in higher Automated Resolution rates - the percentage of customer inquiries fully resolved by AI without human intervention - across channels. A strong AI agent delivers fast, accurate, and personalized responses 24/7 and at scale. Here's how it helps you:

• Improved customer experience: The AI agent ensures a frictionless experience by quickly resolving queries and generating personalized responses.
• More free time for your support team: The AI agent handles routine customer queries independently, allowing your support team to work on more strategic tasks or invest time in upskilling.

CRM

A CRM (Customer Relationship Management system) is a software platform that stores and organizes customer data, interaction history, and relationship information. 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 ("where is my order?") 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.

Step 2: Lay the groundwork

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:

• Integrations help automate processes: Suppose a customer wants to modify the delivery address for an order. There's no such built-in option, so they reach out to support via chat. If the AI agent is integrated with your order management system, it can modify the address without manual effort.
• Data availability is vital for personalization: Your AI agent needs information about customers to generate personalized responses. This includes data related to customer segments, order history, and previous interactions.

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.

Step 3: Create a routing strategy

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.

Step 4: Build self-serve options

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. A knowledge base is a centralized repository of information - including FAQs, how-to guides, policies, and product documentation - that customers and AI agents can access to find answers. Just like a CRM is home to customer data, the knowledge base accommodates information related to processes, features, and 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

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.

Common support channels

An omnichannel system can integrate any support channel. Here's a quick rundown of support channels you might include in your omnichannel setup:

• Live chat: Customers love real-time support, and so should you. Live chat can filter out a large volume of queries because it's a low-effort, fast-resolution support channel.
• Email: Email is the workhorse of customer service, but it's generally slow. An AI agent can help deliver faster email responses. Email's popularity and AI-powered speed make it an excellent support channel to include in your omnichannel setup.
• Phone: To become a viable part of your omnichannel setup, you need to automate phone support using voice AI. It's not only scalable, but it's also a much better experience for customers than pressing buttons trying to navigate an IVR menu.
• SMS: Texting is quick, personal, and async, making it a great channel for quick updates, confirmations, and handling simple issues on the fly.
• Others: Other popular support channels include social media, self-service portals, community forums, and more.

Benefits of AI omnichannel customer service

Omnichannel customer service sounds great in theory. But does it make an impact where it matters - your bottom line and customer experience? Here's how investing in omnichannel customer service can help:

• Faster resolutions: 50% of customers are less likely to spend money with a business that takes longer than expected to respond. Since a large portion of the process is automated, customers don't have to repeat themselves, and reps always have context before receiving a transfer from another channel, resolutions are generally faster.
• Lower churn: Customers churn when they don't get responses on time and are transferred between departments while having to repeat their problem at every transfer. Omnichannel offers a far better experience and helps retain customers through great service. According to Bain & Company , a 5% increase in customer retention can increase a company's profits by 25% to 95%.

• Personalized experience: Omnichannel systems can use data from all channels to personalize responses across the board. This helps personalize responses and is valuable for various internal decisions related to upselling and feature introductions.
• Greater customer loyalty: The best way to build loyalty? Address your customer's most pressing problems. A 2022 Netomi survey reveals that 43% of customers feel long wait times are the most frustrating part of customer service. AI-powered omnichannel support can eliminate this problem at the source, improve CX, and help you build a loyal customer base.

Future trends in AI omnichannel customer service

AI will keep raising the bar for what customers expect from omnichannel support. Here's a quick look at where it's heading.

Hyper-personalization at scale

Hyper-personalization goes well beyond using a customer's first name in an email. AI analyzes customer behavior, preferences, and interactions across all channels and uses them to create genuinely individual 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

Predictive analytics offers insights into your customers' 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.

AI in augmented and virtual reality (AR/VR)

Video calls are currently one of the most interactive support channels. You can see the customer, share your screen, and walk them through 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.

The concept isn't new: IKEA first did it back in 2013. But as AI technologies and AR/VR devices mature, these service channels will have a growing impact on service quality.

Get prepared: Plan for omnichannel customer service

Create an implementation roadmap and test your omnichannel systems before taking them live. A small glitch could translate to a major problem - 17% of US customers could walk away from your brand after just one bad experience, and 59% 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.

Frequently asked questions

What is the difference between omnichannel and multichannel customer service? Multichannel customer service offers support across multiple channels that operate independently, while omnichannel integrates all channels so customers can switch between them without losing context or repeating information.

What channels can be included in an omnichannel setup? Common channels include live chat, email, phone, SMS, social media, self-service portals, and community forums. Any customer touchpoint can be integrated into an omnichannel system.

What is an AI agent in customer service? An AI agent is automated software that uses artificial intelligence to handle customer inquiries, resolve issues, and perform tasks across multiple channels without requiring human intervention.

How does AI improve omnichannel customer service? AI enables 24/7 support at scale, maintains conversation context across channels, delivers personalized responses based on customer data, and automates routine inquiries to free human agents for complex issues.